8 Program Dependence.ipynb

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   "metadata": {
    "slideshow": {
     "slide_type": "slide"
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   },
   "source": [
    "# Program Dependence and Slicing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41b7944d",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
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   "source": [
    "We have so far explored control dependencies and data dependencies independently. These two concepts are related as they both represent cases of _program_ dependencies. In this chapter, we will define the program dependence graph, and use this to implement _slicing_."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2e388af0",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
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   },
   "source": [
    "## Control Dependencies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "de738d47",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
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   "source": [
    "First we need to include all the CFG-related code."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "f7fca29c",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "import javalang"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "fec08d09",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
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   "outputs": [],
   "source": [
    "class CFGNode:\n",
    "    def __init__(self, graph, method_name, ast_node):\n",
    "        self.graph = graph\n",
    "        self.method_name = method_name\n",
    "        self.ast_node = ast_node\n",
    "        \n",
    "    def __str__(self):\n",
    "        if type(self.ast_node) == str:\n",
    "            return self.ast_node\n",
    "        else:\n",
    "            return str(self.ast_node.position.line - 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "23585b1b",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class StartNode:\n",
    "    \n",
    "    def __init__(self, graph, method_name, ast_node):\n",
    "        self.graph = graph\n",
    "        self.method_name = method_name\n",
    "        self.ast_node = ast_node\n",
    "    \n",
    "    def __str__(self):\n",
    "        return \"Start\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "b420b7d9",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "import networkx as nx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "45290e3c",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
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   },
   "outputs": [],
   "source": [
    "class ProgramGraph:\n",
    "    def __init__(self, graph, start, end):\n",
    "        self.graph = graph\n",
    "        self.start = start\n",
    "        self.end   = end\n",
    "        \n",
    "    def nodes(self):\n",
    "        return self.graph.nodes()\n",
    "    \n",
    "    def edges(self):\n",
    "        return self.graph.edges()\n",
    "    \n",
    "    def successors(self, node):\n",
    "        return self.graph.successors(node)\n",
    "    \n",
    "    def predecessors(self, node):\n",
    "        return self.graph.predecessors(node)\n",
    "    \n",
    "    def reverse(self):\n",
    "        reverse_cfg = self.graph.reverse()\n",
    "        return ProgramGraph(reverse_cfg, self.end, self.start)    \n",
    "    \n",
    "    def node_for_line(self, line_no):\n",
    "        for node in self.nodes():\n",
    "            if str(node) == str(line_no):\n",
    "                return node\n",
    "        return None\n",
    "    \n",
    "    def plot(self):\n",
    "        pos = nx.nx_agraph.graphviz_layout(self.graph, prog=\"dot\")\n",
    "        nx.draw_networkx_nodes(self.graph, pos=pos, node_size=800, node_color='#FFFFFF', edgecolors='#000000')\n",
    "        nx.draw_networkx_edges(self.graph, pos=pos, connectionstyle=\"arc\", arrowsize=20)\n",
    "        nx.draw_networkx_labels(self.graph, pos=pos)\n",
    "        nx.draw_networkx_edge_labels(self.graph, pos=pos, edge_labels=nx.get_edge_attributes(self.graph,'label'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "c55e66c2",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "from functools import singledispatchmethod"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "a4dfcee0",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
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   "outputs": [],
   "source": [
    "class CFGBuilder:\n",
    "    def __init__(self, method_declaration):\n",
    "        # create graph\n",
    "        self.graph = nx.DiGraph()\n",
    "        self.method_name = method_declaration.name\n",
    "        \n",
    "        # create entry/end node\n",
    "        self.start = StartNode(self.graph, self.method_name, method_declaration)\n",
    "        self.end   = CFGNode(self.graph, self.method_name, \"End\")\n",
    "        self.graph.add_node(self.start)\n",
    "        self.graph.add_node(self.end)\n",
    "        \n",
    "        # set entry as current target\n",
    "        self.frontier = [ self.start ]\n",
    "        \n",
    "        for node in method_declaration.body:\n",
    "            self.add_node(node)\n",
    "            \n",
    "        # Add edges from last nodes to end node\n",
    "        for parent in self.frontier:\n",
    "            self.graph.add_edge(parent, self.end)\n",
    "\n",
    "    def create_graph(self):\n",
    "        return ProgramGraph(self.graph, self.start, self.end)\n",
    "    \n",
    "    @singledispatchmethod\n",
    "    def add_node(self, node):\n",
    "        pass\n",
    "    \n",
    "    @add_node.register        \n",
    "    def add_block_node(self, block_node: javalang.tree.BlockStatement):\n",
    "        for node in block_node.statements:\n",
    "            self.add_node(node)            \n",
    "    \n",
    "    @add_node.register\n",
    "    def add_statement_node(self, node: javalang.tree.StatementExpression):\n",
    "        cfg_node = CFGNode(self.graph, self.method_name, node)\n",
    "        self.graph.add_node(cfg_node)\n",
    "        for parent in self.frontier:\n",
    "            self.graph.add_edge(parent, cfg_node)\n",
    "        self.frontier = [ cfg_node ]\n",
    "        \n",
    "    @add_node.register\n",
    "    def add_declaration_node(self, node: javalang.tree.LocalVariableDeclaration):\n",
    "        self.add_statement_node(node)\n",
    "        \n",
    "    @add_node.register\n",
    "    def add_if_node(self, if_node: javalang.tree.IfStatement):\n",
    "        cfg_node = CFGNode(self.graph, self.method_name, if_node)\n",
    "        self.graph.add_node(cfg_node)\n",
    "\n",
    "        for parent in self.frontier:\n",
    "            self.graph.add_edge(parent, cfg_node)\n",
    "        self.frontier = [cfg_node]\n",
    "        self.add_node(if_node.then_statement)\n",
    "        \n",
    "        if if_node.else_statement:\n",
    "            current_frontier = self.frontier[:]\n",
    "            self.frontier = [cfg_node]\n",
    "            self.add_node(if_node.else_statement)\n",
    "            self.frontier.extend(current_frontier)\n",
    "        else:\n",
    "            self.frontier.append(cfg_node)\n",
    "            \n",
    "    @add_node.register\n",
    "    def add_while_node(self, while_node: javalang.tree.WhileStatement):\n",
    "        cfg_node = CFGNode(self.graph, self.method_name, while_node)\n",
    "        self.graph.add_node(cfg_node)\n",
    "        for parent in self.frontier:\n",
    "            self.graph.add_edge(parent, cfg_node)\n",
    "        self.frontier = [cfg_node]\n",
    "        self.add_node(while_node.body)\n",
    "        for parent in self.frontier:\n",
    "            self.graph.add_edge(parent, cfg_node)\n",
    "        self.frontier = [cfg_node]\n",
    "\n",
    "    @add_node.register\n",
    "    def add_return_node(self, return_node: javalang.tree.ReturnStatement):\n",
    "        cfg_node = CFGNode(self.graph, self.method_name, return_node)\n",
    "        self.graph.add_node(cfg_node)\n",
    "        for parent in self.frontier:\n",
    "            self.graph.add_edge(parent, cfg_node)\n",
    "        self.graph.add_edge(cfg_node, self.end)\n",
    "        self.frontier = [] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "cc72680e",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
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   },
   "outputs": [],
   "source": [
    "def parse_method(code):\n",
    "    class_code = \"class Dummy {\\n\" + code + \"\\n}\";\n",
    "    tokens = javalang.tokenizer.tokenize(class_code)\n",
    "    parser = javalang.parser.Parser(tokens)\n",
    "    ast = parser.parse()\n",
    "    _, node = list(ast.filter(javalang.tree.MethodDeclaration))[0]\n",
    "    return node"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1071bad7",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "To recall, here's an example method for which we can view the control flow graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "762277ae",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "code = \"\"\"\n",
    "  public int foo(int x) {\n",
    "    int y = 0;\n",
    "\n",
    "    while(x >= 0) {\n",
    "        if(x % 2 == 0)\n",
    "            y += x;\n",
    "        x--;\n",
    "    }\n",
    "\n",
    "    return y;\n",
    "  }\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e058772e",
   "metadata": {
    "scrolled": true,
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()\n",
    "cfg.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7f24309e",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Based on the CFG we defined the notion of dominance, and the resulting dominator tree."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "c3a73d3a",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def dominators(self):\n",
    "        entry = self.start\n",
    "        remaining_nodes = [node for node in self.nodes() if node != entry]\n",
    "\n",
    "        # D(entry) <- {entry}\n",
    "        dominators = {}\n",
    "        dominators[entry] = [entry]\n",
    "\n",
    "        # D(node \\ {entry}) <- nodes\n",
    "        for node in remaining_nodes:\n",
    "            dominators[node] = set(self.nodes())\n",
    "\n",
    "        changed = True\n",
    "        while changed:\n",
    "            changed = False\n",
    "\n",
    "            for node in remaining_nodes:\n",
    "                current_dominators = dominators[node]\n",
    "\n",
    "                # new_dominators = node \\cup intersection(dominators for all predecessors)\n",
    "                new_dominators = set(self.nodes())\n",
    "\n",
    "                for p in self.predecessors(node):\n",
    "                    new_dominators = new_dominators.intersection(dominators[p])\n",
    "\n",
    "                new_dominators.add(node)\n",
    "\n",
    "                if new_dominators.symmetric_difference(current_dominators):\n",
    "                    dominators[node] = new_dominators\n",
    "                    changed = True\n",
    "\n",
    "        return dominators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "da8c1933",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def strict_dominators(self):\n",
    "        dominators = self.dominators()\n",
    "        for node, dom in dominators.items():\n",
    "            dom.remove(node)\n",
    "        return dominators"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "32d33c8a",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def dominator_tree(cfg):\n",
    "    dt = nx.DiGraph()\n",
    "    dt.add_nodes_from(cfg.nodes())\n",
    "    dominator_map = cfg.strict_dominators()\n",
    "    queue = [ cfg.start ]\n",
    "    while queue:\n",
    "        current = queue.pop()\n",
    "        for node in cfg.nodes():            \n",
    "            dominators = dominator_map[node]\n",
    "            \n",
    "            if current in dominators:\n",
    "                dominators.remove(current)\n",
    "                if not dominators:\n",
    "                    dt.add_edge(current, node)\n",
    "                    queue.append(node)\n",
    "\n",
    "    return ProgramGraph(dt, cfg.start, cfg.end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a3d384b7",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()\n",
    "cfg.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6ceca588",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dominator_tree(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b1b9472",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The postdominators are determined simply by applying the same on the reversed CFG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "275687bf",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def reverse(self):\n",
    "        reverse_cfg = self.graph.reverse()\n",
    "        return ProgramGraph(reverse_cfg, self.end, self.start)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3c5f8de5",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def post_dominators(self):\n",
    "        rcfg = self.reverse()\n",
    "        return rcfg.dominators()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "f11f018c",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def postdominator_tree(cfg):\n",
    "    rcfg = cfg.reverse()\n",
    "    return dominator_tree(rcfg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "edad9419",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "c977bd50",
   "metadata": {
    "scrolled": false,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "postdominator_tree(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b727eada",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The postdominator tree allows us to determine the control dependencies in a program."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "cf126739",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def transitive_successors(self, node):\n",
    "        return nx.nodes(nx.dfs_tree(self.graph, node))\n",
    "    \n",
    "    def least_common_ancestor(self, node1, node2):\n",
    "        current = node1\n",
    "        successors = self.transitive_successors(current)\n",
    "\n",
    "        while not (node1 in successors) or not (node2 in successors):\n",
    "            current = list(self.graph.predecessors(current))[0]\n",
    "            successors = self.transitive_successors(current)\n",
    "        \n",
    "        return current  "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "fdaa8e96",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def is_reachable(self, source, target):\n",
    "        successors = self.transitive_successors(source)\n",
    "        return target in successors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "f5a48083",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def in_degree(self, node):\n",
    "        return self.graph.in_degree(node)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "1d021200",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def control_dependence_graph(cfg):\n",
    "    pdt = postdominator_tree(cfg)\n",
    "    cdg = nx.DiGraph()\n",
    "    cdg.add_nodes_from(cfg.nodes())\n",
    "    \n",
    "    # 1. Find S, a set of edges (a,b) in the CFG such that\n",
    "    # b is not an ancestor of a in the post-dominator tree.\n",
    "    edges = set()\n",
    "    for a, b in cfg.edges():\n",
    "        if not pdt.is_reachable(b, a):\n",
    "            edges.add((a, b))\n",
    "\n",
    "    for a, b in edges:\n",
    "        # 2. For each edge (a,b) in S, find L, the least common ancestor\n",
    "        # of a and b in the post-dominator tree.\n",
    "        lca = pdt.least_common_ancestor(a, b)\n",
    "\n",
    "        # Traverse backwards in the post-dominator tree from b to L,\n",
    "        # marking each node visited; mark L only if L = a.\n",
    "        # Statements representing all marked nodes are control dependent on a.\n",
    "        current = b\n",
    "        while current != lca:\n",
    "            cdg.add_edge(a, current)\n",
    "            current = list(pdt.predecessors(current))[0]\n",
    "\n",
    "        if a == lca:\n",
    "            cdg.add_edge(a, lca)\n",
    "\n",
    "    # Any nodes not connected at this point are only dependent on entry\n",
    "    entry = cfg.start\n",
    "    for node in cdg.nodes():\n",
    "        if node != entry and (cdg.in_degree(node) == 0 or list(cdg.predecessors(node)) == [node]):\n",
    "            cdg.add_edge(entry, node)\n",
    "\n",
    "    return ProgramGraph(cdg, cfg.start, cfg.end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "fd7f9721",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()\n",
    "cfg.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "c1d8933b",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "control_dependence_graph(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0f1829a",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Control Dependencies via Dominance Frontier"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4cad22c7",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Before we move on to data dependencies, we will discuss an alternative way to determine the control dependencies."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3af460a2",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "For a CFG and node x, the dominance frontier DF(x) is the set of all nodes y in the CFG such that x dominates an immediate predecessor of y but does not strictly dominate y. The dominance frontier for node $n$ consists of two parts:\n",
    "1. DFlocal: The successors of $n$ in the CFG that are not strictly dominated by $n$\n",
    "2. DFup: Nodes in the dominance frontier of $n$ that are not dominated by $n$'s immediate dominator\n",
    "\n",
    "The dominance frontier for node $n$ consists of DFlocal(n) and DFup(c) for each child c whose immediate dominator is $n$. We thus need to add a method to calculate the immediate dominators, which we previously defined in the lecture but did not implement."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "7d9e191e",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def immediate_dominators(self):\n",
    "        dominators = self.strict_dominators()\n",
    "        idom = {} \n",
    "        for node in cfg.nodes():\n",
    "            idom[node] = set(dominators[node])\n",
    "            \n",
    "            for dom in list(idom[node]):\n",
    "                if set(dominators[dom]) & idom[node]:\n",
    "                    idom[node] -= set(dominators[dom])\n",
    "        return idom\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "d42ef298",
   "metadata": {},
   "outputs": [],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2e15d24d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dominator_tree(cfg).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "3a9283be",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Start: []\n",
      "End: ['11']\n",
      "3: ['Start']\n",
      "5: ['3']\n",
      "6: ['5']\n",
      "7: ['6']\n",
      "8: ['6']\n",
      "11: ['5']\n"
     ]
    }
   ],
   "source": [
    "for key, value in cfg.immediate_dominators().items():\n",
    "    print(f\"{key}: {[str(v) for v in value]}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "01eef6b8",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The dominance frontier can now be calculated with the following algorithm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "47ec425c",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def dominance_frontier(node, cfg):\n",
    "\n",
    "    dominators = cfg.strict_dominators()\n",
    "    dt = dominator_tree(cfg)\n",
    "    idom = cfg.immediate_dominators()\n",
    "    \n",
    "    df = set()\n",
    "    for succ in cfg.successors(node):\n",
    "        if node not in idom[succ]:\n",
    "            df.add(succ)\n",
    "    \n",
    "    for succ in dt.successors(node):\n",
    "        dom_succ = dominance_frontier(succ, cfg)\n",
    "        for n in dom_succ:\n",
    "            if not node in dominators[n]:\n",
    "                df.add(n)\n",
    "    \n",
    "    return df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8d50bd2",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "For example, the dominance frontier of node 6 must be 5."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "331a911a",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cfg.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "f36beef8",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "dominator_tree(cfg).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "4afc1631",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "node = cfg.node_for_line(6)\n",
    "for n in dominance_frontier(node, cfg):\n",
    "    print(str(n))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6b85c7b1",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "For a given node of the CFG, the control dependencies are the dominance frontiers on the reverse control flow graph. We can therefore also calculate the CDG by inverting the CFG, and then for each node calculate its dominance frontier; then add an edge from each node on the frontier to the node."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "0d9b0225",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def control_dependencies2(cfg):\n",
    "    rcfg = cfg.reverse()\n",
    "    \n",
    "    cdg = nx.DiGraph()\n",
    "    cdg.add_nodes_from(cfg.nodes())\n",
    "\n",
    "    for node in cfg.nodes():\n",
    "        frontier = dominance_frontier(node, rcfg)\n",
    "        for frontier_node in frontier:\n",
    "            cdg.add_edge(frontier_node, node)\n",
    "\n",
    "        # Nodes without parents are dependent only on entry\n",
    "        if node != cfg.start and (cdg.in_degree(node) == 0 or list(cdg.predecessors(node)) == [node]):\n",
    "            cdg.add_edge(cfg.start, node)\n",
    "            \n",
    "    return ProgramGraph(cdg, cfg.start, cfg.end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "be1d3750",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "control_dependencies2(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c858d86c",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "For reference, here is the CDG calculated with our previous algorithm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "7e9b2b37",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "control_dependence_graph(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "84d09258",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Let's also revisit our lecture example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "0dfb2fe6",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "code = \"\"\"\n",
    "public boolean testMe(int x, int y) {\n",
    "    if (x <= y) {\n",
    "        if (x == y) {\n",
    "            System.out.println(\"Some output\");\n",
    "        }\n",
    "        if (x > 0) {\n",
    "            if (y == 17) {\n",
    "               return true;\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    return false;\n",
    "}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a0f688d4",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "92a98b90",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "control_dependencies2(cfg).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "40da0d76",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "control_dependence_graph(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "103008d8",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Data Dependencies"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "57021afd",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The second class of dependencies we considered are related to how data is written and propagated within a program. We distinguished between definitions and uses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "cc340289",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "from dataclasses import dataclass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "6011f425",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "@dataclass(frozen=True, eq=True)\n",
    "class Use:\n",
    "    name: str\n",
    "    node: CFGNode\n",
    "        \n",
    "    def __str__(self):\n",
    "        if isinstance(self.node.ast_node, str):\n",
    "            return f\"Use: {self.name} in {self.node.ast_node}\"\n",
    "        \n",
    "        return f\"Use: {self.name} in line {self.node.ast_node.position.line - 1}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "21d3ac47",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class CFGNode(CFGNode):\n",
    "    def uses(self):\n",
    "        uses = set()\n",
    "        if not self.ast_node or isinstance(self.ast_node, str):\n",
    "            return uses\n",
    "        \n",
    "        # Do not check children that contain other statements\n",
    "        root = self.ast_node\n",
    "        if isinstance(self.ast_node, javalang.tree.ForStatement):\n",
    "            root = self.ast_node.control\n",
    "        elif hasattr(self.ast_node, \"condition\"):\n",
    "            root = self.ast_node.condition\n",
    "        elif isinstance(self.ast_node, javalang.tree.StatementExpression):\n",
    "            # Assignment: lhs only if it is a +=, -=, etc\n",
    "            if isinstance(self.ast_node.expression, javalang.tree.Assignment):\n",
    "                if len(self.ast_node.expression.type) > 1:\n",
    "                    root = self.ast_node.expression\n",
    "                else:\n",
    "                    root = self.ast_node.expression.value\n",
    "            \n",
    "        for _, node in root.filter(javalang.tree.MemberReference):\n",
    "            uses.add(Use(node.member, self))\n",
    "        for _, node in root.filter(javalang.tree.MethodInvocation):\n",
    "            uses.add(Use(node.qualifier, self)) # Only works for non-static methods\n",
    "        return uses"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "5b9b15c0",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "@dataclass(frozen=True, eq=True)\n",
    "class Definition:\n",
    "    name: str\n",
    "    node: CFGNode\n",
    "        \n",
    "    def __str__(self):\n",
    "        return f\"Def: {self.name} in line {self.node.ast_node.position.line - 1}\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "d26f924b",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class CFGNode(CFGNode):\n",
    "    def definitions(self):\n",
    "        definitions = set()\n",
    "        if not self.ast_node or isinstance(self.ast_node, str):\n",
    "            return definitions\n",
    "        \n",
    "        # Do not check children that contain other statements\n",
    "        root = self.ast_node\n",
    "        if isinstance(self.ast_node, javalang.tree.ForStatement):\n",
    "            root = self.ast_node.control\n",
    "        elif hasattr(self.ast_node, \"condition\"):\n",
    "            root = self.ast_node.condition\n",
    "                    \n",
    "        for _, node in root.filter(javalang.tree.LocalVariableDeclaration):\n",
    "            decl = node.declarators[0]\n",
    "            definitions.add(Definition(decl.name, self))\n",
    "        for _, node in root.filter(javalang.tree.Assignment):\n",
    "            memberref = node.expressionl\n",
    "            definitions.add(Definition(memberref.member, self))\n",
    "        for _, node in root.filter(javalang.tree.MemberReference):\n",
    "            if node.prefix_operators or node.postfix_operators:\n",
    "                definitions.add(Definition(node.member, self))\n",
    "        return definitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "70bfb720",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class StartNode(StartNode):\n",
    "    def definitions(self):\n",
    "        definitions = set()\n",
    "        \n",
    "        for _, node in self.ast_node.filter(javalang.tree.FormalParameter):\n",
    "            definitions.add(Definition(node.name, self))\n",
    "        \n",
    "        return definitions\n",
    "    \n",
    "    def uses(self):\n",
    "        return set()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c603a84d",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "To find our which definitions can reach which uses we need to apply dataflow analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "5feb8403",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class Lattice(object):\n",
    "    def __init__(self, elements, join_func, meet_func):\n",
    "        self.elements = elements\n",
    "        self.join = join_func\n",
    "        self.meet = meet_func\n",
    "\n",
    "    def wrap(self, object):\n",
    "        return LatticeElement(self, object)\n",
    "\n",
    "    def element_by_index(self, index):\n",
    "        return LatticeElement(self, self.elements[index])\n",
    "\n",
    "    @property\n",
    "    def top(self):\n",
    "        top = self.wrap(self.elements[0])\n",
    "        for element in self.elements[1:]:\n",
    "            top |= self.wrap(element)\n",
    "        return top\n",
    "\n",
    "    @property\n",
    "    def bottom(self):\n",
    "        bottom = self.wrap(self.elements[0])\n",
    "        for element in self.elements[1:]:\n",
    "            bottom &= self.wrap(element)\n",
    "        return bottom\n",
    "    \n",
    "    def plot(self):\n",
    "        dot = Digraph()\n",
    "        \n",
    "        graph = dict()\n",
    "        for indexS, elementS in enumerate(self.elements):\n",
    "            graph[indexS] = []\n",
    "            for indexD, elementD in enumerate(self.elements):\n",
    "                if self.wrap(elementS) <= self.wrap(elementD):\n",
    "                    if not bool( sum([ int(self.element_by_index(x) <= self.wrap(elementD)) for x in graph[indexS]])) and not elementS == elementD:\n",
    "                        graph[indexS] += [indexD]\n",
    "        dot.node(str(self.top.unwrap))\n",
    "        dot.node(str(self.bottom.unwrap))\n",
    "        for s, ds in graph.items():\n",
    "            for d in ds:\n",
    "                dot.edge(str(self.element_by_index(s)), str(self.element_by_index(d)))\n",
    "\n",
    "        return dot\n",
    "\n",
    "    def __repr__(self):\n",
    "        \"\"\"Represents the lattice as an instance of Lattice.\"\"\"\n",
    "        return 'Lattice(%s,%s,%s)' % (self.elements,self.join,self.meet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "08eacc1a",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class LatticeElement():\n",
    "    def __init__(self, lattice, element):\n",
    "        if element not in lattice.elements: raise ValueError('The given value is not a lattice element')\n",
    "        self.lattice = lattice\n",
    "        self.index = lattice.elements.index(element)\n",
    "\n",
    "    @property\n",
    "    def unwrap(self):\n",
    "        return self.lattice.elements[self.index]\n",
    "\n",
    "    def __and__(self, b):\n",
    "        # a.__and__(b) <=> a & b <=> meet(a,b)\n",
    "        return LatticeElement(self.lattice, self.lattice.meet(self.unwrap, b.unwrap))\n",
    "\n",
    "    def __or__(self, b):\n",
    "        # a.__or__(b) <=> a | b <=> join(a,b)\n",
    "        return LatticeElement(self.lattice, self.lattice.join(self.unwrap, b.unwrap))\n",
    "\n",
    "    def __eq__(self, b):\n",
    "        # a.__eq__(b) <=> a = b <=> join(a,b)\n",
    "        return self.unwrap == b.unwrap\n",
    "\n",
    "    def __le__(self, b):\n",
    "        # a <= b if and only if a = a & b,\n",
    "        # or\n",
    "        # a <= b if and only if b = a | b,\n",
    "        a = self\n",
    "        return ( a == a & b ) or ( b == a | b )\n",
    "\n",
    "    def __str__(self):\n",
    "        return str(self.unwrap)\n",
    "\n",
    "    def __repr__(self):\n",
    "        return \"LatticeElement(L, %s)\" % str(self)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "9282fab5",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "code = \"\"\"\n",
    "  public int foo(int x) {\n",
    "    int y = 0;\n",
    "\n",
    "    while(x >= 0) {\n",
    "        if(x % 2 == 0)\n",
    "            y += x;\n",
    "        x--;\n",
    "    }\n",
    "\n",
    "    return y;\n",
    "  }\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "532b70ec",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "tree = parse_method(code)\n",
    "cfg = CFGBuilder(tree).create_graph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "81bb90f3",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def intersection(a, b):\n",
    "    return a & b \n",
    "\n",
    "def union(a, b):\n",
    "    return a | b "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "31d5cd33",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def powerset(A):\n",
    "    length = len(A)\n",
    "    return [\n",
    "        set({e for e, b in zip(A, f'{i:{length}b}') if b == '1'})\n",
    "        for i in range(2 ** length)\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "ca705a96",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "definitions = []\n",
    "for node in cfg.nodes():\n",
    "    definitions.extend([definition for definition in node.definitions()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "72893317",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "U = list(powerset(definitions))\n",
    "join = union\n",
    "meet = intersection\n",
    "\n",
    "L = Lattice(U, join, meet)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "9a14e3e9",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def reaching_definitions(node, in_facts):\n",
    "    gen  = set(node.definitions())\n",
    "    defined_vars = [definition.name for definition in gen]\n",
    "    kill = set([definition for definition in in_facts.unwrap if definition.name in defined_vars])\n",
    "    return in_facts.lattice.wrap(gen | (in_facts.unwrap - kill))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "537ebd21",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class DataFlowAnalysis:\n",
    "    def __init__(self, cfg, program_lattice, transfer_function, is_backward):\n",
    "        self.cfg = cfg\n",
    "        if is_backward:\n",
    "            self.cfg = cfg.reverse()\n",
    "            \n",
    "        self.transfer_function = transfer_function\n",
    "        self.lattice = program_lattice\n",
    "        \n",
    "        self.facts = {}\n",
    "        \n",
    "        for node in cfg.nodes():\n",
    "            self.facts[node] = program_lattice.bottom"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "25a9e9b3",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "class DataFlowAnalysis(DataFlowAnalysis):\n",
    "    def apply(self):\n",
    "            \n",
    "        worklist = [(edge[0], edge[1]) for edge in self.cfg.edges()]\n",
    "        while worklist:\n",
    "            node1, node2 = worklist.pop()\n",
    "            \n",
    "            result = self.transfer_function(node1, self.facts[node1])\n",
    "            self.facts[node1] = result\n",
    "            if not (result <= self.facts[node2]):\n",
    "                self.facts[node2] = self.lattice.join(self.facts[node2], result)\n",
    "                for successor in self.cfg.successors(node2):\n",
    "                    worklist.append((node2, successor))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8b118507",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "We can now use the reaching definitions to define our data dependence graph."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "fc0c55bd",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def get_definitions(cfg):\n",
    "    definitions = []\n",
    "    for node in cfg.nodes():\n",
    "        definitions.extend([definition for definition in node.definitions()])\n",
    "    return definitions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "e2ff5377",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def create_ddg(cfg):\n",
    "    definitions = get_definitions(cfg)\n",
    "    U = list(powerset(definitions))\n",
    "    join = union\n",
    "    meet = intersection\n",
    "\n",
    "    L = Lattice(U, join, meet)\n",
    "    analysis = DataFlowAnalysis(cfg, L, reaching_definitions, False)\n",
    "    analysis.apply()\n",
    "    \n",
    "    # Create unconnected graph\n",
    "    ddg = nx.DiGraph()\n",
    "    ddg.add_nodes_from(cfg.nodes())\n",
    "    \n",
    "    # Add dataflow edges\n",
    "    for node1, node2 in cfg.edges():\n",
    "        for use in node2.uses():\n",
    "            for definition in analysis.facts[node1].unwrap:\n",
    "                if use.name == definition.name:\n",
    "                    # add edge from the definition node to use node\n",
    "                    ddg.add_edge(definition.node, node2, label=use.name)\n",
    "\n",
    "    return ProgramGraph(ddg, cfg.start, cfg.end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "de5dbf51",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "code = \"\"\"\n",
    "  public int foo(int x) {\n",
    "    int y = 0;\n",
    "\n",
    "    while(x >= 0) {\n",
    "        if(x % 2 == 0)\n",
    "            y += x;\n",
    "        x--;\n",
    "    }\n",
    "\n",
    "    return y;\n",
    "  }\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "16d64886",
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "create_ddg(cfg).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "f1f6e0cd",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "create_ddg(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9dba3745",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Program Dependence Graph"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "544c4b79",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "The program dependence graph represents all dependencies in a program. It essentially is a combination of PDG and DDG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "5828dfbe",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def create_pdg(cfg):\n",
    "    # Create unconnected graph\n",
    "    pdg = nx.DiGraph()\n",
    "    pdg.add_nodes_from(cfg.nodes())\n",
    "\n",
    "    ddg = create_ddg(cfg)\n",
    "    cdg = control_dependence_graph(cfg)\n",
    "    pdg.add_edges_from(cdg.edges())\n",
    "    pdg.add_edges_from(ddg.edges()) # TODO: Loses edge labels\n",
    "    \n",
    "    return ProgramGraph(pdg, cfg.start, cfg.end)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "f737de00",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "control_dependence_graph(cfg).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e1c4aa86",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "create_ddg(cfg).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "be7b5e9e",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
      "image/png": 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AqlevDkdHR9l4v5WVVZG29dVUV65cQZcuXdC7d2/s27fvu+/16dOn2L59O/z8/PD582fweDzUqlUL9vb2MDExgUgkgkQiQVJSEqKiovD48WMQEUxNTeHu7g4PD48CJ/5FRkbCwcEB3bt3x8GDB4v98yYiHD58GHPmzMHbt28xefJkLFy4ECYmJsX+eTCMorAJhAyjZogIjx49yjfT/9WrVwAAa2vrfJP9fvrpJ46jVZ379++jbdu2aNy4MYKCgqCtrV2k+3JycvDw4UNERETA29sbz549g5WVFXg8HrS1tWFgYABbW1vExcXh5s2beP/+PbS0tL5b5vHjx9GnTx8sXLgQy5Ytk+v9ZGRkYP369fD29oaOjg6WLl2KCRMmsAOPGE6wCYQMw7Hs7Gy6desWrV27lnr16kUVKlQgACQQCKhp06Y0ffp0OnbsGH38+JHrUDnz6tUrqlatGtnZ2dGXL1/kLqdTp04EgN68efPN9y5dukQA6N69e0Uqa9WqVQSA9u7dK3c8RETv3r0jd3d34vF4ZGNjQ0FBQSUqj2HkwYYJGEbFMjIyEB4eLvvkf+PGDaSmpkJHRwctWrSQdfu3bNmSbW0LICkpCQ4ODkhNTcX169dRpUoVuctq3LgxoqKikJaW9s2eBFlZWTAxMcGyZcvg6en5w7KICKNHj8bBgwdx+fJltGrVSu64gH+HH6ZPn46wsDC4uLhg7dq1sLa2LlGZDFNUbJiAYZTsy5cvuHbtmqzL/86dO8jOzoaRkRHatm0r6/K3t7cvctd3WZGZmQknJyfExMTg2rVrsLKyKlF5FhYWePXqFXJzcwvcSMnFxQVSqRQXLlwoUnlZWVno0qULYmNjER4eDgsLixLFR0Q4fvw4PD098erVK/z8889YsmQJypcvX6JyGeZHWDLAMAr27t27fJP9oqOjQUSoXLlyvvH+Bg0aqMW2vuoqNzcXAwcOxNmzZ3Hp0iW0bt26xGWampoiMzMT6enpBX5/3bp1mD9/PpKSkop83kJiYiJatGgBPT09XLt2TSFtX1ZWFjZu3Ijly5dDIBBg8eLFmDhxokq2XFa258+fw8LCQm13tSyr2JwBhikBqVRKjx8/pj///JNGjRpFtWrVIgAEgGrXrk3u7u7k7+9PT58+JalUynW4GkMqldIvv/xCfD6fTp48qbByRSIRmZmZFfr96OhoAlDsfQDu379PhoaG1K1bN8rJySlpmDLv37+n8ePHE5/Pp7p169Lp06c1+vcoMjKSAFDjxo3p7NmzGv1eShu2zwDDFENOTg7dvXuXNm7cSP3796dKlSoRAOLxeNSoUSOaPHkyHT58uNib0jD55U3O2759u8LKzMzMJABUs2bNQq+RSqVUuXJlmjVrVrHLP3/+PPH5fJo2bVpJwizQvXv3ZJMfO3fuTP/884/C61CFv//+mwAQn89nSYGaYckAw3xHZmYmXblyhby9vcnFxYUMDQ0JAIlEImrTpg3NnTuXzp49S0lJSVyHWmrs2rWLANCiRYsUWu6bN29kD6DvGTFiBDVq1EiuOjZv3qzwJCaPVCqlkydPUp06dYjP55OHh4fGrTDJSwbyvlhSoD5YMsAwX0lJSaHz58/T/PnzydHRkbS1tQkAlStXjrp27UorVqyg0NBQube5Zb4vKCiIhEIhjR07VuEPhrt378o+WX/Pnj17CAC9f/9ernomTZpEQqGQQkJC5Lr/R7KysmjdunVkZGREhoaG5OPjQ5mZmUqpS9H+mwz8Nylo0qQJnTt3jiUFHGDJAFOmffjwgY4ePUrTpk2jJk2ayBolMzMz6tOnD61fv57u3LnDDpdRgdu3b5O+vj65uroq5ecdHBxMAGjIkCHfvS4+Pr5E+wdkZ2dT165dydjYmB49eiRXGUWRkJBAEydOJIFAQLVq1aLjx4+r/UO0sGSAJQXcK+rzm22JxWg8IsLLly8RFhYmm+kfGxsL4N8lZw4ODvDw8ICDgwPq1avHZjur0LNnz9C9e3c0aNAABw8eVMoufAkJCQCAihUrfve6SpUqwc7ODsHBwRg6dGix6xEKhTh8+DBatWoFV1dX3Lx5UylLAytUqIAtW7Zg4sSJmDFjBnr37o327dtj/fr1aNSokcLrUwWpVArg3z0XunXrhvLly8PX1xeHDh2CUCiEUCiEnp4eqlWrhho1aqB69eqoUaMGqlWrVuTVH0zJsGSA0ThSqRQPHjzIt8zvzZs3AID69eujY8eOWLx4MRwcHFCtWjWOoy27Pn78CCcnJxgbG+PMmTPQ19dXSj2JiYkAAHNz8x9e27VrV+zbtw9EJFdSaGRkhNOnT6NFixbo168fLly4oLRlgfXr18f58+cRFBSEmTNnokmTJhgzZgyWL1+OSpUqKaVOeYnF4mJdn52djczMTIjFYmRnZyM7Oxupqak4fvy4LLnLY2lpifbt26NDhw7o0KED+5tWFkV2MzCMMkgkErp58yatXr2a3NzcyNTUlACQUCikFi1akKenJ508eZISExO5DpX5H7FYTE2bNqVKlSpRXFycUutasGABASBfX98fXnvhwgUCQDExMSWqMywsjLS0tJQyB6IgEomENm7cSCYmJlSuXDlatWoVZWRkKL3e70lJSaENGzZQ8+bNicfjFWmYwNramgIDAyk3N7fQctPT0+nx48cUEhJCfn5+NGXKFLK1tc23tHf69On0+PFjFb5bzcXmDDAaKzU1lUJCQmjx4sXUsWNH0tPTIwCkp6dHHTt2pMWLF1NISAilpqZyHSpTAIlEQk5OTmRgYECRkZFKr2/MmDEEgA4dOvTDa9PT00lbW5vWrVtX4noDAgIIAK1du7bEZRXVp0+faOrUqSQUCsnCwoIOHz6s8vH3V69e0axZs8jIyIgEAgH16dOHZs2aVeIk4Ec+fvxIgYGBNHHiRCpfvjwBIBcXFzp37lyJyi3tWDLAaIxPnz7RyZMnydPTk1q0aEFCoVB2Zr2bmxv5+PjQzZs3SSKRcB0q8wNSqZRGjBhBWlpaSpt1/1/dunUjAHThwoUiXd+5c2dycXFRSN1z584lHo9Hp06dUkh5RfXo0SNydXUlANS2bVu6c+eO0uvMzMykOXPmkFAoJCMjI5o1axa9evWKiApfWqiIJKAgGRkZ5O/vT02aNCEAVL9+fbp+/bpC6ygtWDLAqK3Xr1/T/v37ycPDg+rXry9rQKpVq0aDBw+mrVu3UnR0NMv2NZCXlxcBoP3796uszqZNmxIACg8PL9L1q1evJl1dXYUs28vNzaXevXuTvr4+RUVFlbi84rpw4YLsb2jkyJH09u1bpdRz9+5dsrW1JS0tLVqxYgWJxeJ8389LBvKGC5SVBPyXVCqla9euUbNmzYjH49G0adNYj+F/sGSAUQtSqZQePnxIO3bsoOHDh5OFhYXs4V+vXj0aO3Ys7dq1i54/f86WG2m4TZs2EQBas2aNSuu1tLQkAEUeQ87bl+Cvv/5SSP2pqanUuHFjql69OsXHxyukzOLIzs6mbdu2UYUKFUhPT4+WLVtGaWlpCiv/zz//JC0tLbKzsyv0GOg7d+6oNAn4r5ycHFqzZg3p6OhQzZo1KTY2VqX1qzOWDDCcyM7Opjt37tD69eupT58+ZGZmJus2bNKkCU2bNo2OHj1KHz584DpURoECAwOJx+PR9OnTVV63sbExASjyrn25ublkbm5Oc+fOVVgMr1+/psqVK1OLFi0427gqKSmJZs6cSVpaWlS9enXav39/iRPsffv2EY/Ho3Hjxn23J0UqldL9+/c578178uQJWVtbU+XKlVlC8D8sGWBUIiMjg0JDQ2n58uXUtWtXKleuHAEgbW1tcnR0pPnz59P58+fZ704pFhYWRtra2jRo0CCVPwykUqlsfLo4c0qGDh1K9vb2Co3l9u3bpKurS4MGDeK0l+vJkyfUq1cvAkCtWrWimzdvylXOyZMnSSAQ0KhRozh/yBfH+/fvycbGhipXrqzUzaE0BUsGGKX48uULnT17lubOnUtt2rQhkUhEAMjQ0JBcXFzI29ubrl69qjHbqDIlExMTQ8bGxtShQwdO/s0/f/4sSz6LIyAggHg8HiUkJCg0niNHjhAAWrJkiULLlcdff/1FDRs2JAA0dOhQ2WS/ovjw4QMZGhpS7969NXKXzvfv35OVlRU1bNhQI+NXJJYMMAoRHx9Phw8fpsmTJ1OjRo1kE4QqVqxI/fv3p40bN9Ldu3cVerwroxlevXpF1apVIzs7O/ry5QsnMTx+/JgAUIUKFYp139u3bwkAHTx4UOExrVixggDQgQMHFF52ceXk5NAff/xB5ubmpKurS4sWLSrSBLvx48eTsbGxRu/dcfv2beLxeApZRqrJWDLAFJtUKqWnT5+Sv78/jR49mmrXri2b7FerVi0aNWoU/fnnn/T48WM22a+M+/z5M9WvX59++uknpc1gL4pr167Jfj+Lq379+uTu7q7wmKRSKQ0bNoy0tbXl7qJXtOTkZJozZw6JRCKqUqUK7d69u9Cu/+joaOLz+fT777+rOErFmzRpEpUrV65MHz1e1Oc3j4joR7sUpqSkwMjICMnJyTA0NPzR5SqTk5ODBw8eICIiAhEREYiOjoZYLIZEIoFIJIKBgQFsbW1hb28Pe3t72NjYKGVvdE0llUoRHR2db1vf+Ph48Hg82NrawsHBAY6Ojmjbti2qVKnCdbiMmsjMzISTkxNiYmJw7do1WFlZcRbLqVOn0LNnTzRv3hzh4eHFunfGjBkIDAzEy5cvFX5eRWZmJjp16oRnz57h1q1bqFGjhkLLl1dcXBzmzJmDwMBANG3aFL///jvatGmT75qFCxdi27ZtiI+Ph5aWlkLq5aqtTkpKQsWKFbFmzRpMmTJFAe9E8xT1+a2RycDTp0/h6+sLPz8/JCUlgcfjoV69emjUqBFMTEwgEokgkUiQlJSEqKgoxMbGgohgYmICd3d3eHh4oHbt2ly/DZWTSCS4c+eO7MF/7do1fPnyBVpaWmjWrBkcHBzg4OCA1q1bw8TEhOtwGTWUm5uLgQMH4uzZs7h06RJat27NaTx//vknxo4di27duuHs2bPFujcoKAjdunXDw4cPlZLQfPz4ES1atIChoSGuXr0KAwMDhdchr7CwMEyfPh2RkZEYMGAAfvvtN1hYWAAAWrdujWrVquHw4cMF3puSklLk54A6tNVdunQBn8/HhQsXSlSOpiry81uR3QzKdvPmTXJyciIAZGpqSp6enhQWFkYpKSnfvS8lJYXCwsLI09NTtq+9k5NTkTcp0VRisZguXrxICxYsoHbt2pGOjg4BIH19ferSpQstW7aMLl++zNlSKEazSKVS+uWXX4jP59PJkye5DoeIiH799VcSCoU0fPjwYt+bmppKIpGINm7cqITI/hUdHU0GBgbk5uamdvNqcnNzyd/fnypXrkza2to0b948io+PJ4FAQFu3bi3wHj8/P9LS0qKrV69+t2x1aqvXr19PIpGozLZzpWrOQEZGBs2ePZv4fD7Z2dlRQECA3P+w6enpFBAQQHZ2dsTn82n27NmcH/ihKB8/fqRjx47R9OnTqWnTpiQQCGSTq3r16kVr166l27dvl/nZtYx8Vq1aRQBo+/btXIci4+npSSKRiCZPnizX/R06dCBXV1cFR5XfuXPniM/nk6enp1LrkZdYLKYFCxaQjo6ObF+Q48ePf3NdcnKy7AFtaWlZ4MZG6thWnzp1igDQ+/fv5YpD05WaZODOnTtkZWVFIpGIvL29FfYgy87OJm9vbxKJRGRtba2Svb0V7cWLF7Rnzx4aP348WVtbyyb7/fTTTzRs2DDavn07PXjwgE32Y0ps165dBIAWLVrEdSj5jBw5kkQiES1cuFCu+1etWkXlypWjrKwsBUeW3++//04AaOfOnUqtpyRevnxJffv2JQBkYWFBf//9d77v5z3k8b9NxKZOnZrv++raVrNkoBQkA8HBwaSnp0f29vYlPnK0MDExMWRvb0/6+voUHByslDoUIW+HL19fXxoyZAhVr15d9vC3sbGhCRMm0N69e+nly5dch8qUMkFBQSQUClV2XG9xdO/enQQCgdzLx/K20Q0NDVVwZPlJpVLy8PAgoVBIly9fVmpdJZGRkSH75A+A+vbtS8+ePaO4uDjZAWJ5Xzwej8LCwohIvdvqwMBAAlBmdz3V+GQgODiYRCIRdevWTaH7bBckLS2NXFxcSCQSqU1CIJFIKDw8nNasWUM9e/aUHdkpEAioWbNmNGPGDDpx4oTCN01hmK/dvn2b9PX1ydXVVS2Hl5o1a0YAyM/PT677c3NzqXz58jR//nwFR/YtiURCnTp1IhMTkyKfo8AFW1tbGjp0KO3du5eqVq1KIpGI6tatKxt2zPvi8/lkYWFBp0+fVuu2etq0aVS1alW1S2RVRaOTgTt37pC+vj65uLgovfsuT1ZWFrm4uJC+vn6h3VBxcXFKiyctLY3++usvWrp0KXXu3Jn09fUJAOno6FCHDh1o0aJFFBwc/M1pYQyjLE+fPiVzc3Nq0aKF2p4El3fw1bFjx+QuY+DAgdS8eXMFRlW4z58/U7169ahu3br0+fNnldRZXAsXLiRjY2OSSCSUmppKo0ePzpcE/Ld3QCQSqV1b/bU6derQuHHjVBCZetLYZCAjI4OsrKzI3t5e6Vnmf6WlpVGTJk3I2tr6m4kqmzZtIj6fTytWrFBIXZ8/f6bTp0/TrFmzqGXLlqSlpUUAyNjYmFxdXem3336j69evq+wPjGG+9uHDB6pVqxbVrVtXrXuf8pLmknS9//nnn8Tj8ejTp0+KC+w7njx5QqamptSpU6dinaegKpGRkQSA9u3bR7m5uWRnZ/dNr0Del0AgoIYNG6pVW/21q1evEgC1Wf3CBY1NBmbPnk0ikUhp404/Eh0dTSKRiObMmUNE/3bt/fzzz7JffkdHR7nKffPmDR04cIAmTpxItra2sm19q1SpQgMHDqTNmzfTP//8o1EHgjClk1gspqZNm1KlSpUoLi6O63AKlZmZKfu7vHv3rtzlvHr1igDQkSNHFBfcD1y+fJmEQiFNmDBBLbuv+/btSxUrVqTNmzcX2isAgIRCodq01f8lkUjI1taWmjZtqnbLOlVJI5OBmzdvEp/PJ29vb6XW8yMrV64kPp9PISEh1KFDB9mDG/87EOVHn9alUinFxsbSzp07aeTIkbLJOACobt26NGbMGAoICKBnz56pZUPAlF0SiYScnZ3JwMCAIiMjuQ7nu968eSP7u3r+/HmJyrKyslJ5V/LOnTsJgFpu+/v27VsyMDAgHR2dfO3ff4cI1KWtLmgfgtWrVxOfz9fIlWKKpJHJgJOTE9nZ2al8otLIkSPpp59+kv13dnY22dnZkb6+foHdYzdu3Mh3f05ODkVGRtLvv/8uy6jzJtg0btyYpkyZQkeOHKH4+HiVvi+GKQ6pVEojR44kLS0ttZlI+z1RUVGyv8mSHpQ0efJk+umnn1SenHt6ehKfz6ezZ8+qtN6icHV1LbRHgM/nk42NDeeTSvPaamdn53yv7927l/h8Ps2cOZOjyNSHxiUDT548IQAUEBAge83f3/+7XVT/fSjL67/JwPfq5vP5tHLlSgoLC6OVK1eSs7MzGRoaEgASiUTUtm1b8vLyoqCgIM5OcmMYecybN082VqwJQkJCZH+XJR1eO336NAFQ+Sz/nJwc6tGjBxkYGFB0dLRK6/4RLy8v0tXVLbT9/bqtLqrLly8rvD3Pa6ufPn1KRP+fCIwePbpMDw/kKerzW21O7fH19YWpqSkGDBjwzfeWLVsGS0vLb15X5vkCAwcOxNSpU5GSkpLvdalUigULFoCIYGBggDZt2mDOnDlwcHBAs2bNoKOjo7SYGEZZtm7dCm9vb/j4+GDIkCFch1MkCQkJAAAjIyPw+fwSldWuXTsIhUIEBwejTp06igivSAQCAfbt24e2bdvC1dUVt27dgrm5ucrq/x5vb294e3tjzZo1mDVrFvr27Yt58+Zhw4YNOH36dIFtdVFNmTIFzZo1y/eavO35wIEDMWPGDGzevBm6urr47bffMHLkSOzcubPEvxdliiIzC3llZ2eTiYnJN9t15mV8t2/fVkq9eQrqGSAimjlzZoHDBNra2nT79m2WdTKlwtGjR4nH49G0adM0ag7Lpk2bSCAQkIWFhULKc3R0pJ49eyqkrOJ6+fIlVaxYkVq1aqWW26Pv27ePTE1NqXz58lSuXDm5t1bO6xlQ9GTNmTNnkkgkIi0tLVq+fDmbiP2Voj6/1SJtevDgAZKSktCjR49i3/vixQvweDysWbMGO3bsQK1ataCtrY1mzZrh9u3b31x/4sQJNGjQADo6OmjQoAGOHz9eaNk9evRAbm7uN69nZWVBW1sbAoGg2PEyjDq5cuUKhgwZggEDBmDt2rUKP8pXmRISEqCjo6OwEza7du2Ky5cvIzs7WyHlFUeNGjVw8uRJ3L17F2PHjgX9+DBZlRoyZAgePHgAe3t7pKamytVW/5dYLEZOTo4Covu3rZZIJDh8+DAWLFjAegTkoBY/sYiICPB4PDRu3LjA7ycnJyMxMTHf16dPn/Jds3//fvj4+GDChAlYsWIFXrx4gT59+uT7w7548SL69u0LHo+HVatWoVevXhg9ejTu3LlTYL2NGzcusHHk8Xi4cuVKCd4xw3Dv/v376NGjB1q3bo1du3ZpXAOamJgILS0thSUDXbp0QUpKCm7duqWQ8oqrRYsWCAgIwL59+7By5UpOYvieihUrYtCgQd9tq4tq9OjRMDQ0hI6ODjp06FBoG1xUeW31ly9fSlROWaYWcwYiIiJQr149lCtXrsDvd+7c+ZvXtLW1kZmZKfvvV69e4cmTJ7KGoV69eujZsycuXLgAV1dXAMCcOXNQsWJFXL16FUZGRgD+HSvs2rUrfvrpp2/qMDAwgKWlJeLi4vK9zufzERYWhokTJ8r3hhmGY2/evIGzszNq1KiB48ePQ1tbm+uQii0hIQECgQDGxsYKKc/e3h4mJiYIDg5GmzZtFFJmcQ0cOBCxsbFYuHAh6tWrh/79+3MSR2F+1Fb/iEgkQt++fdGtWzdUqFABDx48wJo1a+Dg4IDr16/LnWQYGBigbt26iIiIwKhRo+Qqo6xTi2QgOjoajRo1KvT7W7ZsQd26dfO99t8u+oEDB+b7hODg4AAAsgd5fHw8oqKiMHfuXFkiAPz7acDGxgZpaWkF1t2sWTMkJCQgNTUVRAShUIicnBxcvnwZRKRR3aoMAwBfvnyBi4sL+Hw+goKC8v09aJLExEQAUFgyIBAI0KlTJ1y8eBFLlixRSJnyWLhwIR49eoSRI0fCwsLim4l2XPpRW/0jrVu3RuvWrWX/3aNHD/Tr1w92dnbw8vLC+fPn5S67UaNGiI6Olvv+sk4tkgGxWPzdrr7mzZujadOm3y2jRo0a+f47r7ykpCQAwMuXLwGgwJnC9erVQ2RkZIHlmpiYoE6dOvjrr79w8+ZNXLt2DaGhofl6JRhGU2RmZqJnz554+/Ytrl27hipVqnAdktwSEhKQm5ursGEC4N95Az///DO+fPmisCSjuHg8Hv7880/ExcWhZ8+euHXrFqpVq8ZJLP/1o7ZaHrVr10bPnj1x7Ngx5Obmyj0Xy8TEBE+ePFFobGWJWgwSSiQSiESiEpVR2C9QSSfiiEQiZGVlwcjICE5OTli2bBlCQ0MRHh7OegUYjZKbm4vhw4fj1q1bOHPmDKytrbkOqUQSExORnZ2t0Id2ly5dkJubi8uXLyusTHno6urixIkT0NLSgpubG1JTUzmNJ48i2uqCVK9eHRKJpNAe2qLIa6sZ+ahFMiASiSCRSJRaR96cgIIyx9jY2ELvk0gkGjmeyjBfIyJMnz4dx44dw8GDB/N11WoiIkJiYiIyMzMVmgxYWFigTp06CA4OVliZ8qpUqRJOnz6Np0+fYvjw4ZBKpVyHpLS2Oi4uDjo6OnLPRQBYW11SapEMGBgYyLrzlaVy5cpo1KgRdu3aheTkZNnrwcHBePDgQaH3JSUlwcDAQKmxMYyyrV69Gps2bcLWrVvRs2dPrsMpseTkZOTk5Ch8mAD4t3fg4sWLCi1TXnZ2djhw4ABOnjyJefPmcR1OidvqvI2ivnbv3j2cOnUKXbt2LdGKFtZWl4xazBmwtbXFpUuXCv1+UFAQHj169M3rrVu3LtYvz6pVq9C9e3e0bdsW7u7u+Pz5MzZt2oT69esX2g0XFRWFLl26FLkOhlE3u3fvxty5c7Fw4UJMmDCB63AUIm/yIKC4CYR5unbtiq1btyIuLg41a9ZUaNnycHV1xZo1azBz5kxYWVlxOlv+R231jwwcOBC6urpo3bo1zM3N8eDBA+zYsQN6enr49ddfSxQba6tLSJE7GMnLz8+PeDwepaSk5Hv9R2cT+Pv70/PnzwkA+fj4fFMuAFq8eHG+144ePUrW1takra1NNjY2dOzYsUJ3IExJSSEej0f+/v4KfLcMozpBQUEkFAppzJgxGrW74I9cv35d1g5cvXpVoWV/+fKFBAIB+fr6KrTckpBKpTR27FjS0tKi0NBQzuIorK0uqg0bNlDz5s3J1NSUhEIhVa5cmYYNG0ZPnjwpUVysrS6cRh1UdO/ePQJAYWFhSilfXqGhoQSA/vnnH65DYZhiu337Nunr65Orqyvnp8sp2qlTp2TJwP379xVefps2bahPnz4KL7cksrKyqEOHDlS+fHnZoTyqxtpqzaNR2xHb2NjAxMQEp06d4jqUfE6dOgVTU1ONn3XNlD3Pnj1D9+7d0aBBAxw8eBBCoVqMCCrM12PPylgC2KVLF/z1118K2y5XEUQiEQIDA2FqagpXV1dOdttjbXXppRbJgFAohLu7O/z8/JCRkcF1OACAjIwM+Pn5wd3dvdQ1pEzp9vHjRzg5OcHY2BhnzpyBvr4+1yEpXGJioux9KSMZ6Nq1K758+VLibXIVzdTUFGfOnMGHDx8wcOBAlScrrK0uvdQiGQAADw8PfP78GYcPH+Y6FADAoUOHkJSUBA8PD65DYZgiS01NRffu3ZGWlobz58+jQoUKXIekFAkJCdDT04NIJIKurq7Cy2/WrBmMjIzUYonhf9WtWxeBgYH466+/MG3aNJXXz9rq0kltkoHatWvDyckJ69at47xrLicnB+vXr4ezszNq1arFaSwMU1TZ2dno378/YmNjce7cOVhaWnIdktIkJiZCR0cHxsbGStn8SygUomPHjmqzxPC/OnbsiC1btmDLli3YvHmz0uvLyclBZGQkNm3ahPnz50NHRwerV69mbXVposgJCCUVHh5OfD6fvL29lVrPj6xcuZL4fD6Fh4dzGgfDFJVUKqWRI0eSlpYWBQcHcx2O0nXv3p1q1apF9erVU1odW7duJaFQqPR2rySmT59OfD6fgoKClFJ+WloadevWjXR0dAgA8Xg8EggEsv/P2mr1p1GrCb42e/ZsEolEFBMTo/S6ChIdHU1aWlo0Z84cTupnGHnMmzePANC+ffu4DkUlWrRoQXXq1KEWLVoorY6nT58SADp58qTS6iipnJwc6t69OxkaGiplVUVmZiZVq1at0OXdQqGQtdVqrqjPbx7RjzfvT0lJgZGREZKTk2FoaKicLor/yczMROPGjaGvr4+wsDDo6ekptb6vpaenw8HBARkZGYiMjISOjo7K6mYYeW3duhWTJk2Cj48PPD09uQ5HJWrXrg2BQABLS8sSnXT3I7Vq1UK3bt2wadMmpdVRUmKxGG3atEFqairCw8NhZmam0PL/+ecftGjRAllZWd+c9SIQCNCgQQNcv36dtdVqqqjPb7WZM5BHR0cHe/fuxaNHj9CvXz+ln1mQRyKRoF+/foiNjcWePXvYLxejEY4dO4ZffvkF06ZNw8yZM7kOR2USEhIglUoVvhXxf6nT1sSFMTAwwOnTp5GWloY+ffoo/LCevC2RC/rcmJubi+joaPTu3Zu11ZpOkd0MihQcHEwikYhcXFwoLS1NqXWlpaWRi4sLiUQiCgkJUWpdDKMoYWFhpK2tTQMHDqTc3Fyuw1GZrKwsAkA1atQgDw8PpdZ19OhRAkAvXrxQaj2KcP36ddLW1qYRI0YoZbfJFStWFDpcwOfzycnJibXVakijNh0qSOfOnXH27FmEhYXB0dER9+/fV0o9MTExcHBwQFhYGM6dO4dOnToppR6GUaT79++jR48eaN26NXbt2lWiA140Td65BFlZWUrZY+BrHTt2BJ/PV8slhv/VqlUr+Pn5Yffu3fjtt98UXv6LFy8K/Z5UKsWVK1dYW63B1LoF6dy5M0JDQ5GWloYmTZpg1apVClvKkpOTA29vb9jb2yMjIwOhoaHsl4vRCG/evIGzszNq1KiB48ePl7ljW/OSgbS0NKUPExgbG6N58+YakQwAwJAhQ7Bw4UJ4eXnh2LFjCilTIpGgWbNm2LlzJ2rVqgVbW9t8m/sIBAJ0794dYWFhrK3WZIrsZlCWjIwMmj17NvH5fLKzsyN/f39KT0+Xq6z09HTy9/cnOzs74vP5NGfOHMrIyFBwxAyjHElJSdSgQQOqUaMGvX37lutwOBESEiLrnt6+fbvS61u4cCGZmppSTk6O0utShNzcXBowYADp6elRREREicp6+fIlmZmZEQDq1asX5ebm0uvXr6lChQrE5/Nl/w6XL18mItZWqyONXVr4PTdv3iRnZ2cCQCYmJjRz5kwKDQ394QlaKSkpFBoaSjNnziQTExMCQM7OzmxtKqNRMjIyyNHRkUxMTOjBgwdch8OZgwcPyh5Chw4dUnp9V65cIQB0+/ZtpdelKOnp6dSsWTOqUqUKvXnzRq4y8uZtAaCVK1fm+96NGzdIS0uLAJCtre03cxQU0VYbGhqytloBNHZpYVE8ffoU27dvh5+fHz5//gwej4e6deuiUaNGMDExgUgkgkQiQVJSEqKiovD48WMQEUxNTeHu7g4PDw+2WxWjUXJzczFo0CCcOXMGly5dQuvWrbkOiTObN2/GzJkzIZFIcPHiRaWfYZ+dnY3y5ctj7ty5mDdvnlLrUqT4+Hg0b94cFStWLPYybR8fH8yZMwdCoRCnTp2Cs7PzN9fs2bMHI0aMwL59+zBkyJACyylJWy0Wi/Hzzz9jw4YNcv8MmKI/vzUyGciTk5ODhw8fIiIiAhEREYiOjoZYLEZWVha0tbVhYGAAW1tb2Nvbw97eHtbW1uwgC0bjEBGmTp2KLVu24NixY+jZsyfXIXFqyZIl2Lp1KxISEnDr1i00a9ZM6XX27NkTKSkpuHz5stLrUqSoqCi0bdsWzs7OOHz48A8nmkqlUgwYMABHjx5F+fLlcefOHVhYWBR6/evXr1G9evUfxiFPW+3h4YGQkBDExcWVqQmyilbk57ciuxkYhlG8X3/9lQCQr68v16GohYkTJ1KtWrUIAD158kQldW7atIm0tLRILBarpD5FOnHiBPF4PJo3b953rxOLxWRlZUUAqEmTJpyPz1+/fp0AsCWEJaTxSwsZhvm3K3bu3LlYuHAhJkyYwHU4akHZxxcXpGvXrsjOzkZoaKhK6lOknj174rfffoO3tzf27NlT4DUPHz5E1apV8ejRI4wePRoRERGcb+bTsmVLWFlZ4c8//+Q0jrKCJQMMo6YuXLgAd3d3jBkzBkuXLuU6HLWRd2IhABgZGSm1LqlUivT0dNSpUwc1atTQmCWG/+Xp6YnRo0dj7NixuHbtWr7vBQYGwtbWFmKxGNu2bYOfnx9HUebH4/Hg7u6OY8eOISkpietwSj2WDDCMGoqIiEDfvn3h5OQEX19fpRzTq6kSEhIgEolQrlw5aGlpKbWuI0eOwNDQEGPHjkWrVq3UfmviwvB4PPj6+qJly5bo1asXnj9/DgDw8vJC//79IRKJcO3aNXh4eHAcaX7Dhw9HTk4ODhw4wHUopZ5GTyBkmNLo2bNnaN26NSwsLPDXX3/JusSZf1WpUgV169bFs2fP8Pr1a6XWtXnzZkyePBlCoRBSqRRSqRTXrl3T2NUciYmJaNmyJbS0tFCxYkWEhoaiatWqiIyMhLm5OdfhFahnz554+/Yt7ty5w3UoGkljDypimLLs48ePcHZ2hpGREc6cOcMSgf8gItkOhKqaL8Dn85GTkwOpVAoAcHBwwJgxY2SfrjVJhQoVsHv3bsTGxiI0NBTt2rXDixcv1DYRAAB3d3dERETg3r17XIdSqrFkgGHURGpqKlxdXSEWi3HhwgWFH0VbGqSkpCA7O1slJxYWRiqVYteuXahTp47GJQW3b99Gly5dQETg8Xho2LCh2i+37tatGypWrAh/f3+uQynVWDLAMGogOzsbAwYMwMOHDxEUFARLS0uuQ1JLCQkJAP79eamqZ6Agubm5yM3N1aikYOfOnWjZsiWysrJw8OBBbNmyBRs3bsS2bdu4Du27tLS0MGLECOzZs0fhxzMz/0+9U0KGKQOICOPHj0dwcDDOnTuHxo0bcx2S2lLliYVFkZubCwDw9/eHv78/WrVqhXnz5iEoKAhCoRBaWlowMDBAjRo1UL16ddn/qnrZ3oQJE7Bjxw4YGBjg+vXraNCgAYB/lxROnjwZtWvXVvpOjiUxevRo+Pj44NSpU+jfvz/X4ZRKLBlgGI4tXLgQAQEB2Lt3r1o3yOogr2dAFScWAv+e2FeEOdayax48eIDHjx/jypUryMnJQXZ2NpKTk/Hx48d815uZmcHOzg4dOnRAhw4d0KxZM6WsjJBIJGjbti1u376NOnXq4M6dO/kmka1btw5PnjxB//79cfPmTVhZWSk8BkWwtraWHdHMkgElUeQORgzDFM/WrVsJAK1evZrrUDSCn58fAaAqVarQokWLlFJHamoqbdmyhTp06EACgUB2KFJBX3kn91lbW1NgYCDl5uYWWGZGRgY9efKE/vrrLwoICKClS5eSq6srGRgYEADS19enrl270o4dOyg1NVUh76OgEwcL8uXLF7KxsaFatWpRYmKiQupWhj/++IN4PB69evWK61A0Sqk8tZBhSpNjx44Rj8ejqVOnfnPqG1Ow1atXk7GxMenr69O6desUWvabN29o7ty5ZGJiQnw+n7p160Z9+/bNd1Tvf79+lAT8SHZ2NoWHh9Ovv/5KnTt3Jh6PR8bGxjRz5kx69uyZ3O8lJCREduLgihUrfnh9XFwcVahQgRwdHSkrK0vuepUpOTmZ9PT0ivR+mP/HkgGGUWNXrlwhbW1tGjBggNwPkrJo1qxZVLt2bQJA/v7+CikzPT2dpk2bRkKhkAwNDWnGjBn0/PlzIvr3TIKvk4Gv//+CBQsU/m8XFxdHs2bNIhMTE+LxeDRkyBD6+PFjscpYvXo18Xg80tLSoqCgoCLfd/XqVRKJROTu7q62yenIkSOpZs2a7G+mGNjZBAyjph48eAA3Nze0atUKu3fvZieyFUNiYqJs4qAiJhDevn0bTZo0ga+vL5YvX47Xr19j7dq1+U7qIyLZv1G9evVw5MgRVKlSBenp6fn+7TIzM3H9+nWkpKTIHY+lpSVWr16NN2/eYNu2bbhw4QKsra2xf//+H85dkEql6N+/P2bPng1TU1M8fvy4wKOHC9OmTRvs3LkTfn5+WLNmjdzvQZnGjBmDuLg4XLlyhetQSh9FZhYMw3zf69evqXr16mRra0tfvnzhOhyN4+rqSh07diQA9Pfff5eorLVr15JAIKCmTZvSgwcPCrxmx44dBQ4HjB49mho0aED//PMPrV27ljp37kza2toEQKHDFx8+fKCBAwcSAOrZsyelpaUVeJ0iTxycN28e8Xg8OnHihNxlKItUKqXatWvT8OHDuQ5FY7BhAoZRM0lJSdSgQQOqUaMGvXnzhutwNFLLli3Jzc2NAFBUVJTc5fz+++8EgGbNmkUSiaTQ61JTU+nKlSuyJCA+Pp52795Nbdu2zTd0wOPxZP+tjIfo8ePHSV9fnzp06PDNBMMHDx6QkZERAaDRo0eXuK7c3Fzq27cv6enp0d27d0tcnqJ5e3uTrq4uS6aLiCUDDKNGMjIyyNHRkUxMTAr9FMr8WK1atah///4EgF68eCFXGX/++acsESjK2Pjr169p5syZZG1tLXvgf2+VgbISvbCwMNLX16f27dvLEoIjR46QUCgkHo9HW7duVVhdqampZG9vT9WqVaN3794prFxFePPmDfH5fNq+fTvXoWgElgwwjJrIycmhfv36kY6ODl27do3rcDSakZERDR06VO72KCYmhgQCAXl4eBR5ktzatWu/u7zw66/y5csrdfLdlStXSF9fn8aPH09z584lAKSjo0PXr19XeF1v3ryhKlWqULNmzSg9PV3h5ZdEt27dqEWLFlyHoRFYMsAwakAqldLkyZOJz+er5RisJsnKyiIANGLECOLz+cWeUS6VSqlr165Uq1YtyszMLPJ9EomEOnXq9MM9B3g8Hrm4uBT3bRUY5/ds2LBBVmfVqlXpw4cPJa6zMBEREaSnp6d2q14CAwMJAMXExHAditpjqwkYRg2sXr0amzZtwtatW9GzZ0+uw9Fonz59AgDweDwYGRkVexVGUFAQLl68iLVr10JbW7vI92lpaeH48eOwsbGBQCAo9DqBQIBmzZoVK6b/ioiIQNWqVfH3338X+P3ExETZTH99fX08e/ZMqScONmnSBHv27MHhw4exdOlSpdVTXG5ubqhQoQI7vEiRFJlZMAzz/3bv3k0AaOHChVyHUir8888/BICGDx9ONWvWLPb9/fv3J3t7e7m78ePj46l69erf7SFo0KABNW7cmOrXr0+NGzcmR0dHmjRpEvn5+dG9e/coOzv7u3X07duXAJCxsfE3mw7dunWL9PT0CIBs3oSqhp28vb0JAO3bt08l9RXF9OnTyczMTG03SVIXrGeAYTh04cIFuLu7Y8yYMWr1iUqTleTEQqlUisuXL8PFxQU8Hk+u+itVqoSQkBAYGBjIysjrKeDxeKhVqxYaNGiAli1bonPnzmjZsiWqVKmCS5cuYcyYMWjYsCHMzc3h6emJp0+fflP+ixcvcOzYMQD/HmfdvXt3iMViAN+eOHjgwAGUL18eZ8+eleu9FNfcuXMxYsQIuLu748aNGyqp80fc3d2RkJCgsp9BqafIzIJhGKI7d+6Qvr4+de/e/YefBJmiO3ToEAGgPn36UMeOHYt1b16vwl9//VWiGG7evEktW7YkAGRoaEienp4UFhZGKSkp370vJSWFwsLCyNPTk0xNTQkAOTk5UXh4uOyaadOm5et1EAgE5OrqSuPGjSMAZGBgQNHR0bLrhw4dSo0aNSrR+ymOzMxMatu2LZmbm8u9kkPRmjVrRq6urlyHodbYBEKG4cDTp0/J3NycmjdvrrADZ5h/bd68mbS0tKhLly7Ut2/fYt0bEhJCACguLk6uujMyMmj27NnE5/PJzs6OAgIC5J5hn56eTgEBAWRnZ0d8Pp9mz55N79+/lw0BFPRVp06db9rfFStWkJmZmVwxyOvjx49kaWlJDRo0+GECpArbtm0jPp9Pb9++5ToUtcWGCRhGxT5+/AhnZ2cYGRnhzJkz0NfX5zqkUiUxMRFmZmZITk4u9jCBSCQC8O+RvsUVERGBxo0b4/fff8eKFSsQERGBkSNHQldXt9hlAYCuri5GjhyJiIgIrFixAr///jsaNWqE9PT0Qu9ZtGhRvqOHAcg93FESZmZmOHPmDF69eoXBgwcjNzdX5TF8bdCgQRCJRNizZw+ncZQGLBlgGAVITU2Fq6srxGIxLly4ADMzM65DKnUSEhJQoUIFfPnyBSYmJsW6N2/1wPceuAUJCQmBo6Mj9PX1ERkZCS8vLwiFwmKVURihUAgvLy9ERkaiUqVK310dMWbMGNy+fTvfazk5OQqJo7hsbGxw6NAhBAUFYdasWZzEkMfY2Bj9+vWDn5/fD89uYL6PJQMMU0LZ2dkYMGAAHj58iKCgIFhaWnIdUqmUmJiIChUqICkpqdg9A9bW1hCJRAgLCyvyPSEhIejevTvat2+PsLAw1K9fv5gRF039+vVx7do1dO7cudCEIDc3F927d8e7d+9kr928eRMNGjRQSkw/4uzsjA0bNmD9+vX4448/OIkhj7u7Ox4/foxr165xGoemY8kAw5QAEWH8+PEIDg7GsWPH0LhxY65DKrUSEhJgZmaGL1++FDsZMDAwQKdOnXDy5MkiXR8REYFevXqhU6dOOH78OPT09OSIuOj09PRw+vTpQhOC3NxcfPr0CW5ubsjOzkZ6ejouX76M7t27KzWu7/nll18wceJETJw4EX/99RdncbRr1w6Wlpbw8/PjLIbSgCUDDFMCCxcuREBAAAICAtClSxeuwynV8o4vzs7OLvYwAQD06tULYWFhePLkyXevy8zMxLBhw2BlZYXAwEDZfANlE4lEOH78OGxtbfNtbiQQCMDj8SCVSvH8+XMkJSXh6NGjyMzM5DQZAIANGzagY8eO6Nu3Lx4/fsxJDHw+H6NHj8bhw4dlSzGZ4mPJAMPIadu2bVi5ciVWr16NoUOHch1OqZeQkCCblFncngEAGDZsGGrUqAEPD4/vji8vXrwYcXFx2LVrl9J7BP5LT08Pe/fulU0OrFy5Mvr374+NGzciMjISHz9+hLa2NmbPno3evXvDyspKpfH9l1AoxKFDh1CpUiW4urri8+fPnMQxcuRIpKen48iRI5zUXyoocmkCw5QVx44dIx6PR1OnTlXqwTTMv6RSKWlpadH8+fNLtPPe+fPnCQAFBAQU+P2bN28Sn88nb2/vkoRbYitXriQ+n59vH4I8kydPJn19fXr16hUHkRXs6dOnVL58eerQocN3j4RWpq5du1KbNm04qVudsX0GGEZJrly5Qtra2mp3eEtpltcGLV26lACU6BjoYcOGkY6ODl24cOGb7zk5OZGdnR3nm0VlZ2eTnZ0dOTs753t948aNBIDWr1/PTWDfERoaSlpaWjRu3DhOEuS8TakePXqk8rrVGUsGGEYJ7t+/T8bGxtS+fftinXzHlMzTp08JAK1YsYIA0Lt37+QuKyMjg7p3707a2tp07tw52etPnjz5bq/Bjzx+/JgGDhxIVatWJV1dXapXrx4tXbqU0tLS5CrP39+fANDTp0+J6P9PK/T09FTb3qi8mNetW6fyujMzM8nU1JRmz56t8rrVGUsGGEbBXr9+TdWrVydbW1v68uUL1+GUKTdv3iQAsgNz5N39L09mZib16NGDRCIRrVu3jnJycmjmzJlkamoqV9mvXr0iY2Nj+umnn2jVqlW0fft2GjVqFAGgHj16yBVjeno6mZiY0NSpU2nGjBkEgGbNmqW2iUCeOXPmEI/Ho9OnT6u87smTJ1PFihU5G6pQRywZYBgFSkpKogYNGlCNGjXozZs3XIdT5pw+fZoA0PLly0lbW1shZWZlZdGUKVOIx+NR8+bNycjIiDw9PeUqa+XKlQSAYmJi8r0+YsQIAkCfP3+Wq9yZM2eSlpYWaWtr05o1a9Q+ESAiys3NpV69elG5cuXo3r17Kq377t27BIBOnTql0nrVGduOmGEUJDMzE7169cLbt29x/vx5VK1aleuQypzExEQA/+66J89KgoKIRCJs2LABV69excePH5GcnIwePXrIVVZKSgoAoGLFivler1y5Mvh8vtzLE3v06IHs7GwcOXIEM2fO5GQL4uLi8/nYs2cPateuDTc3N3z48EFldTdq1AiNGzdmew7IgSUDDPMdUqkUI0aMQHh4OE6fPg1ra2uuQyqTEhISYGRkBLFYrLBkIE/r1q3h5eUFHo8n96ZR7du3B/DvtsFRUVF4/fo1Dh06hG3btmHKlClyn1PRuHFj8Hg8fPr0Sa77uVKuXDmcPn0a2dnZ6NWrFzIzM1VWt7u7O86cOaPSJKQ0YMkAwxSCiDB9+nQcPXoUBw4cQJs2bbgOqcz6eitieTYc+pF//vkH9erVQ7ly5eS639nZGcuXL0dwcDAaN26MGjVqYNCgQZg8eTLWr18vd1wGBgaoW7cuIiIi5C6DK9WqVcPJkycRFRUFd3d3lZ0dMGTIEAgEAuzdu1cl9ZUWLBlgmEL4+Phg48aN2LJlC3r16sV1OGVaSbYiLoro6Gg0atSoRGVYWFjA0dERO3bswNGjR+Hu7g5vb29s3ry5ROU2atQI0dHRJSqDK82aNcPu3btx4MABLF++XCV1mpqaonfv3vjzzz/Z4UXFoJjjtximlNmzZw/mzJmDBQsWwMPDg+twyry8noEvX76gUqVKCi9fLBaXqMfh4MGDGD9+PB4/foxq1aoBAPr06QOpVIo5c+Zg8ODBKF++vFxlm5iY/HALZXXWv39/LF++HAsXLkS9evUwcOBApdfp7u6Orl27Ijw8HC1btlR6faUB6xlgmP+4ePEi3N3d4e7ujmXLlnEdDoN/kwEzMzO5TiwsColEUqIzCLZu3YrGjRvLEoE8PXr0QHp6Ou7evSt32SKRCFlZWXLfrw7mz5+PoUOHYtSoUbh165bS6+vYsSNq1KjBJhIWA0sGGOYrkZGR6Nu3L7p27QpfX1+NmL1dFiQkJMh6BpSRDIhEIkgkErnv//DhA3Jzc795PTs7G8C/qyDkJZFIoK2tLff96oDH42Hnzp1o3LgxevTogdevXyu1PoFAgFGjRuHgwYNIS0tTal2lBUsGGOZ/4uLi4OLiAhsbGxw+fBhaWlpch8T8T17PwJcvX5QygdDAwABJSUly31+3bl3cvXv3m5P7Dhw4AD6fDzs7O7nLTkpKgoGBgdz3qwsdHR2cOHECOjo6cHNzQ2pqqlLrGzVqFMRiMY4eParUekoLlgwwDP795Onk5AQjIyOcOXNG7qVgjOJlZ2fjy5cvMDU1RXJyslJ6BmxtbREVFSX3/bNmzUJubi4cHBywfPlybN26Fd26dcOJEyfg7u6OKlWqyF12VFQUbG1t5b5fnZibm+PMmTOIi4vD0KFDC+xNURRLS0t06tSJDRUUEUsGmDIvLS0N3bt3h1gsxvnz52FmZsZ1SMxX8tbY6+vrg4iUkgzY29sjNjYWYrFYrvsdHR1x/fp12NvbY+vWrZg2bRqePXuGlStXYtu2bXLHJRaL8fjxY9jb28tdhrpp0KABDh48iDNnzsDLy0updbm7uyM0NBRPnz5Vaj2lAUsGmDItOzsbAwYMwMOHD3Hu3DnUrFmT65CY/0hISAAA2QQ/ZQwT2Nvbg4hK1DvQvHlznDt3DvHx8ZBIJIiNjcW8efMgFMq/aOvu3bsgolKVDABAt27dsHbtWvj4+ODPP/9UWj29e/eGkZER/P39lVZHacGSAabMIiJ4eHjg4sWLOHbsGJo0acJ1SEwB8rYiFggEAKCUngEbGxuYmJjg1KlTCi+7JE6dOgVTU9NSufPl1KlTMWHCBHh4eCA0NFQpdejq6mLIkCEICAhQ6pBEacCSAabMWrRoEfz8/ODv748uXbpwHQ5TiLyeAT7/3+ZKGcmAUCiEu7s7/Pz8kJGRofDy5ZGRkQE/Pz+4u7uXqHdBXfF4PGzatAnt2rVDnz59lNaV7+7ujnfv3uHixYtKKb+0YMkAUyZt27YNK1aswOrVqzFs2DCuw2G+IzExEVpaWrKlf8oYJgAADw8PfP78GYcPH1ZK+cV16NAhJCUllXhnRHWmpaWFI0eOoEKFCnB1dS3Rio7C2Nvbw9bWlk0k/AGWDDBlzvHjxzFp0iRMnToVnp6eXIfD/EDe7oPJyckAACMjI6XUU7t2bTg5OWHdunUl2hdAEXJycrBu3ToYGRlh2LBh6NChA8LCwjiNSVlMTExw5swZfPz4EQMGDJDtzaAoPB4P7u7uOHnypGzIifkWSwaYMuXq1asYPHgw+vfvj3Xr1rFNhTTA1xsOGRgYKLXLfNmyZYiJiYGPj4/S6iiK1atX4/79+7hw4QJOnDiBpKQktGvXDp06dcLVq1c5jU0Z6tSpg2PHjuHvv//GlClTFH6mQF7vHzu8qHAsGWDKjAcPHsDNzQ2tWrXC7t27ZWPQjHpT9lbEX2vevDk8PT2xZMkS3L9/X6l1FSYmJgZLlizBrFmz0KJFC/Ts2RORkZE4evQoEhIS4ODggK5du+LGjRucxKcs7du3x7Zt2+Dr64tNmzYptOwKFSqgZ8+e8PPzY4cXFYK1hkyZ8ObNGzg7O6N69eo4ceKExm/vWpYoeyvi/1q6dClq1qyJkSNHIj09Xen1fS09PR0jR45E7dq1sWTJEtnrfD4fffr0QVRUFI4cOYJ3796hdevWcHZ2Rnh4uEpjVKaxY8di5syZmD59OoKCghRatru7O6KjozXyOGhVYMkAU+p9+fIFLi4u4PF4CAoKUtqYM6Mcyt6K+L90dHSwd+9ePHr0CP369SvRmQXFIZFI0K9fP8TGxmLPnj3Q0dH55ho+n49+/frhn3/+wcGDB/Hq1Su0bNkS3bt3x507d1QSp7L99ttv6N69OwYOHIiYmBiFldu1a1dUrVqVTSQsBEsGmFItMzMTvXr1wtu3b3H+/HlUrVqV65CYYsrrGVDFMEEee3t7nDhxApcuXUKvXr2U3kOQnp6OXr164dKlSzh58uQPNxni8/kYOHAgoqOjsX//fjx79gzNmjWDm5sbIiMjlRqrsgkEAuzfvx+WlpZwc3PDx48fFVbuyJEjsX//frVZPqpOWDLAlFpSqRQjRoxAeHg4Tp8+XSo3bintiEi2mkBVwwR5OnfujLNnzyIsLAyOjo5Km0MQExMDBwcHhIWF4dy5c+jUqVOR7xUIBBg8eDDu37+PPXv2IDY2Fvb29ujVq1eJdlPkWrly5XD69GlkZGSgd+/eyMzMVEi5o0ePRnJyMo4fP66Q8koTlgwwpRIRYfr06Th69CgOHDiANm3acB0SIwexWAyJRKLSYYKvde7cGaGhoUhLS0OTJk2watUqhS07zMnJgbe3N+zt7ZGRkYHQ0NBiJQJfEwgEGDZsGB48eIBdu3YhJiYGjRs3Rp8+ffDPP/8oJF5Vq1GjBk6ePImIiAiMGzdOIRP/ateujXbt2rGhgoJQESQnJxMASk5OLsrlDMO53377jQDQtm3buA6FKYFnz54RAAoJCaEqVarQ4sWLOYkjIyODZs+eTXw+nxo0aED+/v6Unp4uV1np6enk7+9PdnZ2xOfzac6cOZSRkaHQeLOzs8nf358sLS0JAPXr14+io6MVWoeqHDhwgADQypUrFVLerl27CADFxcUppDx1V9TnN0sGmFJn9+7dBIAWLFjAdShMCd28eZMA0L1790hPT4/Wr1/PaTx///03aWtrEwAyMTGhmTNnUmhoKKWkpHz3vpSUFAoNDaWZM2eSiYkJASBnZ2cKDw9XarwSiYR27txJFhYWxOPxaMCAAXT//n2l1qkMS5YsIQB05MiREpeVmppKBgYGtGjRIgVEpv5YMsCUSRcuXCChUEju7u4klUq5DocpoTNnzhAAev78OQGggIAATuPZuXMn8Xg8CgkJIU9PTzI1NSUAxOPxqF69ejRw4EDy8PCgKVOmkIeHBw0cOJDq1atHPB6PAJCpqSl5enrS06dPVRp3VlYW7dixg2rUqEE8Ho8GDx5MDx8+VGkMJSGVSmnQoEGkq6tLt2/fLnF548aNo+rVq1NOTo4ColNvRX1+84h+PBCTkpICIyMjJCcnw9DQUNEjFQyjEJGRkWjXrh0cHR1x4sQJaGlpcR0SU0K7du3CqFGj8Pr1a9keET179uQkFiJCo0aNUKNGDZw+fRrAv+P+Dx8+REREBCIiIhAdHQ2xWIysrCxoa2vDwMAAtra2sLe3h729PaytrTk9dEgikcDPzw8rV67Eu3fvMHjwYCxatAh169blLKaiysjIQIcOHfDq1SvcunUL1apVk7usmzdvolWrVrh48WKpP6SsyM9vRWYWDMOVZ8+ekbm5OTVv3pxSU1O5DodREB8fHzI0NKTY2FgCQH///TdnsVy+fJkA0MWLFzmLQVEyMzNpy5YtVKVKFeLz+TRixAh68uQJ12H9UHx8PFWvXp0aN25cor9zqVRK1tbWNGjQIAVGp56K+vxmqwkYjZeQkAAnJycYGRnhzJkz0NfX5zokRkG+3ooYUN6JhUWxceNGWFtbo3PnzpzFoCja2tqYOHEinj17ht9//x3BwcGwsrLC6NGjERcXx3V4hapUqRLOnDmDx48fY/jw4ZBKpXKVw+PxMGbMGBw/fhyfP39WcJSaiSUDjEZLS0tD9+7dIRaLcf78eZiZmXEdEqNAX29FDECl+wx87cWLFzh58iSmTJlSqg630tHRweTJk/Hs2TOsXbsWQUFBqFu3LsaOHYsXL15wHV6B7OzscODAAZw4cQLz58+Xu5xhw4YhNzcX+/fvV2B0moslA4zGys7OxoABA/Dw4UOcO3cONWvW5DokRsG+3ooY4K5nYMuWLTA0NMTw4cM5qV/ZdHV1MXXqVMTFxWH16tU4ffo06tSpg/Hjx+Ply5dch/cNNzc3+Pj44Ndff8WuXbvkKqNixYpwdXVlew78D0sGGI1ERPDw8MDFixdx7NgxNGnShOuQGCX4eitiPp+PcuXKqTyGtLQ07Ny5E2PHji31Q1B6enqYMWMG4uLisGrVKpw4cQJ16tSBh4cHXr16xXV4+cyYMQNjxozBuHHjcOXKFbnKcHd3x927d3H37l0FR6d5WDLAaKRFixbBz88P/v7+pX42cFn2362Iueii37NnD1JSUjBp0iSV180VfX19eHp6Ii4uDsuXL0dgYCBq166NSZMm4c2bN1yHB+Dfcf+tW7eiTZs26N27t1xzHVxcXFCpUiX4+/srIULNwpIBRuP4+vpixYoV+O233zBs2DCuw2GUKCEhgbOtiIF/e6A2btyInj17wsLCQuX1c61cuXKYM2cOnj9/jqVLl+LgwYOoVasWJk+ejHfv3nEdHkQiEY4ePQoTExO4uroiOTm5WPcLhUKMGDECe/fuVdj5B5qKJQOMRjlx4gQmTZqEKVOmYNasWVyHwyhRdnY2vnz5ovITC78WEhKChw8fYsqUKSqvW50YGBjAy8sLz58/x8KFC7F3717UrFkT06ZNQ3x8PKexmZqa4syZM4iPj8eAAQOKfXaEu7s7kpKScOrUKSVFqBlYMsBojGvXrmHw4MHo27cv1q9fX6pmdTPfylvyldczwEUysHHjRtjZ2aFdu3Yqr1sdGRoaYsGCBXjx4gXmzZuHgIAA1KxZEzNmzMCHDx84i6tevXoIDAzEpUuXMH369GLf26ZNG/z5559Kik4zsGSA0QgPHjyAm5sbWrRogd27d4PPZ7+6pV1CQgIAyHoGVD1M8PTpU5w9e7bULSdUBCMjIyxatAgvXrzA7Nmz8eeff8LS0hKzZs3Cx48fOYmpU6dO2LJlCzZv3owtW7YU6153d3cEBwer3SRJVWItKqP23r59C2dnZ1SrVg0nTpyAjo4O1yExKpCYmAiAu56BzZs3w9TUFEOGDFFpvZrE2NgYS5cuxfPnzzFz5kxs374dlpaWmDNnjuzfT5UmTJiAadOmYerUqbh48WKR7+vfvz/09PTkXqZYGrBkgFFrX758gYuLCwAgKCiIs01nGNX7umdA1cmAWCyGn58fxo8fD11dXZXVq6lMTU2xfPlyPH/+HNOmTcPWrVthYWEBLy8vfPr0SaWxrFmzBk5OTujfvz8ePHhQpHsMDAwwYMAA+Pv7y72roaZjyQCjtrKystC7d2+8efMG58+fR9WqVbkOiVGhxMRECIVCGBkZqXyYICAgAOnp6fj5559VVmdpUL58eaxcuRLPnz/HL7/8gk2bNsHCwgILFixQ2ba/AoEABw4cQI0aNeDm5lbkHgp3d3c8f/4coaGhSo5QPbFkgFFLUqkUI0aMwM2bN3Hq1CnY2NhwHRKjYnkbDgFQac+AVCrFpk2b0LdvX1SvXl0ldZY2FSpUwK+//ornz5/j559/xvr162FpaYlFixbJzplQJkNDQ5w+fRpisRh9+vRBVlbWD+9p06YN6tatW2Z3JGTJAKN2iAgzZsxAYGAg9u/fj7Zt23IdEsOBvA2H0tPTkZOTo7Jk4Pz583jy5EmZX06oCGZmZli9ejXi4uIwduxY+Pj4wNLSEkuXLi32ngDFZWFhgRMnTiA8PBwTJkwAEX33eh6PB3d3dwQGBsq2v87IyMC+ffvQvn17NGrUSKnxck6RRyAyjCKsXr2aANDWrVu5DoXh0KBBg6hDhw70+vVrAkDnzp1TSb1OTk5kb29PUqlUJfWVJfHx8TRt2jTS1tYmY2NjWrZsmdKfK3v37iUA9Ouvv/7w2nfv3hGfz6e5c+eSh4cHlStXjgAQADI0NFRqnMpS1Oc3SwYYlZJKpd9tZPfs2UMAaP78+SqMilFHnTt3pv79+1N0dDQBoOvXryu9zocPHxIA2rVrl9LrKsvevn1LkydPJm1tbTI1NaWVK1dSSkqK0upbsGAB8Xg8OnbsWIHfT0hIoBMnTtD69etlCYBQKJQlAgCobt26SotPmVgywKilxYsXU506dejJkyfffO/ixYskFApp9OjR7FMZQw0bNqSJEyfSlStXCAA9fPhQ6XVOnDiRzM3NKTMzU+l1MURv3ryhSZMmkUgkovLly9OqVatILBYrvJ7c3Fzq378/6enpUWRkpOz1nJwc2rZtG+no6BAA4vF4+RKAr786duyo8LhUoajPbzZngFGp3bt348mTJ2jevDnu3Lkjez0yMhJ9+vRBly5dsH37drbJCyObM5A34UzZcwa+fPmCXbt2wcPDA9ra2kqti/lX1apVsXnzZjx9+hQDBgzAokWLYGlpCR8fH6SlpSmsHj6fj4CAANjY2MDNzU12roKbmxt+/vln2bkEVMi8AoFAUOpXM7FkgFGZly9f4vnz5wCAlJQUODg4ICgoCHFxcXBxcYG1tTWOHDkCLS0tjiNluEZESExMlG04BCg/GfDz84NEIoGHh4dS62G+Vb16dWzduhVPnjxBnz59MG/ePNSsWRNr165Fenq6QurQ09OTnT/g5uaGNWvWICgoqEj38vl8VK5cWSFxqCseFZYKfSUlJQVGRkZITk6GoaGhKuJi1FBOTg4ePHiAiIgIREREIDo6GmKxGBKJBCKRCAYGBrC1tYW9vT3s7e1hY2MDoVAou3/nzp0YN26c7L95PB54PB4qVKgAIyMjXLt2DWZmZly8NUbNiMViGBoa4sCBA0hISMDs2bORkZGhtPpyc3NRp04dtG7dGnv37lVaPUzRvHjxAitXroS/vz8qVKiAuXPnYsKECQrZAOrWrVto3bo1cnNzi3wPj8fDwIEDUb58+WK3e1wr6vOb9QwwP/T06VN4enrC3NwcDRs2xJgxY3Dp0iVUqVIFLVu2ROfOndGyZUtUqVIFly5dwpgxY9CwYUOYm5vD09MTT58+BQBcuHABAoFAVi4RQSqV4uPHj+jRo4dsTTnDfL0VsSpOLDxz5gyeP3/OlhOqCQsLC/zxxx94/PgxunXrBk9PT9SqVQsbN24s0VHDX758wdy5c4u1y6BAIAAR4dChQ3K1expDkRMQmNLl5s2b5OTkRADI1NSUPD09KSws7IezflNSUigsLIw8PT3J1NSUAFDXrl1JT0+v0Mk5AOjnn3+mnJwcFb07Rp2Fh4cTAIqKiqLp06eTlZWVUuvr2LEjtWzZUql1MPJ78uQJjRw5kvh8PlWpUoU2b95c7Emejx8/ptq1a5NAIPhuO8Tj8YjP58uWE5ak3XNycqLw8PCSvPUSY6sJGLllZGTQ7Nmzic/nk52dHQUEBFB6erpcZaWnp1NAQADZ2tp+d6Zu3h9hr1695K6LKT3Onj1LAOjt27c0atQoatWqldLqylu6uH//fqXVwShGbGwsDRs2jPh8PlWrVo22bt1apKRg/fr1+R7y32uDeDwe2djYKKTds7OzIz6fT7Nnz6aMjAy5yioplgwwcrlz5w5ZWVmRSCQib29vys7OVki52dnZ5O3tTUKh8IeZebt27djSwjIuICCAAFBmZib16tWLXFxclFbXuHHjqEqVKiSRSJRWB6NYDx8+pCFDhhCPx6Pq1avT9u3bKSsrq8BrpVJpvs2DCvsSCAQkFAqV0u6JRCKytramO3fuKKTc4mBLC5liCwkJgaOjI/T19REZGQkvLy+FTYQRCoXw8vJCVFQUGjRoAD7/21+9vPkEurq6ZfbkMOZfiYmJMDAwgLa2tlLPJfj06RP27t2Ln3/+ma1i0SBWVlbYt28fYmJi0Lp1a3h4eKBu3brYuXMnsrOz81179uxZpKam5nvtv0uX+Xw+GjRogKioKKW0e5GRkdDT00O7du0QEhKikLIVjSUDDIB/E4Hu3bujffv2CAsLQ/369ZVST/369XH9+nV07twZfD5flhQYGxtjxowZiI2NRVBQUL6JhkzZk5CQIFtZoswTC3fu3Inc3FyMHz9eKeUzymVjY4ODBw8iOjoazZs3x7hx41CvXj34+fkhOzsbRIQFCxZ88+GjRo0aACBrg7p06YLr168rtd0LCwuDo6Mjunfvrp4JgSK7GRjNdOfOHdLX1ycXF5dCu9oULSsri7p27UpaWlr066+/qqxeRjOMGTOGmjdvTkREP/30E82bN0/hdWRnZ1P16tVp1KhRCi+b4ca9e/eoT58+BIBq1apFU6dOLXBIQCQS0fLly0kkEpGTk5NK2z0XFxfS19dX2ZABGyZgiiQzMxPDhg2DlZUVAgMDIRKJVFKvSCTC8ePHYWtri127drFhASafvA2HgH+XgymjZ+DkyZN4/fo1W05YitjZ2eHo0aO4e/cuGjRogA0bNhR4XU5ODry9vWFra4tjx46ptN0LDAxEvXr1MHz48BItk1Q0lgyUcYsXL0ZcXBx27doFPT09ldatp6eHXbt24dmzZ1iyZIlK62bUW0JCAipUqIDc3FwkJycrZc7Ahg0b4ODggMaNGyu8bIZbjRo1wqhRowr9vlQqRXZ2Nmv3vsKSgTIsPDwca9aswZIlS5Q2VvYjDRo0wOLFi+Hj44Nbt25xEgOjfvJ6BlJSUgAofiviu3fv4sqVK6xXoJSSSqWYP39+gROVgX8nEC5btoy1e19h2xGXYc7OzoiPj0dERASn22fm5OTA3t4eVapUKfJe4UzpZmpqijlz5mDAgAGoWbMmQkJC0KlTJ4WVP3r0aFy6dAlxcXFqtXUsoxhHjx5Fv379Cvwen8+HlZUV7t27VybaPbYdMfNdT58+xYULFzBjxoxi/0Hcv38f/fv3R82aNaGnp4cKFSrA0dERp0+flisWoVCI6dOn4/z583j27JlcZTClR05ODpKSkmRbEQOK7Rn4+PEj9u/fj0mTJrFEoBSSSqVYsGBBoSefSqVSzJ49W+5/+8jISPTo0QOmpqbQ09NDgwYNsHHjxmKXo27tHksGyihfX1+YmppiwIABxb735cuXEIvFGDlyJDZs2ICFCxcCAHr06IEdO3bIFc/AgQNhYmICX19fue5nSo9Pnz4BACpUqKCUEwt37NgBgUCAsWPHKqxMRn3ExMTg0aNHhR5HbGRkJFe7BwAXL15Eq1at8PHjRyxcuBAbNmyAq6sr3rx5I1d56tTusWGCMignJwfm5uYYM2YMfHx8FFJmbm4u7O3tkZmZiUePHslVhqenJ/z9/fHhwwf2ia0Mu3//Pho0aIBr164hPj4e/fr1w6dPn2BqalrisrOzs/HTTz/B1dVV7sSVUW9EhBs3biA1NRX07y67ICLk5ORg6NChmDBhglztXkpKCurWrYvWrVsjMDCw0PkIxaXsdo8NEzCFevDgAZKSktCjRw+FlSkQCFC9enXZJzl59OjRA58/f8bDhw8VFhejeRISEgD8e2Jh3u+Toj6EHD16FPHx8Zg8ebJCymPUD4/HQ+vWrdG1a1c4OTnB2dkZLi4u+OmnnyAWi+Vu9/bv348PHz5g5cqV4PP5SEtLU8iSaHVp91gyUAZFRESAx+OVeElVWloaEhMT8ezZM6xfvx5BQUElmuTVuHFj8Hg8RERElCguRrPlHV+cN0xgYGCgsE9MGzZsQMeOHWFra6uQ8hjNUdJ2LyQkBIaGhnj79i3q1auHcuXKwdDQED///HOJ9gtQl3aPJQNlUEREhOyXuSRmzpwJMzMz1K5dG56enujduzc2b94sd3kGBgaoW7cu538UDLcSExMhEAhgbGys0K2Ib926hZs3b7LlhGVUSdu9J0+eICcnBz179oSTkxOOHj0Kd3d3+Pr6YvTo0XLHpS7tHhuYLYOio6PRqFGjEpczbdo09OvXD+/evcPhw4eRm5sLiURSojIbNWqE6OjoEsfGaK68DYd4PJ5CDynauHEjLC0t4erqqpDyGM1S0nYvNTUV6enp8PDwkK0e6NOnDyQSCbZv345ly5ahTp06cpWtDu0e6xkog8RisUI+bVlZWaFz584YMWIEzpw5g9TUVLi5uRU6i7coTExMIBaLSxwbo7n+uxWxIpKB+Ph4HD58GL/88gs7BKuMKmm7p6urCwAYPHhwvteHDBkCALhx44bcZatDu8eSgTJIIpEoZS/ufv364fbt23j8+LHcZYhEImRlZSkwKkbT5PUMAIo7sdDX1xcikQju7u4lLovRTCVt96pUqQIAqFixYr7Xzc3NAUC2J4Y81KHdY8lAGSQSiUrcnV+QjIwMAEBycrLcZUgkEmhraysqJEYDKbpnICsrC76+vhg5cqRSzjhgNENJ2z17e3sAwNu3b/O9/u7dOwCQ/c7KQx3aPZYMlEEGBgYlymI/fvz4zWvZ2dnYvXs3dHV1YWNjI3fZSUlJMDAwkPt+RvN93TOgiBMLDx8+jI8fP7LlhGVcSdu9vI2K/vzzz3yv79y5E0KhEO3bt5e7bHVo99gEwjLI1tYWly5dkvv+CRMmICUlBY6OjqhatSrev3+Pffv24dGjR1i7dm2JVilERUWhS5cuct/PaL7ExMR8wwQl+TRPRNiwYQOcnJxgZWWloAgZTVTSdq9x48Zwd3eHn58fcnJy0K5dO/z99984cuQIvLy8ZMMI8lCHdo/1DJRB9vb2iI2NlXvCysCBA8Hn87Ft2zb8/PPPWLduHapVq4aTJ09ixowZcsclFovx+PFjWXccU/YQERISEhQ2THDjxg1ERESw5YRMids94N+5J0uWLEF4eDimTZuGu3fvYv369fD29pa7THVp91jPQBlkb28PIkJUVBQcHByKff+gQYMwaNAghcd19+5dEBHnfxQMd9LS0pCVlYUKFSogKysLGRkZJRom2LBhA+rUqQNnZ2cFRsloovLly5eo3QMALS0tLF68GIsXL1ZYXOrS7rGegTLIxsYGJiYmOHXqFNeh5HPq1CmYmprC2tqa61AYjhS0FbG8PQNv3rzB0aNHMXnyZIXtI89olrdv32LdunVo2rQpevbsCaFQyNq9QrC/kDJIKBTKxr7yVgBwLSMjA3/88QfKly+Pq1evlmivAkZz/XcrYkD+ZGDr1q3Q09PDyJEjFRQdowmSkpKwc+dOdOzYEdWrV8e8efNgYWGBo0ePYtKkSWrX7vn5+cHd3Z3zw9lYMlBGeXh44PPnzzh8+DDXoQAADh06hJSUFEilUnTo0AG2trbw9fVFamoq16ExKpSXDJiZmclmfsszTJCRkYEdO3bA3d2dnbRaBqSnp+Pw4cPo1asXKlasiAkTJkAoFMLPzw8fPnxAYGAg+vTpg19++UXt2r2kpCR4eHhwHQpLBsqq2rVrw8nJCevWrUNOTg6nseTk5GD9+vVwdnbGkydPEBISgjp16mDSpEmoVq0apk+fjidPnnAaI6MaecMEJe0ZOHDgAD5//oxffvlFgdEx6iQ7Oxvnz5/HiBEjULFiRQwcOBDv37/HmjVr8PbtW1y8eBGjRo2CkZGR7B51bfdq1arFaSwAACqC5ORkAkDJyclFuZzREOHh4cTn88nb25vTOFauXEl8Pp/Cw8Pzvf7ixQuaO3culS9fngCQs7MznT17lnJzczmKlFG2tWvXkoGBARERHThwgABQSkpKscqQSqVkZ2dHrq6uygiR4ZBUKqVr167RpEmTyMzMjACQlZUVLV++nJ48eVKkMtS93VO0oj6/WTJQxs2ePZtEIhHFxMRwUn90dDRpaWnRnDlzCr0mIyOD/P39qUmTJgSAatWqRWvXrqXPnz+rMFJGFebOnUuWlpZERLR161YSCAQklUqLVcbff/9NAOjixYvKCJHhQHR0NHl5eZGFhQUBoGrVqtGsWbPo7t27xf79INKMdk9RWDLAFElGRgZZWVmRvb09paWlqbTutLQ0atiwIdWuXZsyMjJ+eL1UKqUbN27QkCFDSEtLi/T09Gj8+PF07949FUTLqMLYsWOpefPmRETk7e1N5cuXL3YZvXv3Jmtra7keEoz6eP78Oa1atYpsbW0JAJmamtKECRMoNDS0xL2DXLd7TZo0IWtr6yK1eyVV1Oc3mzNQxuno6GDv3r149OgR+vXrp5QzCwoikUjQt29f3L9/H58/f8a9e/d+eA+Px0PLli2xb98+vHr1CnPnzsWZM2fQsGFDtGvXDoGBgcjOzlZB9IyylHQr4hcvXuDkyZOYMmUKeDyeMkJklCghIQFbt25F27ZtYWlpiWXLlqF+/fo4deoU4uPj4evrC0dHxxIvFeWy3evXrx9iY2OxZ88e6OjoqKTeIlFkZsForuDgYBKJROTi4qL0TDktLY1cXFxIJBJRYGAgtW7dmrS1tengwYPFLksikdChQ4fIwcGBAFDVqlVp+fLl9OHDByVEzihbmzZtaMSIEURENG7cOGratGmx7vf09CRjY2NKTU1VRniMEqSkpNCePXvIxcWFBAIBCQQC6tatG+3du5fEYrFS6+aq3QsJCVFqXV9jwwRMsQUHB5O+vj7Z29srbSwtOjqamjRpQvr6+rI/iIyMDBo2bBgBoGXLlsndvRsVFUVjx44lXV1dEolENGzYMLp58ybrLtYgdevWpZkzZxIRUf/+/alz585Fvjc1NZWMjY3J09NTWeExCpKVlUUnT56kgQMHkq6uLgGgtm3b0tatW+njx48qjYWrdk9VWDLAyOXOnTtkZWVFIpGIvL29KTs7WyHlZmdn08qVK0kkEpG1tTXduXMn3/elUiktW7aMANDQoUNLNJb26dMnWrNmDVlaWhIAatq0KQUEBKhkfI4pGVNTU1q1ahUREXXp0oX69+9f5Ht9fX2Jz+fT8+fPlRQdUxK5ubl0+fJlGjduHJmYmBAAsrOzo19//ZVevHjBaWxctXuqwJIBRm4ZGRk0e/Zs4vP5ZGdnR/7+/pSeni5XWenp6eTv7092dnbE5/Npzpw5330oHzx4kHR0dKh169Yl/oSQk5NDp0+fJicnJwJAFSpUIC8vL3r58mWJymWUIzs7m3g8Hu3cuZOIiJo2bUrjxo0r0r1SqZRsbGyod+/eygyRKSapVEoRERE0c+ZMqlq1KgEgCwsLmjdvHkVHR3MdXj5ctnvKxJIBpsRu3rxJzs7OBIBMTExo5syZFBoa+sN13ykpKRQaGkozZ86UfQJwdnYu8nramzdvUsWKFcnS0pLu37+viLdCsbGxNHXqVDI0NCQ+n099+vShv/76iw0hqJEPHz4QADpx4gQREdWuXZtmzZpVpHuDg4MJAF2+fFmJETJF9fjxY1q6dCnVq1ePAJCZmRn98ssvdP36dbX/m+Oq3VOWoj6/eUQ/3gQ+JSUFRkZGSE5OZlt7lkFPnz7F9u3b4efnh8+fP4PH46Fu3bpo1KgRTExMIBKJIJFIkJSUhKioKDx+/BhEBFNTU7i7u8PDw6PYO2y9fPkSbm5uePnyJQ4fPgwnJyeFvBexWIy9e/di8+bNePDgAWxsbPDLL79g+PDhKFeunELqYOTz4MED1K9fH9euXUPr1q1hZmaGGTNmwMvL64f3urm54dWrV4iKimKrCDgSHx+PQ4cOYf/+/bh9+zbKlSuHPn36YMiQIejUqRPne+8XFxftnjIU9fnNkgGmyHJycvDw4UNEREQgIiIC0dHREIvFyMrKgra2NgwMDGBrawt7e3vY29vD2tq6RA1ASkoKBg8ejAsXLmDjxo2YOHGiwt4LEeHvv//Gpk2bcPLkSZQrVw6jR4/GxIkTUbduXYXVwxRdaGgo2rdvj9jYWNSpUwdaWlrYtGkTfv755+/e9/TpU9StWxd//PEHxowZo6JoGeDf5Z/Hjh3D/v37cfnyZQiFQnTr1g1DhgyBq6srdHV1uQ6xxFTd7ilakZ/fiuxmYBhFy8nJoWnTphEAmjJlisIm9nzt5cuX5OXlRRUqVJB17Z05c4Zte6xigYGBBIA+f/5MYrGYAND+/ft/eN/UqVOpfPnyco/vMsWTnp5OgYGB1Lt3bxKJRMTj8ahjx460c+dOtiuoGmKbDjGlgkAgwPr167Ft2zZs2bIFPXr0QEpKikLrqFGjBry9vfH69WsEBAQgISEBrq6uqFOnDtauXSs7PY9RroSEBAgEAhgZGRX5xEKxWAw/Pz+MHz++VHwKVVc5OTkIDg7G6NGjUalSJfTr1w+vX7/Gr7/+itevX+PSpUsYM2aMXCdMMuqBJQOMRvDw8MC5c+dw7do1tGnTBi9fvlR4HTo6Ohg5ciRu376NmzdvonXr1vDy8kLVqlUxfvx4/PPPPwqvk/l/iYmJKF++PPh8fpFPLNy1axfS09N/OJTAFB8RITw8HFOnTkW1atXQtWtXXLt2DdOnT0dsbCxu376N6dOno2rVqlyHyigASwYYjdG1a1fcuHEDaWlpaN68OW7evKmUeng8Hlq0aIE9e/bg9evXmDdvHs6ePYuGDRvC0dERR44cYdseF0AsFsPKygqTJk3Cmzdvin1/QkICzMzMAKBIyYBUKsXGjRvRt29fVK9eXZ6QmQI8fPgQCxcuRO3atdGyZUscOXIEQ4YMwe3btxEbG4slS5aweTWlEEsGGI1iY2OD8PBw1KlTB+3bt8fBgweVWl/FihWxYMECvHjxAocPHwaPx8OAAQNgYWGB5cuX4/3790qtX5N8+vQJsbGx2Lp1KywtLYudFCQmJsrOJSjKMMGFCxfw5MkTTJkypWSBM3j9+jV8fHzQuHFj2NjYYNOmTejQoQMuXbqE169fY926dWjatClbqVGaKXICAsOoSmZmpmwL46VLl6p07fK9e/do3LhxpKurS1paWjR06FC6ceOG2q+fVrbnz58TANmXQCAgoVBIEydOpNevX//w/q5du1K/fv2IiGjXrl0EgDIzMwu93snJiZo0aVLmf+7ySkxMJF9fX3J0dCQApKOjQ/3796fjx49/9+fOaBY2gZAp1bS1tbF7924sX74cixcvxrBhw5CZmamSuu3s7LBjxw68ffsWv/76K27cuIFWrVqhWbNm2LVrl8riUHe5ubnIycnB9u3bi9RT8N8TC3V1daGtrV3gtY8ePcKFCxcwdepU9mm1GNLS0nDgwAG4ubmhUqVKmDRpEnR1dbFr1y58+PABhw8fRq9evQr9uTOlF0sGGI3F4/GwYMECHDp0CMeOHUOnTp3w8eNHldVvYmKCGTNm4MmTJzhz5gzMzMwwatQoVKtWDV5eXkqZ5KiJipoUJCYmyuYMJCUlfXe+wObNm2Fubo6BAwcqK+xSIzs7G2fPnsXQoUNhbm6OIUOG4NOnT1i/fj3evn2L8+fPY8SIEWwPmTKOJQOMxhswYABCQ0Px7NkztGjRAvfv31dp/Xw+H927d0dQUBAeP36MYcOGYevWrahZsyZ69+6Nv/76C/Tjvb1KvbykwNfXFz/99BM6deqEuLg4+Pn54c8//8T79+/x+vVrXLt2Da9fv4aRkVGB5Xz58gUBAQHw8PBgn2ALIZVKceXKFfz888+oXLkyXF1dERUVhfnz5+PZs2e4fv06fvnlF1SsWJHrUBl1ocgxB4bh0suXL8nW1pYMDQ3p/PnznMYiFotp27ZtVL9+fQJA1tbWtGXLFqWfz86l/84ZKMrXxIkTSUtLq9Dv16hRg9q2bUujR48mf39/evHiBa1bt460tLTo3bt3XL9ltSKVSikqKopmz55N1atXl/385syZQ/fu3WNzK8oodlARUyalpKRQ9+7dic/n0+bNm7kOh6RSKV2+fJn69OlDfD6fDA0NacqUKRQbG8t1aArz8uVLWrFiBbVo0eKHD3+BQEA8Ho/69++f7xCqZ8+eEQA6duwYxcTEUMuWLalBgwY0b948GjZsGDVs2JB4PB4BIKFQSLVq1aLAwECSSCQcvnP18OzZM1qxYgXZ2NgQACpfvjz9/PPPdOXKFbaLJsOSAabsysnJoenTpxMAmjx5slK2MJbHy5cvad68ebJtj52cnOj06dOUk5PDdWhyCQ8Pp4EDB5JAICADAwPq3LlzoUmAUCgkHo9HAwYMKPAkytu3bxMAioyMJCKidu3a0ZAhQ/Jd8+nTJ5o7dy4BoJo1axIAqlKlCi1btozi4+NV8p7Vxfv372njxo3UsmVLAkD6+vo0dOhQOnv2LEuQmHxYMsCUedu2bSOBQEAuLi5q9bubkZFBu3btoqZNmxIAsrS0JB8fH/r06RPXoRXJnTt3qE2bNgSAateuTZs3byaxWFzgMMGPkoA8586dIwCyJYh2dnY0adKkb67r2LEjtWjRgoiI/vnnH5owYQLp6emRlpYWjRgxgt6/f6+cN60GkpOTKSAggLp27Up8Pp+EQiG5ubnRgQMHKDU1levwGDXFkgGGIaKLFy+SkZER1a9fn54/f851ON8IDw+nYcOGkUgkIl1dXRo7dixFRUVxHVaBJBIJLV26lIRCITVs2JBOnDiRr1fj62QgLwno378/xcTE/LDs3bt3EwDKyMggIqIaNWrQ/Pnz810THR1d4OFFnz9/prVr11KFChXI1NSUdu/eXWrGxzMyMujYsWPUr18/0tHRIQDUrl072r59OyUmJnIdHqMBWDLAMP/z4MEDqlmzJpmbm9P169e5DqdA79+/pxUrVlDVqlUJADk4ONChQ4fUpsv3xYsX1KxZMxIIBLRw4ULKysoq8BoAP0wCWrVqRT/99BM1b96c3NzcaMyYMdShQwcSiUQUEBAgm1To4eFBKSkpsvvGjx9PlStXLrBuIqKPHz/SkCFDCAC5uLhQQkKCYt68iuXk5FBISAi5u7uTkZERAaDGjRuTj48PvXr1iuvwGA3DkgGG+UpCQgK1bduWtLW1i3QsLlckEgkdOXKE2rVrRwCocuXKtHTpUk7HxN++fUs1a9YkCwsLCg8PL/Q6qVRKW7Zs+WFPgK2t7TdDCXw+v9D5Bj4+PpSYmEi6urq0fPnyH8Z76tQpMjMzIzs7O41JCKRSKd26dYumTZtGlStXJgBUq1YtWrhwIT148IDr8BgNxpIBhvmPzMxMGj58OAGgJUuWqH1X8n/HxIcMGULXr19XadwJCQlkY2ND1apVoxcvXiikzO3bt8tWBhT1y9zcnAQCQZFjiImJIXNzc7VPCB49ekSLFi2i2rVrEwCqWLEiTZ06lcLDw9X+95PRDCwZYJgCSKVSWrlyJQGgwYMHy8ao1dnnz59p3bp1VKtWLQJATZo0IX9/f0pPT1dqvVKplDp27Ejm5uYKXQqZkpJCurq6xd6TAAAZGRmRl5dXkc46uH//Ppmbm1ObNm3UaondmzdvaO3atWRvb08AyNDQkEaPHk3BwcFqs/KFKT1YMsAw33H48GHS0dGhVq1aacwM9NzcXDp79iy5uLjI1pPPmTNHYZ/Y/+vo0aMEgM6dO6fwsidMmEBCoVCuhEAgEBCfz6d+/fpRdHT0d+sJDQ0lALRjxw6Fv4fi+Pz5M/3xxx/UoUMH4vF4pK2tTX369KHAwECNSEgZzcWSAYb5gfDwcKpYsSL99NNPP3yoqJvHjx/T9OnTycjIiPh8PvXq1YtCQkIU1rWcmZlJlpaW5OLiopDy/uvu3btyJQL//erbt+8P6xo5ciSZmJjQx48flfJeCpOWlkaHDh2inj17kpaWFvH5fOrcuTP5+flRUlKSSmNhyi6WDDBMEbx8+ZLs7OzIwMCAgoKCuA6n2MRiMfn6+lKDBg0I+P9tj7+ehS+PvF4BRSZJ2dnZdO/ePfLz86NJkyaRoaEhaWlpyb6+N4nwv198Pp9atWpVpAf8x48fSU9Pj1atWqWw91IYiURCQUFBNHz4cCpXrhwBoObNm9Pvv//Otk9mOFHU5zeP6McnqKSkpMDIyAjJycnsZCum1BGLxRgyZAjOnTuHDRs24JdffuE6pGIjIoSGhmLz5s04ceIE9PT0MGrUKEyaNAn16tUrdnmTJk3CxYsX8eTJkxLH9vTpU/j6+sLPzw9JSUng8XioV68eGjVqBBMTE4hEIkgkEiQlJeH27duIi4sDEUEgECA3N7fAMocNG4adO3cW+aCiXr164dOnT7hy5UqJ389/ERFu3LiB/fv34/Dhw0hISEC9evUwdOhQDB48GLVr11Z4nQxTVEV+fisys2AYTfX1FsaTJk3S6Ilcr169yrftcZcuXejUqVPF2vbYysqKxo8fX6I4bt68SU5OTgSATE1NydPTk8LCwn7Ya5GSkkJhYWHk6elJhoaGsp4A/K9XYNWqVcUeDtm+fTvx+XyF7vIYHR1NXl5eZGFhQQCoatWq5OnpSZGRkWwlAKM22DABw8jB19eXBAIBOTs705cvX7gOp0QyMjJo9+7d1Lx5cwJAFhYWtHr16iI9ELW1tWnDhg1y1zt79mzi8/lkZ2dHAQEBcq98SE9Pp4CAALKxsSEej0e9evWSa8JdZGQkAfjuPglF8fz5c1q1apVsrwQTExMaP348/f3332q1YoFh8rBkgGHkFBwcrNZbGMsjPDychg8fTiKRiHR0dGjMmDF09+7dQq83MDCgtWvX5ntNKpXShg0bvvszuXPnDllZWZFIJCJvb2+F9bBkZ2eTt7c3iUQisra2pjt37hTr/nv37smdDHz8+JG2bNkiO49BV1eXBg0aRKdOnSp0N0SGURcsGWCYEnj48CHVrFmTzMzM1HYLY3l8+PCBVq5cSdWqVSMA1KZNGzp48OA32x6XL1+evL29870WHBws2xnv8+fP35QdHBxMenp6ZG9vX6TzCOQRExND9vb2pK+vT8HBwYVe9+jRo3zDIlFRUcVKBlJSUmjPnj3k4uJCAoGABAIBdevWjfbu3UtisbjE74NhVIUlAwxTQl9vYbxv3z6uw1Go7OxsCgwMpPbt28u2PV6yZIls2+MWLVp8s2zPzc1N9mB0dHTM96k4ODiYRCIRdevWjdLS0pQae1paGrm4uJBIJCowIdi5cycBoHXr1sle27NnDwH47rbOWVlZdPLkSRo4cKBsU6S2bdvS1q1bVb4skWEUhSUDDKMAmZmZNGLECAJAixcvLpUTw6Kjo/Ntezx48GCaMGEC6evry8b6nz9/nm8LYR6PR6NGjSKpVEp37twhfX19cnFxUVm3eVZWFrm4uJC+vn6+IYM9e/bI4rSzs5O9PmjQILK3t/+mnNzcXLp8+TKNGzeOTExMZPf9+uuvStvMiWFUiSUDDKMgUqmUvL29NWoLY3kkJSXR+vXrZfvkAyAPDw9KT0+n2bNnk0Ag+Ga9/7Jly8jKyors7e2V3iPwX2lpadSkSROytramjIwMOnz48DdnHjx8+JDEYjEZGxvTwoULiejff8+IiAiaOXOm7JRICwsLmjdvnsZtPsUwP8L2GWAYBQsMDMTw4cPRqFEjnDhxAhUrVuQ6JKWQSqU4f/48Ro4cicTERBgbGyM9PR0SiaTA60UiESIjI1G/fn0VRwrExMTA3t4erq6uOHnyZL59CQQCAebPn4+0tDRs3boVZ8+exZUrV7B//37ExsbCzMwMAwYMwJAhQ9CqVSvweDyVx88wylbU5zdLBhimGG7fvo0ePXpAW1sbZ86cQYMGDbgOSWni4uJQv359VKxYES9fvizwGh6Ph5UrV8LLy0vF0f0/b29vLFiwAAU1Zebm5khMTETlypXx9u1blCtXDr1798aQIUPQqVMnaGlpcRAxw6gOSwYYRklev34NNzc3xMXF4dChQ3BxceE6JKX57bffMHfu3AK/x+fzYWVlhXv37kEoFKo4sv+Xk5ODhg0b4uHDhwUmBADg5uaGYcOGwdXVFXp6eiqOkGG4U9TnN1+FMTFMqVC9enVcvXoV7dq1g6urKzZt2sR1SErTpk2bQr8nlUoxe/bsYicCo0aNAo/HK/Tr7du3xSpPKBRi1qxZhSYCgwcPxqlTpzBgwACWCDBMIVjPAMPIKTc3F7Nnz8a6deswadIk/P7775x+QlaGwYMH48iRIwWeEWBkZIT4+Hjo6uoWq8wbN27g2bNn+V4jInh4eMDCwgL3798vdpwZGRmoVKkSUlJSvvlehQoV8P79ewgEgmKXyzCarqjP79LVcjGMCgkEAqxduxb16tXDpEmT8PTpUxw6dAhGRkZch6YQ8fHxhSYCAoEA48aNK3YiAACtWrVCq1at8r129epVpKenY+jQoXLFqquri3HjxuH333//Jt7ExET8/fff6NSpk1xlM0xZwIYJGKaExo8fj/Pnz+PmzZto3bo1nj9/znVICvHy5UvweDzo6OjAzMwMderUgY2NDXR1dZGbm4sePXoorK79+/eDx+NhyJAhcpfRo0ePAhMXoVCIffv2lSQ8hin12DABwyjIo0eP4OrqipSUFJw4cQKtW7fmOqQSy83N/aZ7fceOHfDw8EBKSgrKlStX4jqys7NRuXJlWFlZ4erVq3KXIxaLYWRkBD6f/01SYGBggOTkZLZ8kClz2DABw6iYlZUVbt68iT59+qBjx47w8/Mr0SdddVDQOPs///yDevXqKSQRAIALFy7g06dPcg8R5DEwMEDdunXRuXNnzJ8/Hy9evJB9iUQilggwzHewZIBhFKhChQoIDg7GhAkTMHToUMTGxmLJkiWl6kEUHR2NRo0aKay8/fv3Q0tLCwMGDChxWY0aNUJMTAwqV66MypUrfzM3gWGYgrFkgGEUTFtbG/7+/rCysoKXlxdiY2Ph7+8v12Q7dSQWi2FiYqKQslJTU3Hy5Ek4OTmhfPnyJS7PxMQET548UUBkDFO2sAmEDKMEPB4Pc+fORWBgIE6dOoWOHTviw4cPXIelEBKJBCKRSCFlnThxokSrCP5LJBIhKytLIWUxTFnCkgGGUaK+ffsiNDQUL168QPPmzREdHc11SCUmEokKPaeguPbt24dy5copbGWCRCKBtra2QspimLKEJQMMo2TNmjXDrVu3YGpqijZt2uDcuXNch1QiBgYGSEpKKnE5CQkJCAkJQe/evRW2M2BSUhIMDAwUUhbDlCUsGWAYFahevTquXLmC9u3bw83NDRs3bix0+1x1Z2tri6ioqBKXc+jQIeTk5ChsiAAAoqKiYGtrq7DyGKasYMkAw6hIuXLlcPz4cUyfPh1Tp07FL7/8gpycHK7DKjZ7e3vExsZCLBaXqJx9+/bB3NwcnTt3VkhcYrEYjx8/hr29vULKY5iyhCUDDKNCAoEAa9aswY4dO7Bjxw50794dycnJXIdVLPb29iCiEvcO3LhxAx8+fFDYmQF3794FEbFkgGHkwJIBhuHAuHHjcP78edy6dQutW7dGXFwc1yEVmY2NDUxMTHDq1CmuQ8nn1KlTMDU1hbW1NdehMIzGYckAw3CkU6dOuHHjBrKystCiRQtcu3aN65CKRCgUwt3dHX5+fsjIyOA6HAD/nlro5+cHd3f3UndyJMOoAksGGIZDVlZWCA8Ph42NDTp27KgxB+p4eHjg8+fPOHz4MNehAPh3MmJSUhI8PDy4DoVhNBJLBhiGY+XLl0dwcDCGDBmCYcOGYdGiRZBKpVyH9V21a9eGk5MT1q1bx/kkyJycHKxfvx7Ozs6oVasWp7EwjKZiyQDDqAGRSAQ/Pz+sWrUKy5cvx+DBg9WmC74wy5YtQ0xMDHx8fDiNY/Xq1YiJicHSpUs5jYNhNBlLBhhGTeRtYXz06FGcPn0aHTp0wPv377kOq1DNmzeHp6cnlixZgvv373MSQ0xMDJYsWYJZs2ahefPmnMTAMKUBj4qw80lRz0NmGEYx7ty5gx49ekBLSwunT5+GnZ0d1yEVKDMzE40bN4a+vj7CwsIUtpNgUaSnp8PBwQEZGRmIjIyEjo6OyupmGE1R1Oc36xlgGDXUtGlTjdjCWEdHB3v37sWjR4/Qr18/hZ1Z8CMSiQT9+vVDbGws9uzZwxIBhikhlgwwjJqqVq0arly5go4dO6r1Fsb29vY4ceIELl26hF69eiE9PV2p9aWnp6NXr164dOkSTp48yTYZYhgFYMkAw6ixcuXK4dixY5gxYwamTp2KSZMmITs7m+uwvtG5c2ecPXsWYWFhcHR0VNocgpiYGDg4OCAsLAznzp1Dp06dlFIPw5Q1LBlgGDUnEAjg4+ODP/74A3/88Qe6d++OL1++cB3WN/6vvfuPqar+/wD+PDe54LUbXWozL7JcOAiBiZ5Fa6lg4HKzGKXRNHUBbV11TtBrQuL4YfO3bW6t4RZ3t8g1CZpRYFhucikh5CIBSdnFH5nSyrjaAa9eT9zPH37hW4pyL97LAe7zsbm5nfc979f9Q8/zvs85r3dycjJqa2vR29uL2bNnY/v27V577VCWZWzbtg2iKMLhcKC2tpZBgMiLGAaIxog33ngDNTU1OHHixKhtYSyKIk6ePImsrCzk5eVBFEWYzeZhvybpcDhgNpshiiK2bNmC7OxsNDc389YAkZcxDBCNIc899xwaGhpw8+bNUdvCOCgoCDt37sTx48eh1+uRnp6O0NBQGI1GWCyWIXc7lCQJFosFRqMRoaGhSE9Ph16vR319PXbs2MGHBYl8gK8WEo1Bf/31FxYvXoz6+nqUlJRg+fLlSpd0VzabDfv374fJZEJ3dzcEQUBERATi4uKg0+mgVqvhdDpht9thtVrR2dkJl8uFkJAQZGRkwGAwsLMg0TC5e/1mGCAao5xOJ958802YzWbk5eWhsLAQKtXoXeyTZRkdHR2wWq2wWq1oa2vDH3/8AZvNhunTp+PcuXOIjo7GmjVrIIoioqKiuOkQ0X1iGCDyAy6XC7t27UJOTg7S0tJgNpsxceJEpctyW//9f6vVisTEROTn52PDhg1Kl0U0brDpEJEfEAQBmzZtGmhhnJiYOKpbGN+NLMuQJAk6nU7pUoj8EsMA0Tjw8ssvo66uDhcuXEB8fDxaW1uVLskjPT09AICHH35Y2UKI/BTDANE4IYoiGhsb8eijj+LZZ59FVVWV0iW5rf8NA4YBImUwDBCNI1OnToXFYkFSUhJSUlKwb9++UdnC+Hb9YYC3CYiUwTBANM70tzDesGEDsrKysHr16lHZwvjfuDJApCy+t0M0DqlUKuzatQuRkZEwGAzo7OxEWVnZqL3YMgwQKYsrA0TjWGZmJo4cOYKmpqZR28IYuPX6kyAICA4OVroUIr/EMEA0zs2fP3+ghXF8fDy+/fZbpUu6gyRJeOihh0Z10ySi8Yz/8oj8QEREBBoaGhATE4OkpCSUlpYqXdJ/9PT08OFBIgUxDBD5iUceeQRHjhzBa6+9hpUrVyIvLw99fX1KlwXg1m0CPi9ApBw+QEjkR9RqNUpKSvDkk08iJycHp0+fhtlshkajUbQuSZIYBogUxJUBIj8jCALeeustVFRUoKqqalS0MGYrYiJlMQwQ+amXXnoJdXV1uHjxIuLj4/HDDz8oVgtXBoiUxdsERH5s9uzZaGxsxIsvvog5c+bgk08+wQsvvOCTucrLy/Hdd9/hyy+/REBAADQaDWRZBgDYbDZcv34dr7/+OoKCgjBp0iQsW7YM0dHRCAoK8kk9RPT/uIUxEaG3txfLly9HZWUl9u7di3Xr1kEQBK/OMWXKFI9vR+j1ely8eNGrdRD5E25hTERumzRpEioqKmA0GpGdnY1Vq1Z5vYXxunXrPO4jMGfOHK/WQESD48oAEf1HSUkJDAYDEhMT8emnn3rtXr4kSQgLC8PVq1fdGh8YGIhffvkFYWFhXpmfyB9xZYCIhiUzMxNff/01rFYrnnnmGXR2dnrlvFqtFjk5OW6vDmzevJlBgGiEMAwQ0R0SExPR0NCAf/75B08//TTq6uoGHXfz5k288soryM3Ndeu8a9asgVarvecYQRAwdepUGI1Gj+smouFhGCCiQfW3MI6NjUVSUhI++uij/xx3uVxYu3YtysvLsXfvXvz555/3PJ8syzh79iySk5MB3NpZMSAgYOBP/4qBy+VCdnY2AgICfPPFiOgOfGaAiO7J6XRi1apVMJlM2Lx5M4qKiqBSqbBv3z5kZWUBuHVh37p1K95+++07Pm+z2VBcXAyTyQS73Q5BEPDEE0/gqaeegk6ng1qthtPphN1ux4kTJ3DmzBm4XC7odDpkZGTAYDBg+vTpI/yticYHd6/fDANENCSXy4U9e/Zg06ZNWLx4MZYuXYolS5bg3/99TJ48GRcuXBj4Rf/9998jPz8fNTU1CAkJQUZGBlJSUhAXF3fPWwWSJKGlpQWVlZUwmUzo7u7G888/j6KiIsTHx/v8uxKNJwwDROR1hw4dwtKlS+F0OuFyuXD7fx8HDx5ESkoK8vPzsWfPHsTExGD9+vVIS0vDxIkTPZ7P4XCgrKwM7777Ltrb22E0GlFYWMhGRERuYhggIq/7/fffERsbi8uXL99xTKVSYcaMGZBlGWfOnEFBQQE2btyICRPuv9GpLMvYvXs3CgoKEB4ejtLSUoiieN/nJRrv+GohEXmVw+HAokWLcOXKlUGP9/X14dSpU9BoNGhubkZubq5XggAATJgwAbm5uWhuboZGo0FCQgK++eYbr5ybiBgGiMgNfX19WLlyJVpaWgb2E7idSqXCggULUFdXh+joaJ/UER0dDYvFgnnz5mHRokUMBERewjBAREPaunUrysvL0dfXN+jx/iBQWVkJjUbj01o0Gg0OHTqEpKQkpKamwmq1+nQ+In/AMEBEQ2ptbR34++1L/w888ABiY2Px2WefQa1Wj0g9arUa5eXliIyMxIoVK3D9+vURmZdovGIYIKIhVVRU4Ndff8WBAweQmZmJ8PDwgWOCIODAgQM+XxG4nUajwYcffojOzk4UFBSM6NxE4w3DABG5JSwsDMuWLUNxcTFsNhuqq6uhUqlQVFTks2cEhhITE4P8/Hzs3r0bjY2NitRANB7w1UIiGpaFCxeiq6sLVqvVa28NDIcsyxBFEXq9HocPH1asDqLRiK8WEpHP2Gw21NTUYP369YoGAeDWMwzZ2dn46quvvLbDIpG/YRggIo8VFxcjJCQEaWlp9xzX09OD/Px8LFy4ECEhIRAEAWaz+Y5xjY2NWL16NURRREBAAARB8KieV199FTqdDsXFxR59johuYRggIo/IsgyTyYSMjIwhWwxfvnwZRUVF6OjowMyZM+86rrq6Gh988MHAJkaemjhxIjIyMmAyme7aB4GI7o5hgIg8curUKdjtdqSkpAw5dsqUKejq6sL58+exe/fuu45btWoVrl69iqamJixYsGBYdaWkpKC7uxsdHR3D+jyRP2MYICKPWK1WCIKAWbNmDTk2MDAQjz322JDjJk+ePKyNjP5t1qxZEASBTYiIhoFhgIg8YrVaERkZiQcffFDpUv5Dq9UiIiKCYYBoGBgGiMgjbW1tiIuLU7qMQcXFxaGtrU3pMojGHIYBIvKIJEnQ6XRKlzEonU4HSZKULoNozGEYICKPOJ3OEduDwFNqtRo3btxQugyiMYdhgIg8olar4XQ6lS5jUE6nE4GBgUqXQTTmMAwQkUe0Wi3sdrvSZQzKbrdDq9UqXQbRmMMwQEQeiY2NRUtLi9JlDKqlpQWxsbFKl0E05ijbVJyIxhxRFPH+++9DkiS3foW/9957uHLlCi5dugQA+OKLL/Dbb78BANauXYvg4GCcP38epaWlAICmpiYAwDvvvAMAePzxx7FixYoh55EkCadPn0ZOTs6wvheRP+OuhUTkkdbWVsycORMWiwVz584dcvy0adNw/vz5QY+dPXsW06ZNw7FjxzB//vxBxyQkJODYsWNDzmOxWJCQkIDW1lauDhD9H3ev31wZICKPzJgxAzqdDpWVlW6FgXPnzg05JjExEW78LrmnyspKhISEICoq6r7OQ+SP+MwAEXlkwoQJA5sCORwOpcsBADgcjoHNk5TeUploLGIYICKPGQwGdHd3o6ysTOlSAAAHDx6E3W6HwWBQuhSiMYnPDBDRsCxcuBBdXV2wWq2K/hqXZRmiKEKv1+Pw4cOK1UE0Grl7/ebKABENS1FREdrb2++5NfFI2LVrF9rb21FYWKhoHURjGcMAEQ1LfHw8jEYjCgoK8OOPPypSQ3t7OwoKCrBx40bEx8crUgPReMDbBEQ0bNevX8esWbMwadIkWCwWaDSaEZv72rVrmDt3LhwOB5qbmxEUFDRicxONFbxNQEQ+FxQUhI8//hg//fQTlixZMmJ7FjidTixZsgQ///wzSktLGQSI7hPDABHdF1EUcejQIRw9ehSpqam4du2aT+e7du0aUlNTcfToUXz++ecQRdGn8xH5A4YBIrpvycnJqKqqgsViwbx583z2DEF7ezvmzp0Li8WC6upqJCUl+WQeIn/DMEBEXpGcnIza2lr09vZi9uzZ2L59O2RZ9sq5ZVnGtm3bIIoiHA4HamtrGQSIvIhhgIi8RhRFnDx5EllZWcjLy4MoijCbzcPuVOhwOGA2myGKIrZs2YLs7Gw0Nzfz1gCRlzEMEJFXBQUFYefOnTh+/Dj0ej3S09MRGhoKo9EIi8UCSZLu+XlJkmCxWGA0GhEaGor09HTo9XrU19djx44dfFiQyAf4aiER+ZTNZsP+/fthMpnQ3d0NQRAQERGBuLg46HQ6qNVqOJ1O2O12tLS04PTp03C5XAgJCUFGRgYMBgPCw8OV/hpEY5K712+GASIaEbIso6OjA1arFVarFW1tbZAkCTdu3EBgYCC0Wi1iY2MhiiJEUURUVBQ3HSK6TwwDREREfo5Nh4iIiMgtDANERER+jmGAiIjIzzEMEBER+TmGASIiIj/HMEBEROTnGAaIiIj8HMMAERGRn2MYICIi8nNu9frsb1L4999/+7QYIiIi8p7+6/ZQzYbdCgP9u4yFhYXdZ1lEREQ00iRJQnBw8F2Pu7U3QV9fHy5dugStVgtBELxaIBEREfmGy+WCJEnQ6/VQqe7+ZIBbYYCIiIjGLz5ASERE5OcYBoiIiPwcwwAREZGfYxggIiLycwwDREREfo5hgIiIyM8xDBAREfm5/wFR/cxyQRnhAwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "create_pdg(cfg).plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "721f7797",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "source": [
    "## Slicing"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae8b5985",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Slicing uses the program dependence graph to extract an executable subset of a program that only contains statements relevant for the execution of a target statement, i.e., the slice criterion. We thus need the PDG for our example program to start with, and we need to add a helper function that gives us the transitive predecessors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "dc9a3270",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "class ProgramGraph(ProgramGraph):\n",
    "    def transitive_predecessors(self, node):\n",
    "        return nx.nodes(nx.dfs_tree(self.graph.reverse(), node))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ad359ceb",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "A backwards slice gives us information about what set of statements could have affected a statement (or if we want to, even at the level of a specific variable at this statement). A backward slice is simply created by a backwards traversal of the PDG, starting from the slicing criterion."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "c3a48511",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [],
   "source": [
    "def backward_slice(code, line):\n",
    "    tree = parse_method(code)\n",
    "    cfg = CFGBuilder(tree).create_graph()\n",
    "    definitions = []\n",
    "    for node in cfg.nodes():\n",
    "        definitions.extend(node.definitions())\n",
    "        \n",
    "    pdg = create_pdg(cfg)\n",
    "    target = pdg.node_for_line(line)\n",
    "    statements = set([str(n) for n in pdg.transitive_predecessors(target)])\n",
    "\n",
    "    lines = code.split('\\n')\n",
    "    result = lines[1] + \"\\n\"\n",
    "    for line_no, line in enumerate(lines):\n",
    "        if str(line_no + 1) in statements:\n",
    "            result += line + \"\\n\"\n",
    "            \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "2875c3eb",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "code = \"\"\"\n",
    "public boolean testMe(int x, int y) {\n",
    "    if (x <= y) {\n",
    "        if (x == y) {\n",
    "            System.out.println(\"Some output\");\n",
    "        }\n",
    "        if (x > 0) {\n",
    "            if (y == 17) {\n",
    "               return true;\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    return false;\n",
    "}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "id": "3ebc4a68",
   "metadata": {
    "scrolled": true,
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "public boolean testMe(int x, int y) {\n",
      "    if (x <= y) {\n",
      "        if (x > 0) {\n",
      "            if (y == 17) {\n",
      "               return true;\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(backward_slice(code, 9))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "18bcb91c",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "Note that our slice isn't actually compilable, because we did not deal with closing braces. However, in principle we can also get these from the AST."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4a39ded0",
   "metadata": {
    "slideshow": {
     "slide_type": "skip"
    }
   },
   "source": [
    "A forward slice tells us which statements can be affected by a given statement, or variable in that statment. It is determined using a forward traversal of the PDG."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "a9466fef",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "def forward_slice(code, line):\n",
    "    tree = parse_method(code)\n",
    "    cfg = CFGBuilder(tree).create_graph()\n",
    "    definitions = []\n",
    "    for node in cfg.nodes():\n",
    "        definitions.extend(node.definitions())\n",
    "        \n",
    "    pdg = create_pdg(cfg)\n",
    "    target = pdg.node_for_line(line) \n",
    "    statements = set([str(n) for n in pdg.transitive_successors(target)])\n",
    "\n",
    "    lines = code.split('\\n')\n",
    "    result = lines[1] + \"\\n\"\n",
    "    for line_no, line in enumerate(lines):\n",
    "        if str(line_no + 1) in statements:\n",
    "            result += line + \"\\n\"\n",
    "            \n",
    "    return result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "9baf6d89",
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [],
   "source": [
    "code = \"\"\"\n",
    "public boolean testMe(int x, int y) {\n",
    "    if (x <= y) {\n",
    "        if (x == y) {\n",
    "            System.out.println(\"Some output\");\n",
    "        }\n",
    "        if (x > 0) {\n",
    "            if (y == 17) {\n",
    "               return true;\n",
    "            }\n",
    "        }\n",
    "    }\n",
    "    return false;\n",
    "}\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "3bca3390",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "public boolean testMe(int x, int y) {\n",
      "            if (y == 17) {\n",
      "               return true;\n",
      "    return false;\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(forward_slice(code, 8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "id": "b128efd7",
   "metadata": {
    "slideshow": {
     "slide_type": "fragment"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "public boolean testMe(int x, int y) {\n",
      "        if (x == y) {\n",
      "            System.out.println(\"Some output\");\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(forward_slice(code, 4))"
   ]
  }
 ],
 "metadata": {
  "celltoolbar": "Slideshow",
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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