Systems And Methods For Software Analytics

• US 20150363197A1
• Filed: 06/10/2015
• Published: 12/17/2015
• Est. Priority Date: 06/13/2014
• Status: Abandoned Application

• Current Assignee: Charles Stark Draper Laboratory Incorporated
• Original Assignee: Charles Stark Draper Laboratory Incorporated
• Inventors: Carback, Richard T. III, Gaynor, Brad D., Shnidman, Nathan R., Chin, Sang Hoon
• Application Number:
  US14/735,684
• Publication Number:
  US 20150363197A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 11/362 Software debugging
• CPC Class Codes: G06F 11/3672 Test management
• CPC Class Codes: G06F 8/37 Compiler construction; Parser generation
• CPC Class Codes: G06F 8/70 Software maintenance or management
• CPC Class Codes: G06F 8/73 Program documentation
• CPC Class Codes: G06F 8/75 Structural analysis for program understanding

Abstract

Systems, methods, and computer program products are provided for locating design patterns in software. An example method includes accessing a database having multiple artifacts corresponding to multiple software, and identifying a design pattern for at least one of the software files by automatically analyzing at least one of the artifacts associated with the software. Additional embodiments also provide for storing an identifier for the design pattern for the software in the database. For certain example embodiments, the artifacts include developmental, which may be searched for a string that denotes a design pattern, such as flaw, feature, or repair. Additional example embodiments also include finding in the software file a program fragment that implements the design pattern.

Claims

1. A method for identifying design patterns, comprising:

accessing a database having a plurality of artifacts for each of a plurality of files; and

identifying automatically a design pattern based on at least one of the plurality of artifacts for a first file of the plurality of files.

2. The method of claim 1 wherein the design pattern is in the first file.

3. The method of claim 1 wherein identifying automatically the design pattern further comprises basing the identification of the design pattern also on at least one of the plurality of artifacts for a second file of the plurality of files wherein the first file and the second file both belong to a project.

4. The method of claim 3 wherein identifying automatically the design pattern includes matching the at least one of the plurality of artifacts for the first file and the at least one of the plurality of artifacts for the second file to a pre-identified pattern denoting the design pattern.

5. The method of claim 4 wherein the design pattern relates to an interface between the first file and the second file.

6. The method of claim 1 wherein the design pattern is a flaw or a repair.

7. The method of claim 1 wherein the design pattern is a feature or a feature enhancement.

8. The method of claim 1 wherein the design pattern is a pre-identified program fragment.

9. The method of claim 1 wherein identifying automatically the design pattern based on the at least one of the plurality of artifacts includes locating in the at least one of the plurality of artifacts a character string that denotes a flaw or a repair.

10. The method of claim 9 wherein the at least one of the plurality of artifacts is a developmental artifact.

11. The method of claim 1 wherein identifying automatically the design pattern based on the at least one of the plurality of artifacts includes locating in the at least one of the plurality of artifacts a character string that denotes a feature or a feature enhancement.

12. The method of claim 11 wherein the at least one of the plurality of artifacts is a developmental artifact.

13. The method of claim 1 wherein identifying automatically the design pattern based on the at least one of the plurality of artifacts includes matching the at least one of the plurality of artifacts to a pre-identified pattern denoting the design pattern.

14. The method of claim 1 wherein the at least one of the plurality of artifacts each are a static artifact.

15. The method of claim 1 wherein the at least one of the plurality of artifacts each are a dynamic artifact.

16. The method of claim 1 wherein the at least one of the plurality of artifacts each are a derived artifact.

17. The method of claim 1 wherein the at least one of the plurality of artifacts each are a meta data artifact.

18. The method of claim 1 further comprising storing an identifier for the design pattern in the database.

19. The method of claim 18 wherein storing an identifier for the design pattern comprises storing a label for the design pattern using a character string obtained from at least one of the plurality of artifacts for the first file.

20. The method of claim 2 further comprising finding in the first file a program fragment that corresponds to the design pattern.

21. The method of claim 20 wherein the first file is in a binary code format.

22. The method of claim 20 wherein the first file is in a source code format.

23. The method of claim 20 wherein the first file is in an intermediate representation (IR) format.

24. A method for identifying design patterns, comprising:

accessing a database having a plurality of artifacts;

clustering the plurality of artifacts; and

identifying from the clustering a previously unidentified design pattern based on one or more previously identified design patterns.

25. The method of claim 24 wherein the previously unidentified design pattern and the one or more previously identified design patterns are the same design pattern.

26. The method of claim 24 wherein the previously identified design pattern is a flaw.

27. The method of claim 26 further comprising identifying one or more repairs associated with the previously identified flaw.

28. The method of claim 24 wherein the plurality of artifacts includes a plurality of developmental artifacts, and further comprising extracting a semantic meaning from the plurality of developmental artifacts that correspond to the clustered plurality of artifacts based on the occurrence of a character, word, or phrase in the developmental artifacts.

29. The method of claim 24 wherein clustering the plurality of artifacts includes using machine learning.

30. The method of claim 24 wherein clustering the plurality of artifacts includes using deep learning.

31. The method of claim 24 wherein clustering the plurality of artifacts includes using an auto-encoder.

32. The method of claim 24 further comprising providing training for the clustering of the plurality of artifacts wherein the training includes using one or more differences between a first version of a software file and a second version of the software file.

33. The method of claim 32 wherein the one or more differences correspond to a flaw or a repair.

34. The method of claim 33 wherein the flaw is a security vulnerability or the repair is a patch.

35. The method of claim 32 wherein the one or more differences correspond to a feature or a feature enhancement.

36. A system for identifying design patterns, comprising:

one or more storage devices having a plurality of artifacts for each of a plurality of files; and

a processor configured to identify automatically a design pattern based on at least one of the plurality of artifacts for a first file of the plurality of files.

37. The system of claim 36 further comprising the processor also being configured to find in the first file a program fragment that implements the design pattern.

38. The system of claim 36 wherein identify automatically the design pattern further comprises basing the identification of the design pattern also on at least one of the plurality of artifacts for a second file of the plurality of files wherein the first file and the second file both belong to a project.

39. The system of claim 36 wherein the design pattern is a flaw or a repair.

40. The system of claim 36 wherein the design pattern is a feature or a feature enhancement.

41. The system of claim 36 wherein the design pattern is a pre-identified program fragment.

42. A system for identifying design patterns, comprising:

one or more storage devices having a plurality of artifacts; and

a processor configured to cluster the plurality of artifacts, and

to identify from the clustering a previously unidentified design pattern based on one or more previously identified design patterns.

43. The system of claim 42 wherein the previously identified design pattern is a flaw.

44. The system of claim 42 further comprising identifying one or more repairs associated with the previously identified flaw.

45. The system of claim 42 wherein clustering the plurality of artifacts includes using machine learning.

46. The system of claim 42 wherein clustering the plurality of artifacts includes using deep learning.

47. A non-transitory computer readable medium with an executable program stored thereon, wherein the program instructs a processing device to perform the following steps:

access a database having a plurality of artifacts for each of a plurality of files; and

identify automatically a design pattern based on at least one of the plurality of artifacts for a first file of the plurality of files.

48. A non-transitory computer readable medium with an executable program stored thereon, wherein the program instructs a processing device to perform the following steps:

access a database having a plurality of artifacts;

cluster the plurality of artifacts; and

identify from the clustering a previously unidentified design pattern based on one or more previously identified design patterns.