Lang updates

README.md

@@ -18,7 +18,7 @@ To install this library, download the latest version of [NuGet Package](https://
 
 There are several ways to populate workflows for the Rules Engine as listed below.
 
-You need to store the rules based on the [schema definition](https://github.com/microsoft/RulesEngine/blob/main/schema/workflowRules-schema.json) given and they can be stored in any store as deemed appropriate like Azure Blob Storage, Cosmos DB, Azure App Configuration, [Entity Framework](https://github.com/microsoft/RulesEngine#entity-framework), SQL Servers, file systems etc. For RuleExpressionType `LamdaExpression`, the rule is written as a [lambda expressions](https://docs.microsoft.com/en-us/dotnet/csharp/programming-guide/statements-expressions-operators/lambda-expressions).
+You need to store the rules based on the [schema definition](https://github.com/microsoft/RulesEngine/blob/main/schema/workflow-schema.json) given and they can be stored in any store as deemed appropriate like Azure Blob Storage, Cosmos DB, Azure App Configuration, [Entity Framework](https://github.com/microsoft/RulesEngine#entity-framework), SQL Servers, file systems etc. For RuleExpressionType `LamdaExpression`, the rule is written as a [lambda expressions](https://docs.microsoft.com/en-us/dotnet/csharp/programming-guide/statements-expressions-operators/lambda-expressions).
 
 An example rule:
 
@@ -33,15 +33,15 @@ An example rule:
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country == \"india\" AND input1.loyalityFactor <= 2 AND input1.totalPurchasesToDate >= 5000"
+        "Expression": "input1.country == \"india\" AND input1.loyaltyFactor <= 2 AND input1.totalPurchasesToDate >= 5000"
       },
       {
         "RuleName": "GiveDiscount20",
         "SuccessEvent": "20",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country == \"india\" AND input1.loyalityFactor >= 3 AND input1.totalPurchasesToDate >= 10000"
+        "Expression": "input1.country == \"india\" AND input1.loyaltyFactor >= 3 AND input1.totalPurchasesToDate >= 10000"
       }
     ]
   }
@@ -106,7 +106,7 @@ var bre = new RulesEngine.RulesEngine(wfr, null);
 
 ![](https://github.com/microsoft/RulesEngine/blob/main/assets/BlockDiagram.png)
 
-The rules can be stored in any store and be fed to the system in a structure which adheres to the [schema](https://github.com/microsoft/RulesEngine/blob/main/schema/workflowRules-schema.json) of WorkFlow model.
+The rules can be stored in any store and be fed to the system in a structure which adheres to the [schema](https://github.com/microsoft/RulesEngine/blob/main/schema/workflow-schema.json) of WorkFlow model.
 
 A wrapper needs to be created over the Rules Engine package, which will get the rules and input message(s) from any store that your system dictates and put it into the Engine. The wrapper then handles the output using appropriate means.
 

RulesEngine.sln

@@ -18,7 +18,7 @@ Project("{2150E333-8FDC-42A3-9474-1A3956D46DE8}") = "Solution Items", "Solution
 		CHANGELOG.md = CHANGELOG.md
 		global.json = global.json
 		README.md = README.md
-		schema\workflowRules-schema.json = schema\workflowRules-schema.json
+		schema\workflow-schema.json = schema\workflow-schema.json
 	EndProjectSection
 EndProject
 Project("{9A19103F-16F7-4668-BE54-9A1E7A4F7556}") = "RulesEngineBenchmark", "benchmark\RulesEngineBenchmark\RulesEngineBenchmark.csproj", "{C058809F-C720-4EFC-925D-A486627B238B}"

benchmark/RulesEngineBenchmark/Workflows/Discount.json

@@ -8,31 +8,31 @@
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country == \"india\" AND input1.loyalityFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
+        "Expression": "input1.country == \"india\" AND input1.loyaltyFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
       },
       {
         "RuleName": "GiveDiscount20",
         "SuccessEvent": "20",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country == \"india\" AND input1.loyalityFactor == 3 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
+        "Expression": "input1.country == \"india\" AND input1.loyaltyFactor == 3 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
       },
       {
         "RuleName": "GiveDiscount25",
         "SuccessEvent": "25",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country != \"india\" AND input1.loyalityFactor >= 2 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 5"
+        "Expression": "input1.country != \"india\" AND input1.loyaltyFactor >= 2 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 5"
       },
       {
         "RuleName": "GiveDiscount30",
         "SuccessEvent": "30",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.loyalityFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000 AND input2.totalOrders > 5 AND input3.noOfVisitsPerMonth > 15"
+        "Expression": "input1.loyaltyFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000 AND input2.totalOrders > 5 AND input3.noOfVisitsPerMonth > 15"
       },
       {
         "RuleName": "GiveDiscount30NestedOrExample",
@@ -46,7 +46,7 @@
             "ErrorMessage": "One or more adjust rules failed.",
             "ErrorType": "Error",
             "RuleExpressionType": "LambdaExpression",
-            "Expression": "input1.loyalityFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000"
+            "Expression": "input1.loyaltyFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000"
           },
           {
             "RuleName": "OrHasHighNumberOfTotalOrders",
@@ -69,7 +69,7 @@
             "ErrorMessage": "One or more adjust rules failed.",
             "ErrorType": "Error",
             "RuleExpressionType": "LambdaExpression",
-            "Expression": "input1.loyalityFactor > 3"
+            "Expression": "input1.loyaltyFactor > 3"
           },
           {
             "RuleName": "AndHasTotalPurchased100000",

demo/DemoApp/EFDemo.cs

@@ -20,7 +20,7 @@ public class EFDemo
         public void Run()
         {
             Console.WriteLine($"Running {nameof(EFDemo)}....");
-            var basicInfo = "{\"name\": \"hello\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyalityFactor\": 3,\"totalPurchasesToDate\": 10000}";
+            var basicInfo = "{\"name\": \"hello\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyaltyFactor\": 3,\"totalPurchasesToDate\": 10000}";
             var orderInfo = "{\"totalOrders\": 5,\"recurringItems\": 2}";
             var telemetryInfo = "{\"noOfVisitsPerMonth\": 10,\"percentageOfBuyingToVisit\": 15}";
 

demo/DemoApp/JSONDemo.cs

@@ -17,7 +17,7 @@ public class JSONDemo
         public void Run()
         {
             Console.WriteLine($"Running {nameof(JSONDemo)}....");
-            var basicInfo = "{\"name\": \"hello\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyalityFactor\": 3,\"totalPurchasesToDate\": 10000}";
+            var basicInfo = "{\"name\": \"hello\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyaltyFactor\": 3,\"totalPurchasesToDate\": 10000}";
             var orderInfo = "{\"totalOrders\": 5,\"recurringItems\": 2}";
             var telemetryInfo = "{\"noOfVisitsPerMonth\": 10,\"percentageOfBuyingToVisit\": 15}";
 

demo/DemoApp/Workflows/Discount.json

@@ -8,31 +8,31 @@
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country == \"india\" AND input1.loyalityFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
+        "Expression": "input1.country == \"india\" AND input1.loyaltyFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
       },
       {
         "RuleName": "GiveDiscount20",
         "SuccessEvent": "20",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country == \"india\" AND input1.loyalityFactor == 3 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
+        "Expression": "input1.country == \"india\" AND input1.loyaltyFactor == 3 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
       },
       {
         "RuleName": "GiveDiscount25",
         "SuccessEvent": "25",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.country != \"india\" AND input1.loyalityFactor >= 2 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 5"
+        "Expression": "input1.country != \"india\" AND input1.loyaltyFactor >= 2 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 5"
       },
       {
         "RuleName": "GiveDiscount30",
         "SuccessEvent": "30",
         "ErrorMessage": "One or more adjust rules failed.",
         "ErrorType": "Error",
         "RuleExpressionType": "LambdaExpression",
-        "Expression": "input1.loyalityFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000 AND input2.totalOrders > 5 AND input3.noOfVisitsPerMonth > 15"
+        "Expression": "input1.loyaltyFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000 AND input2.totalOrders > 5 AND input3.noOfVisitsPerMonth > 15"
       },
       {
         "RuleName": "GiveDiscount30NestedOrExample",
@@ -46,7 +46,7 @@
             "ErrorMessage": "One or more adjust rules failed.",
             "ErrorType": "Error",
             "RuleExpressionType": "LambdaExpression",
-            "Expression": "input1.loyalityFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000"
+            "Expression": "input1.loyaltyFactor > 3 AND input1.totalPurchasesToDate >= 50000 AND input1.totalPurchasesToDate <= 100000"
           },
           {
             "RuleName": "OrHasHighNumberOfTotalOrders",
@@ -69,7 +69,7 @@
             "ErrorMessage": "One or more adjust rules failed.",
             "ErrorType": "Error",
             "RuleExpressionType": "LambdaExpression",
-            "Expression": "input1.loyalityFactor > 3"
+            "Expression": "input1.loyaltyFactor > 3"
           },
           {
             "RuleName": "AndHasTotalPurchased100000",

src/RulesEngine/RulesEngine.csproj

@@ -6,7 +6,7 @@
     <Copyright>Copyright (c) Microsoft Corporation.</Copyright>
     <PackageLicenseFile>LICENSE</PackageLicenseFile>
     <PackageProjectUrl>https://github.com/microsoft/RulesEngine</PackageProjectUrl>
-    <Authors>Abbas Cyclewala, Dishant Munjal, Yogesh Prajapati</Authors>
+    <Authors>Abbas Cyclewala, Dishant Munjal, Yogesh Prajapati, Alex Reich</Authors>
     <Description>Rules Engine is a package for abstracting business logic/rules/policies out of the system. This works in a very simple way by giving you an ability to put your rules in a store outside the core logic of the system thus ensuring that any change in rules doesn't affect the core system.</Description>
 	<PackageReleaseNotes>https://github.com/microsoft/RulesEngine/blob/main/CHANGELOG.md</PackageReleaseNotes>
 	<PackageTags>BRE, Rules Engine, Abstraction</PackageTags>

test/RulesEngine.UnitTest/BusinessRuleEngineTest.cs

@@ -775,7 +775,7 @@ private Workflow ParseAsWorkflow(string WorkflowsFileName)
         private dynamic GetInput1()
         {
             var converter = new ExpandoObjectConverter();
-            var basicInfo = "{\"name\": \"Dishant\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyalityFactor\": 3,\"totalPurchasesToDate\": 10000}";
+            var basicInfo = "{\"name\": \"Dishant\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyaltyFactor\": 3,\"totalPurchasesToDate\": 10000}";
             return JsonConvert.DeserializeObject<ExpandoObject>(basicInfo, converter);
         }
 
@@ -801,10 +801,10 @@ private dynamic GetInput3()
         /// </returns>
         private static dynamic[] GetInputs4()
         {
-            var basicInfo = "{\"name\": \"Dishant\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyalityFactor\": 3,\"totalPurchasesToDate\": 70000}";
+            var basicInfo = "{\"name\": \"Dishant\",\"email\": \"[email protected]\",\"creditHistory\": \"good\",\"country\": \"canada\",\"loyaltyFactor\": 3,\"totalPurchasesToDate\": 70000}";
             var orderInfo = "{\"totalOrders\": 50,\"recurringItems\": 2}";
             var telemetryInfo = "{\"noOfVisitsPerMonth\": 10,\"percentageOfBuyingToVisit\": 15}";
-            var laborCategoriesInput = "[{\"country\": \"india\", \"loyalityFactor\": 2, \"totalPurchasesToDate\": 20000}]";
+            var laborCategoriesInput = "[{\"country\": \"india\", \"loyaltyFactor\": 2, \"totalPurchasesToDate\": 20000}]";
             var currentLaborCategoryInput = "{\"CurrentLaborCategoryProp\":\"TestVal2\"}";
 
             dynamic input1 = JsonConvert.DeserializeObject<List<RuleTestClass>>(laborCategoriesInput);

test/RulesEngine.UnitTest/RuleTestClass.cs

@@ -12,8 +12,8 @@ public class RuleTestClass
         [JsonProperty("country")]
         public string Country { get; set; }
 
-        [JsonProperty("loyalityFactor")]
-        public int LoyalityFactor { get; set; }
+        [JsonProperty("loyaltyFactor")]
+        public int loyaltyFactor { get; set; }
         public int TotalPurchasesToDate { get; set; }
     }
 }

test/RulesEngine.UnitTest/TestData/rules1.json

@@ -7,7 +7,7 @@
       "ErrorMessage": "One or more adjust rules failed.",
       "ErrorType": "Error",
       "RuleExpressionType": "LambdaExpression",
-      "Expression": "input1.country == \"canada\" AND input1.loyalityFactor <= 4"
+      "Expression": "input1.country == \"canada\" AND input1.loyaltyFactor <= 4"
     }
   ]
 }

test/RulesEngine.UnitTest/TestData/rules2.json

@@ -13,23 +13,23 @@
           "ErrorMessage": "One or more adjust rules failed.",
           "ErrorType": "Error",
           "RuleExpressionType": "LambdaExpression",
-          "Expression": "input1.country == \"india\" AND input1.loyalityFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
+          "Expression": "input1.country == \"india\" AND input1.loyaltyFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
         },
         {
           "RuleName": "GiveDiscount20",
           "SuccessEvent": "20",
           "ErrorMessage": "One or more adjust rules failed.",
           "ErrorType": "Error",
           "RuleExpressionType": "LambdaExpression",
-          "Expression": "input1.country == \"india\" AND input1.loyalityFactor == 3 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
+          "Expression": "input1.country == \"india\" AND input1.loyaltyFactor == 3 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 2"
         },
         {
           "RuleName": "GiveDiscount25",
           "SuccessEvent": "25",
           "ErrorMessage": "One or more adjust rules failed.",
           "ErrorType": "Error",
           "RuleExpressionType": "LambdaExpression",
-          "Expression": "input1.country != \"india\" AND input1.loyalityFactor >= 2 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 5"
+          "Expression": "input1.country != \"india\" AND input1.loyaltyFactor >= 2 AND input1.totalPurchasesToDate >= 10000 AND input2.totalOrders > 2 AND input3.noOfVisitsPerMonth > 5"
         }
       ]
     }

test/RulesEngine.UnitTest/TestData/rules3.json

@@ -7,7 +7,7 @@
       "ErrorMessage": "One or more adjust rules failed.",
       "ErrorType": "Error",
       "RuleExpressionType": "LambdaExpression",
-      "Expression": "input1.couy == \"india\" AND input1.loyalityFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input2.noOfVisitsPerMonth > 2"
+      "Expression": "input1.couy == \"india\" AND input1.loyaltyFactor <= 2 AND input1.totalPurchasesToDate >= 5000 AND input2.totalOrders > 2 AND input2.noOfVisitsPerMonth > 2"
     }
   ]
 }