Generating software components from business rules expressed in a natural language

• US 8,050,907 B2
• Filed: 07/30/2004
• Issued: 11/01/2011
• Est. Priority Date: 07/30/2004
• Status: Expired due to Fees

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Baisley, Donald Edward, Dirckze, Ravi Anthony Joseph
• Primary Examiner(s): Dorvil; Richemond
• Assistant Examiner(s): Adesanya; Olujimi A
• Application Number:
  US10/903,452
• Publication Number:
  US 20060025987A1
• Time in Patent Office: 2,650 Days
• Field of Search: 704/4, 704/7, 704/9, 704/10
• US Class Current: 704/9
• CPC Class Codes: G06F 40/211 Syntactic parsing, e.g. based on context-free grammar [CFG] or unification grammars

Abstract

An embodiment of the present invention is a method for generating software components from one or more business rule statements expressed in a language. Symbols of a vocabulary of a language and business rule statements expressed using the symbols of the vocabulary of the language are received as input. The language has grammatical rules. Each of the business rule statements is parsed in accordance with the grammatical rules to generate a language-based structure. The language-based structure is processed to generate an expression model. The expression model is processed to generate a logical model. The logical model is processed to generate platform-independent implementation model in response to a user request for such generation. A target platform description is received. The platform-independent implementation model is processed to generate a platform-specific implementation model using the target platform description. Software components are generated from the platform-specific implementation model for deployment.

Claims

1. A method for generating software components from one or more rule statements expressed in a language, the method comprising:

at a computing system that includes a processor, memory, and mass storage device, receiving symbols of a vocabulary of a natural language, the natural language having grammatical rules, and details about each of the symbols;

receiving, at the computing system, at least one rule statement expressed using the symbols of the vocabulary of the natural language;

at the computing system, parsing the rule statement in accordance with the natural language grammatical rules to generate a language-based structure of the rule statement that identifies the symbols used and their interrelationships with respect to a sentence structure, wherein the parsing reports how each word in the rule statement is categorized into;

a) terms defined in the vocabulary,

b) names defined in the vocabulary for individual things,

c) connecting symbols of function forms defined in the vocabulary,

d) key words and phrases, quantifiers, and logical connectives, and

e) words that are not recognized;

at the computing system, processing the language-based structure of the rule statement corresponding to an expression to generate an expression model;

at the computing system, processing the expression model to generate a logical model wherein processing the expression model comprises;

a) relating synonymous terms to a single concept;

b) relating synonymous forms and related noun forms to a single fact type;

c) relating synonymous names to a single instance;

d) relating each instance to its corresponding concept;

e) determining identifying fact types for concepts;

determining generalizations between concepts; and

g) reporting logical inconsistencies, if any;

at the computing system, processing the logical model to generate a platform-independent implementation model in response to a request for such generation;

at the computing system, receiving a specific target platform description; and

at the computing system, processing the platform-independent implementation model using the specific target platform description to generate a platform-specific implementation model.

2. The method of claim 1 further comprising:

processing the platform-specific model to generate software components for deployment.

3. The method of claim 1 further comprising:

providing feedback to a user regarding the rule statement to resolve logical inconsistency.

4. The method of claim 1 wherein parsing the rule statement comprises:

breaking the rule statement into tokens;

identifying, among the tokens, first tokens that correspond to terms, and, if the rule statement includes names, second tokens that correspond to the names;

identifying, among the tokens, third tokens that correspond to connecting symbols;

identifying, among the tokens, fourth tokens that correspond to key words and phrases; and

constructing a parse tree representing the language-based structure of the rule statement.

5. The method of claim 1 wherein processing the language-based structure of the rule statement corresponding to an expression to generate an expression model comprises:

creating a model element for the expression;

determining whether the expression has a logical connective;

if the expression has no logical connective,

marking the expression as a simple expression;

identifying function form that corresponds to the expression; and

processing the model element representing the expression;

if the expression has a logical connective,

creating a model element for the logical connective.

6. The method of claim 5 further comprising:

if the expression has a logical connective,

repeating recursively the operations in claim 5 for each of the propositions included in the expression that are connected by the logical connective, substituting each of the propositions as the expression in the operations.

7. The method of claim 5 wherein processing the model element representing the expression comprises:

for a role in the expression, creating a role expression;

determining whether the operator in the role expression is a pronominal operator;

if the operator in the role expression is a pronominal operator referring to a discourse referent,

creating a model element referencing the discourse referent;

else, creating a model element representing the operator.

8. The method of claim 1 wherein processing the expression model to generate a logical model comprises:

processing terms included in the expression model to associate each of the terms with a type;

processing a sentence form included in the expression model to associate the sentence form with a fact type;

if the expression model includes a name, processing the name to map the name to a type, the name corresponding to a term of the processed terms;

if the expression model includes a nominal restrictive form, processing the nominal restrictive form to map the nominal restrictive form to a fact type;

if the expression model includes a mathematical function form, processing the mathematical function form to map the mathematical function form to a fact type;

if the expression model includes an identity criterion, processing the identity criterion to map the identity criterion to a type;

if at least one of the types has type specializations or generalizations, deriving the type specializations and generalizations for the one of the types;

if at least one of the types has fact type specializations or generalizations, deriving the fact type specializations and generalizations for the one of the fact types; and

if the expression model includes an expression, processing the expression to generate a logical formulation, the expression including at least one of a name, a term, a function form having at least a placeholder, and an identity criterion.

9. The method of claim 1 wherein processing the logical model to generate a platform-independent implementation model comprises:

generating a component interface model from the business rule if the business rule is an authorization rule to provide information or an authorization rule to request information;

generating a database model from the logical model; and

generating an execution model from the logical model.

10. The method of claim 1 wherein the target platform description comprises:

specification of a component interface technology;

specification of a database system; and

specification of a programming platform.

11. A system for generating software components from one or more rule statements expressed in a natural language, the system comprising:

a computing system having a processor and one or more storage media in communication with the processor, the one or more storage media storing;

a natural language parser for using the processor in parsing at least one rule statement based on a vocabulary of a natural language and grammatical rules of the natural language to generate a language-dependent structure of the rule statement, wherein the natural language parser identifies symbols used and their interrelationships with respect to a sentence structure, wherein the parsing reports how each word in the rule statement is categorized into;

a) terms defined in the vocabulary,

b) names defined in the vocabulary for individual things,

c) connecting symbols of function forms defined in the vocabulary,

d) key words and phrases, quantifiers, and logical connectives, and

e) words that are not recognized;

an expression model generator for using the processor in processing the language-dependent structure of the rule statement to generate an expression model;

a logical model generator for using the processor in processing the expression model to generate a logical model, wherein generating the logical model comprises;

a) relating synonymous terms to a single concept;

b) relating synonymous forms and related noun forms to a single fact type;

c) relating synonymous names to a single instance;

d) relating each instance to its corresponding concept;

e) determining identifying fact types for concepts;

f) determining generalizations between concepts; and

g) reporting logical inconsistencies, if any;

a platform-independent implementation model generator for using the processor in processing the logical model to generate a platform-independent implementation model in response to a request for such generation; and

a platform-specific implementation model generator for using the processor in receiving description of a specific target platform and processing the platform-independent implementation model using the description of the target platform to generate a platform-specific implementation model.

12. The system of claim 11 further comprising:

a software component generator for generating and assembling software components for deployment on the target platform.

13. The system of claim 11 further comprising:

a graphic user interface for receiving the rule statement and the vocabulary of the natural language;

wherein the logical model generator is in communication with the natural language parser and the graphical user interface to provide feedback to a user regarding logical consistency of the rule statement.

14. An article of manufacture embodied on a machine-accessible tangible medium, to be used for generating software components from one or more rule statements expressed in a natural language, the article of manufacture comprising:

the machine-accessible, tangible medium storing computer-executable instructions that, when accessed and executed by a machine, cause the machine to;

receive symbols of a vocabulary of a natural language, the natural language having grammatical rules, and details about each of the symbols;

receive at least one rule statement expressed using the symbols of the vocabulary of the natural language;

parse the rule statement in accordance with the natural language grammatical rules to generate a language-based structure of the rule statement that identifies the symbols used and their interrelationships with respect to a sentence structure, wherein the parsing reports how each word in the rule statement is categorized into;

a) terms defined in the vocabulary,

b) names defined in the vocabulary for individual things,

c) connecting symbols of function forms defined in the vocabulary,

d) key words and phrases, quantifiers, and logical connectives, and

e) words that are not recognized;

process the language-based structure of the rule statement corresponding to an expression to generate an expression model;

process the expression model to generate a logical model wherein processing the expression model comprises;

a) relating synonymous terms to a single concept;

b) relating synonymous forms and related noun forms to a single fact type;

c) relating synonymous names to a single instance;

d) relating each instance to its corresponding concept;

e) determining identifying fact types for concepts;

f) determining generalizations between concepts; and

g) reporting logical inconsistencies, if any;

process the logical model to generate a platform-independent implementation model in response to a request for such generation;

receive a specific target platform description; and

process the platform-independent implementation model using the specific target platform description to generate a platform-specific implementation model.

15. The article of manufacture of claim 14 wherein the data further comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

processing the platform-specific model to generate software components for deployment.

16. The article of manufacture of claim 14 wherein the data further comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

providing feedback to a user regarding the rule statement to resolve logical inconsistency.

17. The article of manufacture of claim 14 wherein the data causing the machine to perform the operation of parsing the rule statement comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

breaking the rule statement into tokens;

identifying, among the tokens, first tokens that correspond to terms, and, if the rule statement includes names, second tokens that correspond to the names;

identifying, among the tokens, third tokens that correspond to connecting symbols;

identifying, among the tokens, fourth tokens that correspond to key words and phrases; and

constructing a parse tree representing the language-based structure of the rule statement.

18. The article of manufacture of claim 14 wherein the data causing the machine to perform the operation of processing the language-based structure of the rule statement corresponding to an expression to generate an expression model comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

creating a model element for the expression;

determining whether the expression has a logical connective;

if the expression has no logical connective,

marking the expression as a simple expression;

identifying function form that corresponds to the expression; and

processing the model element representing the expression;

if the expression has a logical connective,

creating a model element for the logical connective.

19. The article of manufacture of claim 18 wherein the data causing the machine to perform the operation of processing the language-based structure of the rule statement corresponding to an expression to generate an expression model further comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

if the expression has a logical connective,

repeating recursively the operations in claim 5 for each of the propositions included in the expression that are connected by the logical connective, substituting each of the proposition as the expression in the operations.

20. The article of manufacture of claim 18 wherein the data causing the machine to perform the operation of processing the model element representing the expression comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

for a role in the expression, creating a role expression;

determining whether the operator in the role expression is a pronominal operator;

if the operator in the role expression is a pronominal operator referring to a discourse referent,

creating a model element referencing the discourse referent;

else, creating a model element representing the operator.

21. The article of manufacture of claim 14 wherein the data causing the machine to perform the operation of processing the expression model to generate a logical model comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

processing terms included in the expression model to associate each of the terms with a type;

processing a sentence form included in the expression model to associate the sentence form with a fact type;

if the expression model includes a name, processing the name to map the name to a type, the name corresponding to a term of the processed terms;

if the expression model includes a nominal restrictive form, processing the nominal restrictive form to map the nominal restrictive form to a fact type;

if the expression model includes a mathematical function form, processing the mathematical function form to map the mathematical function form to a fact type;

if the expression model includes an identity criterion, processing the identity criterion to map the identity criterion to a type;

if at least one of the types has type specializations or generalizations, deriving the type specializations and generalizations for the one of the types;

if at least one of the types has fact type specializations or generalizations, deriving the fact type specializations and generalizations for the one of the fact types; and

if the expression model includes an expression, processing the expression to generate a logical formulation, the expression including at least one of a name, a term, a function form having at least a placeholder, and an identity criterion.

22. The article of manufacture of claim 14 wherein the data causing the machine to perform the operation of processing the logical model to generate a platform-independent implementation model comprises data that, when accessed by the machine, causes the machine to perform operations comprising:

generating a component interface model from the business rule if the business rule is an authorization rule to provide information or an authorization rule to request information;

generating a database model from the logical model; and

generating an execution model from the logical model.

23. The article of manufacture of claim 14 wherein the target platform description comprises:

specification of a component interface technology;

specification of a database system; and

specification of a programming platform.

24. A system for generating software components from one or more rule statements expressed in a natural language, the method, the system comprising:

a processor;

a memory coupled to the processor and the memory containing instructions that, when executed by the processor, cause the processor to;

receive symbols of a vocabulary of a natural language, the natural language having grammatical rules, and details about each of the symbols;

receive at least one rule statement expressed using the symbols of the vocabulary of the natural language;

parse the rule statement in accordance with the natural language grammatical rules to generate a language-based structure of the rule statement that identifies the symbols used and their interrelationships with respect to a sentence structure, wherein the parsing reports how each word in the rule statement is categorized into;

a) terms defined in the vocabulary,

b) names defined in the vocabulary for individual things,

c) connecting symbols of function forms defined in the vocabulary,

d) key words and phrases, quantifiers, and logical connectives, and

e) words that are not recognized;

process the language-based structure of the rule statement corresponding to an expression to generate an expression model;

process the expression model to generate a logical model wherein processing the expression model comprises;

a) relating synonymous terms to a single concept;

b) relating synonymous forms and related noun forms to a single fact type;

c) relating synonymous names to a single instance;

d) relating each instance to its corresponding concept;

e) determining identifying fact types for concepts;

f) determining generalizations between concepts; and

g) reporting logical inconsistencies, if any;

process the logical model to generate a platform-independent implementation model in response to a request for such generation;

receive a specific target platform description; and

process the platform-independent implementation model using the specific target platform description to generate a platform-specific implementation model.

25. The system of claim 24 wherein the instructions further comprise instructions that, when executed by the processor, cause the processor to:

process the platform-specific model to generate software components for deployment.

26. The system of claim 24 wherein the instructions further comprise instructions that, when executed by the processor, cause the processor to:

provide feedback to a user regarding the rule statement to resolve logical inconsistency.

27. The system of claim 24 wherein the instructions causing the processor to parse the rule statement comprise instructions that, when executed by the processor, cause the processor to:

break the rule statement into tokens;

identify, among the tokens, first tokens that correspond to terms, and, if the rule statement includes names, second tokens that correspond to the names;

identify, among the tokens, third tokens that correspond to connecting symbols;

identify, among the tokens, fourth tokens that correspond to key words and phrases; and

construct a parse tree representing the language-based structure of the rule statement.

28. The system of claim 24 wherein the instructions causing the processor to process the language-based structure of the rule statement corresponding to an expression to generate an expression model comprise instructions that, when executed by the processor, cause the processor to:

create a model element for the expression;

determine whether the expression has a logical connective;

if the expression has no logical connective,

mark the expression as a simple expression;

identify function form that corresponds to the expression; and

process the model element representing the expression;

if the expression has a logical connective,

create a model element for the logical connective.

29. The system of claim 28 wherein the instructions causing the processor to process the language-based structure of the rule statement to generate an expression model further comprise instructions that, when executed by the processor, cause the processor to:

if the expression has a logical connective,

repeat recursively the operations in claim 5 for each of the propositions included in the expression that are connected by the logical connective, substituting each of the proposition as the expression in the operations.

30. The system of claim 28 wherein the instructions causing the processor to process the model element representing the expression comprise instructions that, when executed by the processor, cause the processor to:

for a role in the expression, creating a role expression;

determine whether the operator in the role expression is a pronominal operator;

if the operator in the role expression is a pronominal operator referring to a discourse referent,

create a model element referencing the discourse referent;

else, create a model element representing the operator.

31. The system of claim 24 wherein the instructions causing the processor to process the expression model to generate a logical model comprise instructions that, when executed by the processor, cause the processor to:

process terms included in the expression model to associate each of the terms with a type;

process a sentence form included in the expression model to associate the sentence form with a fact type;

if the expression model includes a name, process the name to map the name to a type, the name corresponding to a term of the processed terms;

if the expression model includes a nominal restrictive form, process the nominal restrictive form to map the nominal restrictive form to a fact type;

if the expression model includes a mathematical function form, process the mathematical function form to map the mathematical function form to a fact type;

if the expression model includes an identity criterion, process the identity criterion to map the identity criterion to a type;

if at least one of the types has type specializations or generalizations, derive the type specializations and generalizations for the one of the types;

if at least one of the types has fact type specializations or generalizations, derive the fact type specializations and generalizations for the one of the fact types; and

if the expression model includes an expression, process the expression to generate a logical formulation, the expression including at least one of a name, a term, a function form having at least a placeholder, and an identity criterion.

32. The system of claim 24 wherein the instructions causing the processor to process the logical model to generate a platform-independent implementation model comprise instructions that, when executed by the processor, cause the processor to:

generate a component interface model from the business rule if the business rule is an authorization rule to provide information or an authorization rule to request information;

generate a database model from the logical model; and

generate an execution model from the logical model.

33. The system of claim 24 wherein the target platform description comprises:

specification of a component interface technology;

specification of a database system; and

specification of a programming platform.