Knowledge extraction and transformation

• US 8,412,653 B2
• Filed: 07/01/2010
• Issued: 04/02/2013
• Est. Priority Date: 03/09/2006
• Status: Active Grant

• Current Assignee: EvolveWare, Inc.
• Original Assignee: EvolveWare, Inc.
• Inventors: Marfatia, Miten, Rambhia, Ajay M.
• Primary Examiner(s): RIFKIN, BEN M
• Application Number:
  US12/829,278
• Publication Number:
  US 20100275182A1
• Time in Patent Office: 1,006 Days
• Field of Search: 706/45
• US Class Current: 706/14
• CPC Class Codes: G06F 8/51 Source to source
• CPC Class Codes: G06F 8/73 Program documentation
• CPC Class Codes: G06F 8/74 Reverse engineering; Extracting design information from source code
• CPC Class Codes: G06N 5/022 Knowledge engineering; Knowledge acquisition
• CPC Class Codes: G06N 5/048 Fuzzy inferencing
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 10/087 Inventory or stock management, e.g. order filling, procurement or balancing against orders
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

The present disclosure includes a system and method for learning (or discovering and extracting) business knowledge from a collection of source code. The collection of source code is abstracted to generate an abstracted data stream, which is then transformed to an Extensible Markup Language (XML) format. The transformed data in XML format can be further converted to target formats or processed to satisfy different needs such as software system documentation, migration, impact analysis and security analysis. The disclosure also includes an implementation and operation for a pattern abstraction engine configured to receive an input data stream and format it for abstraction into a standard format using a pattern matching mechanism. The disclosure also includes an implementation and operation for a contextual pattern decoder engine configured to extract knowledge attributes and contextual taxonomy from classified blocks of an input data stream.

Claims

1. A computer-implemented method for transforming source code of an application, the method comprising:

receiving the source code in a programming language;

accessing a plurality of predefined patterns stored in a contextual taxonomy store;

pattern matching a plurality of blocks in the source code using the plurality of predefined patterns, wherein a pattern comprises one or more restrictions and a piece of text matches the pattern if the piece of text satisfies the one or more restrictions of the pattern;

determining an unmatched block of the source code that does not match any of the plurality of predefined patterns;

generating a dynamic pattern that matches the unmatched block of the source code using dynamic rules;

determining the relevance of the dynamic pattern for future pattern matching using fuzzy rules;

responsive to determining that the dynamic pattern is relevant, storing the dynamic pattern in the contextual taxonomy store;

classifying two or more of the plurality of blocks into a logic block that corresponds to a business rule;

discovering a knowledge element from the logic block using the dynamic pattern, the knowledge element being one of the following;

a data entity and a variable;

tracing a life cycle of the knowledge element in the logic block; and

transforming the source code into a desired target format based on the dynamic pattern, the predefined patterns, and the life cycle of the knowledge element.

2. The computer-implemented method of claim 1, wherein tracing the life cycle of the knowledge element comprises:

creating a life cycle flow graph for the knowledge element identifying how a value of the data entity changes within the logic block due to actions performed by one or more statements in the logic block.

3. The computer-implemented method of claim 2, further comprising:

marking the knowledge element, life cycle information of the knowledge element, and one or more statements associated with the knowledge element in the logic block using the life cycle flow graph.

4. The computer-implemented method of claim 2, further comprising:

extracting taxonomy information from the logic block using the life cycle flow graph, wherein the taxonomy information comprises a name of the knowledge element used in the logic block and its life cycle information.

5. The computer-implemented method of claim 4, wherein transforming the source code further comprises:

transforming the source code into the desired target format based at least in part on the extracted taxonomy information and one or more patterns derived from the logic block using the life cycle flow graph.

6. The computer-implemented method of claim 2, further comprising:

deriving an association of the knowledge element with the one or more statements in the logic block.

7. A system for transforming source code of an application, comprising a computer processor and a computer readable medium storing instructions executable by the processor, the instructions when executed by the processor implementing components comprising:

a contextual pattern decoder engine configured to receive the source code in a programming language;

a contextual taxonomy store configured to store a plurality of predefined patterns;

a pattern classification engine configured to;

pattern match a plurality of blocks in the source code using the plurality predefined patterns and classify two or more of the plurality of blocks into a logic block that corresponds to a business rule, wherein a pattern comprises one or more restrictions and a piece of text matches the pattern if the piece of text satisfies the one or more restrictions of the pattern; and

determine an unmatched block of the source code that does not match any of the plurality of predefined patterns;

a pattern hatcher engine configured to generate a dynamic pattern that matches the unmatched block of the source code using dynamic rules;

a pattern filtering engine configured to;

determine the relevance of the dynamic pattern for future pattern matching using fuzzy rules; and

store the dynamic pattern in the contextual taxonomy store, responsive to determining that the dynamic pattern is relevant;

a contextual pattern decoder engine configured to discover a knowledge element from the logic block using the dynamic pattern, the knowledge element being one of the following;

a data entity and a variable, trace a life cycle of the knowledge element in the logic block, and transform the source code into a desired target format based on the dynamic pattern, the predefined patterns and the life cycle of the knowledge element.

8. The system of claim 7, wherein the contextual pattern decoder engine is further configured to create a life cycle flow graph for the knowledge element identifying how a value of the data entity changes within the logic block due to actions performed by one or more statements in the logic block.

9. The system of claim 8, wherein the contextual pattern decoder engine is further configured to mark the knowledge element, life cycle information of the knowledge element, and one or more statements associated with the knowledge element in the logic block using the life cycle flow graph.

10. The system of claim 8, wherein the contextual pattern decoder engine is further configured to extract taxonomy information from the logic block using the life cycle flow graph, wherein the taxonomy information comprises a name of the knowledge element used in the logic block and its life cycle information.

11. The system of claim 10, wherein the contextual pattern decoder engine is further configured to transform the source code into the desired target format based at least in part on the extracted taxonomy information and one or more patterns derived from the logic block using the life cycle flow graph.

12. The system of claim 8, wherein the contextual pattern decoder engine is further configured to derive an association of the knowledge element with the one or more statements in the logic block.

13. A non-transitory computer readable medium structured to store instructions executable by at least one processor to transform source code of an application, the instructions when executed by the at least one processor cause the at least one processor to:

receive the source code in a programming language;

access a plurality of predefined patterns stored in a contextual taxonomy store;

pattern match a plurality of blocks in the source code using the plurality of predefined patterns, wherein a pattern comprises one or more restrictions and a piece of text matches the pattern if the piece of text satisfies the one or more restrictions of the pattern;

determine an unmatched block of the source code that does not match any of the plurality of predefined patterns;

generate a dynamic pattern that matches the unmatched block of the source code using dynamic rules;

determine the relevance of the dynamic pattern for future pattern matching using fuzzy rules;

store the dynamic pattern in the contextual taxonomy store, responsive to determining that the dynamic pattern is relevant;

classify two or more of the plurality of blocks into a logic block that corresponds to a business rule;

discover a knowledge element from the logic block using the dynamic pattern, the knowledge element being one of the following;

a data entity and a variable;

trace a life cycle of the knowledge element in the logic block; and

transform the source code into a desired target format based on the dynamic pattern, the predefined patterns, and the life cycle of the knowledge element.

14. The non-transitory computer readable medium of claim 13, wherein the instructions when executed by the at least one processor further cause the at least one processor to:

create a life cycle flow graph for the knowledge element identifying how a value of the data entity changes within the logic block due to actions performed by one or more statements in the logic block.

15. The non-transitory computer readable medium of claim 14, wherein the instructions when executed by the at least one processor further cause the at least one processor to:

mark the knowledge element, life cycle information of the knowledge element, and one or more statements associated with the knowledge element in the logic block using the life cycle flow graph.

16. The non-transitory computer readable medium of claim 14, wherein the instructions when executed by the at least one processor further cause the at least one processor to:

extract taxonomy information from the logic block using the life cycle flow graph, wherein the taxonomy information comprises a name of the knowledge element used in the logic block and its life cycle information.

17. The non-transitory computer readable medium of claim 16, wherein the instructions when executed by the at least one processor further cause the at least one processor to:

transform the source code into the desired target format based at least in part on the extracted taxonomy information and one or more patterns derived from the logic block using the life cycle flow graph.

18. The non-transitory computer readable medium of claim 14, wherein the instructions when executed by the at least one processor further cause the at least one processor to:

derive an association of the knowledge element with the one or more statements in the logic block.