Initial commit for publication

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.gitignore

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+# IntelliJ
+.idea/
+*.iml
+
+# Custom scripts
+scripts/ignored
+
+# Maven compile output directory
+target/
+
+# Custom directories holding data for/from analysis
+results/
+data/

LICENSE.txt

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README.md

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+# toCairn
+
+Proof of Concept for the thesis 'Identifying microservice boundaries in a monolithic application based on data
+autonomy'. toCairn can cluster the classes based on multiple metrics. The metrics used determine the input required.
+Multiple clustering algorithms can be used to identify the microservice boundaries. These algorithms include an
+agglomerative hierarchical clustering algorithm as well as multiple multi-objective evolutionary clustering algorithms
+(MOEA). As this is a Proof of Concept, please consider it for evaluation but not for production purposes.
+
+This thesis project was conducted at the University of Amsterdam by Pieter Dirk Soels.
+
+## Features
+
+- Creates a dependency graph of your application.
+- Identifies frequency of class interaction based on static source code analysis.
+- Identifies frequency of class interaction based on a custom JaCoCo coverage report.
+- Identifies size of a class based on JFR memory allocation analysis.
+- Identify microservices based on multiple established metrics formed from microservice characteristics.
+- Perform clustering using an agglomerative hierarchical clustering algorithm with provided weights for the metrics.
+- Perform clustering using MOEA to generate a non-dominated solution space optimizing these multiple objectives.
+
+## Running the project locally
+
+Currently, the project is only built to be running locally. The project requires input files to be present on an
+available filesystem path.
+
+To run the project locally, you must have an instance of Neo4j running, the graph database that this project uses. For
+convenience, a `docker-compose.yml` definition is provided in the project root to run an instance already configured to
+run with this project. When you have `docker-compose` installed on your machine, you can boot up the Neo4j instance
+using `docker-compose up -d`. If you run your own instance, please configure the server application to use your own
+configured Neo4j instance through application properties (see `application.yml`).
+
+To run the server, start the Spring server defined in `ThesisApplication.java`. This will start the server upon which it
+will be accessible at `localhost:8080`.
+
+## Prerequisites
+
+For this application to work, you need to compile this project. For this, one needs to have Java JDK 11 and Maven 3.8+
+installed. Furthermore, one needs to have a Neo4J database. One can set one up themselves manually or use our convenient
+`docker-compose.yaml` script to set one up with defaults matching the application. Storage is persisted in a Docker
+volume in this set up. For the latter, one needs to have both `docker` and `docker-compose` installed on their system.
+
+Lastly, a convenience would be the use of Postman to communicate with our API. In the root of this repository, there is
+a collection file (`toCairn.postman_collection.json`) that you can import to start using the application straight away.
+
+## Usage
+
+This PoC does not come with a frontend. Instead, we use manual API requests to store and retrieve data as well as to
+perform actions. On top of that, we use the visualisations from Neo4J to inspect our created graph and its configuration
+manually.
+
+Make sure you have a Neo4J database running either through the aforementioned manual set up or through running
+`docker-compose up -d` in the root of this repository. Then, run `ToCairnApplication` to start the application.
+
+You can then interact with the application on `http://localhost:8080` and interact with the database on
+`localhost:7474`.
+
+## FAQ
+
+These are common questions and problems encountered and how to solve them.
+
+### Neo4j missing annotations
+
+When receiving an error message containing `Missing @TargetNode declaration in class`
+or `missing a property for the generated, internal ID (@Id @GeneratedValue Long id)`, it could be that the project did
+not compile correctly. Try to run it again or run `mvn clean compile` to recompile the project, and the problem should
+be gone. This happens when initializing the Spring context both during running the application and during tests.
+
+### Persistence queries seem to take very long
+
+Due to how Spring Data Neo4J (SDN) is implemented it could be that, when persisting certain resources, a lot of queries
+need to be executed. SDN tries to make sure that the graph database exactly matches the Java model. As most of our
+resources are linked, this means that it will try to verify the whole graph every time you persist a resource. We tried
+to mitigate this as much as possible with custom queries for persisting relationships as well as using projections for
+storing and retrieving data.
+
+However, it could be the case on a different model that it keeps getting stuck when persisting entities. To debug such
+case for yourself, run the application with the `-Dlogging.level.org.springframework.data.neo4j=DEBUG` environment
+variable set. This will log all the queries made to Neo4J in the console.
+
+### Missing expected relationships
+
+As the relationships between classes is determined using static code analysis, there are various reasons why certain
+expected relationships are not present in the constructed graph. Most understandably at first, relationships based on
+reflection that are only present during runtime are not possible (at least to a certain point) using static analysis.
+The same goes for polymorphism. We can hardly deduce from static analysis whether a class is a certain subtype and
+therefore we do not see such relationships.
+
+Lastly, from static code analysis, we often only know the name of a class. However, to accurately match that class, we
+need its fully qualified name. For that, we use JavaParser's symbol solver. From traffic on discussion fora, it seems
+that this is still the most used AST parser and way to deduce this in meta-programming. However, this symbol solver is
+(at the time of writing) unmaintained. Therefore, some AST could not be resolved due to, for example, new Java
+constructs that the solver does not yet support (such as Java 10's `var`). Lastly, not providing dependency `.jar` files
+greatly lowers the ability to solve class FQNs as often a type must be deduced from library usage (e.g. deserialization)
+. To see such problems, you can enable debug logging through the environment property `logging=debug` which will print
+them to the console.
+
+## License
+
+This project is licensed under the [Apache 2.0 license](LICENSE.txt).

docker-compose.yml

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+version: "3.6"
+
+# Development environment set up for this application
+services:
+  # Neo4j graph database for storing input and result data
+  neo4j:
+    image: neo4j:4.3.0
+    ports:
+      - 7687:7687
+      - 7474:7474
+    volumes:
+      - neo4j:/conf
+      - neo4j:/data
+      - neo4j:/import
+      - neo4j:/logs
+      - neo4j:/plugins
+    environment:
+      # Start with a default database
+      - NEO4J_dbms_default__database=tocairn
+      # Raise memory limits
+      - NEO4J_dbms_memory_pagecache_size=1G
+      - NEO4J_dbms_memory_heap_initial__size=1G
+      - NEO4J_dbms_memory_heap_max__size=1G
+      # DO NOT copy paste these auth variables for a production environment
+      - NEO4J_AUTH=neo4j/password
+      # Allow for DB upgrades
+      - NEO4J_dbms_allow__upgrade=true
+
+# Store data of databases between restarts in Docker volume
+volumes:
+  neo4j: