Categorization and presentation tool for code resources

• US 6,785,683 B1
• Filed: 07/06/2000
• Issued: 08/31/2004
• Est. Priority Date: 07/06/2000
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Yaeli, Avi, Bortnikov, Vita, Zodik, Gabi
• Primary Examiner(s): ABEL JALIL, NEVEEN
• Application Number:
  US09/611,060
• Time in Patent Office: 1,517 Days
• Field of Search: 707/2, 707/3, 707/102, 707/100, 707/104, 707/10, 707/101, 706/45, 706/10, 704/4, 717/2
• US Class Current: 1/1
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation
• CPC Class Codes: Y10S 707/99943 Generating database or data structure, e.g. via user interface

Abstract

A technique for rapid retrieval and navigation of assets stored on a computer system involves defining a taxonomy and classification rules according to asset-specific criteria, identifying the stored assets, automatically categorizing the identified assets according to the defined classification system, followed by indexing of the categorized assets. A presentation tool is utilized to display and navigate the indexed assets in a first pane, using a tree view having two integrated hierarchies of classified information. The hierarchies can be specific to a programming language or other code assets. All categories of indexed information in which a said selected element is classified is displayed in a second pane.

Claims

1. A computer-implemented method for locating program code assets stored on a storage device, comprising the steps of:

defining asset-specific categories for classification of asset-specific information, said categories relating to predefined features of an object-oriented programming language used in creating said program code assets;

identifying stored program code assets;

extracting said asset-specific information from said stored program code assets using semantic characteristics of said object-oriented programming language to define extracted information;

classifying said extracted information in said asset-specific categories according to a predefined set of rules to define classified textual and semantic information; and

storing said classified textual and semantic information for retrieval,

wherein extracting said asset-specific information comprises dividing composite names in the program code assets into single words.

2. The method according to claim 1, wherein dividing said composite names comprises searching the program code assets for capital letters inside strings, and dividing said strings such that an individual word begins with each of the capital letters.

3. A computer-implemented method for locating program code assets stored on a storage device, comprising the steps of:

defining asset-specific categories for classification of asset-specific information, said categories relating to predefined features of an object-oriented programming language used in creating said program code assets;

identifying stored program code assets;

extracting said asset-specific information from said stored program code assets using semantic characteristics of said object-oriented programming language to define extracted information;

classifying said extracted information in said asset-specific categories according to a predefined set of rules to define classified textual and semantic information; and

storing said classified textual and semantic information for retrieval,

wherein said features are arranged in a plurality of groups according to said semantics of said object-oriented programming language, and wherein said set of rules comprises a plurality of subsets, which are respectively applicable to said plurality of groups, and

wherein said assets comprise a class, and wherein said groups comprise a name group, comprising names that describe behavior of said class.

4. The method according to claim 3, wherein said step of extracting is performed with a language specific parser.

5. The method according to claim 3, wherein said predefined set of rules comprises a plurality of predefined sets of rules, each of said predefined sets of rules being applied to a different language specific group.

6. The method according to claim 3, wherein said storage device comprises a plurality of storage devices linked in a communications network.

7. The method according to claim 3, further comprising automatically updating said steps of identifying, extracting, and classifying, when a new resource is stored in said storage device.

8. The method according to claim 3, wherein said step of extracting is performed with a language specific parser.

9. The method according to claim 8, further comprising a step of grouping information obtained in said step of extracting according to a plurality of language specific groups.

10. The method according to claim 9, wherein said predefined set of rules comprises a plurality of sets of rules, each of said sets of rules being applied to a different one of said language specific groups.

11. The method according to claim 3, wherein said storage device comprises a plurality of storage devices linked in a communications network.

12. The method according to claim 3, further comprising the steps of automatically updating said steps of identifying, extracting, and classifying, when a new resource is stored in said storage device.

13. The method according to claim 3, wherein said names comprise a parent name of said class.

14. The method according to claim 13, wherein said parent name defines an inheritance relation characteristic of said class.

15. The method according to claim 3, wherein said names comprise at least one of a method name of a method in said class and a member function name of a member function in said class.

16. The method according to claim 3, and comprising:

displaying said stored information in a tree view having a first hierarchy of said classified textual and semantic information and a second hierarchy of said classified textual and semantic information, wherein nodes that are represented in said tree view comprise nodes of said first hierarchy and nodes of said second hierarchy.

17. The method according to claim 16, wherein said step of displaying further comprises the steps of:

selecting a displayed element in a first display area to define a selected element; and

displaying all categories of said stored information in which said selected element is classified.

18. The method according to claim 17, wherein said selected element is classified according to a category relevancy score.

19. The method according to claim 16, wherein said first hierarchy comprises categories of a computer programming language that were identified in said step of classifying, and said second hierarchy comprises a hierarchy of instances of said categories.

20. The method according to claim 19, wherein said second hierarchy comprises a class package.

21. The method according to claim 19, wherein said second hierarchy comprises a name space.

22. The method according to claim 3, wherein a syntax of rules in said predefined set of rules is “

<

condition>

→

<

category>

@<

weight-factor>

”

.

23. A computer software product for locating program code assets stored on a storage device, the product comprising a computer-readable medium in which computer program instructions are stored, which instructions, when read by a computer, cause the computer to perform the steps of:

receiving a definition of asset-specific categories for classification of asset-specific information, said categories relating to predefined features of an object-oriented programming language used in creating said program code assets;

identifying stored program code assets;

extracting said asset-specific information from said stored program code assets using semantic characteristics of said object-oriented programming language to define extracted information;

classifying said extracted information in said asset-specific categories according to a predefined set of rules to define classified textual and semantic information; and

storing said classified textual and semantic information for retrieval,

wherein extracting said asset-specific information comprises dividing composite names in the program code assets into single words.

24. The product according to claim 23, wherein dividing said composite names comprises searching the program code assets for capital letters inside strings, and dividing said strings such that an individual word begins with each of the capital letters.

25. A computer software product for locating program code assets stored on a storage device, the product comprising a computer-readable medium in which computer program instructions are stored, which instructions, when read by a computer, cause the computer to perform the steps of:

receiving a definition of asset-specific categories for classification of asset-specific information, said categories relating to predefined features of an object-oriented programming language used in creating said program code assets;

identifying stored program code assets;

extracting said asset-specific information from said stored program code assets using semantic characteristics of said object-oriented programming language to define extracted information;

classifying said extracted information in said asset-specific categories according to a predefined set of rules to define classified textual and semantic information; and

storing said classified textual and semantic information for retrieval,

wherein said features are arranged in a plurality of groups according to said semantics of said object-oriented programming language, and wherein said set of rules comprises a plurality of subsets, which are respectively applicable to said plurality of groups, and

wherein said assets comprise a class, and wherein said groups comprise a name group, comprising names that describe behavior of said class.

26. The computer software product according to claim 25, further comprising the steps of automatically updating said steps of identifying, extracting, and classifying, when a new resource is stored.

27. The computer software product according to claim 25, wherein said storage device comprises a plurality of storage devices linked in a communications network.

28. The computer software product according to claim 25, wherein said step of extracting is performed with a language specific parser.

29. The computer software product according to claim 28, further comprising a step of grouping information obtained in said step of extracting according to a plurality of language specific groups.

30. The computer software product according to claim 29, wherein said predefined set of rules comprises a plurality of sets of rules, each of said sets of rules being applied to a different one of said language specific groups.

31. The product according to claim 25, wherein said names comprise a parent name of said class.

32. The product according to claim 31, wherein said parent name defines an inheritance relation characteristic of said class.

33. The product according to claim 25, wherein said names comprise at least one of a product name of a product in said class and a member function name of a member function in said class.

34. The product according to claim 25, wherein said instructions further cause the computer to perform the step of:

displaying said stored information in a tree view having a first hierarchy of said classified textual and semantic information and a second hierarchy of said classified textual and semantic information, wherein nodes that are represented in said tree view comprise nodes of said first hierarchy and nodes of said second hierarchy.

35. The computer software product according to claim 34, wherein said step of displaying further comprises the steps of:

selecting a displayed element in said first display area; and

in a second display area of said monitor displaying all categories of said stored information in which a selected element is classified.

36. The computer software product according to claim 35, wherein said selected element is classified according to a category relevancy score.

37. The computer software product according to claim 34, wherein said first hierarchy comprises categories of a computer programming language that were identified in said step of classifying, and said second hierarchy comprises a hierarchy of instances of said categories.

38. The computer software product according to claim 37, wherein said second hierarchy comprises a class package.

39. The computer software product according to claim 37, wherein said second hierarchy comprises a name space.

40. The product according to claim 25, wherein a syntax of rules in said predefined set of rules is “

<

condition>

→

<

category>

@<

weight-factor>

”

.

41. A computer system, comprising:

a storage device for storage of program code assets therein;

a memory for storage of program instructions; and

an execution unit that accesses said program instructions in said memory for execution thereof, wherein said program instructions cause said execution unit to perform the steps of;

defining asset-specific categories for classification of asset-specific information, said categories relating to predefined features of an object-oriented programming language used in creating said program code assets;

identifying stored program code assets;

extracting said asset-specific information from said stored program code assets using semantic characteristics of said object-oriented programming language to define extracted information;

classifying said extracted information in said asset-specific categories according to a predefined set of rules to define classified textual and semantic information; and

storing said classified textual and semantic information for retrieval,

wherein extracting said asset-specific information comprises dividing composite names in the program code assets into single words.

42. The system according to claim 41, wherein dividing said composite names comprises searching the program code assets for capital letters inside strings, and dividing said strings such that an individual word begins with each of the capital letters.

43. A computer system, comprising:

a storage device for storage of program code assets therein;

a memory for storage of program instructions; and

an execution unit that accesses said program instructions in said memory for execution thereof, wherein said program instructions cause said execution unit to perform the steps of;

defining asset-specific categories for classification of asset-specific information, said categories relating to predefined features of an object-oriented programming language used in creating said program code assets;

identifying stored program code assets;

extracting said asset-specific information from said stored program code assets using semantic characteristics of said object-oriented programming language to define extracted information;

classifying said extracted information in said asset-specific categories according to a predefined set of rules to define classified textual and semantic information; and

storing said classified textual and semantic information for retrieval,

wherein said features are arranged in a plurality of groups according to said semantics of said object-oriented programming language, and wherein said set of rules comprises a plurality of subsets, which are respectively applicable to said plurality of groups, and

wherein said assets comprise a class, and wherein said groups comprise a name group, comprising names that describe behavior of said class.

44. The computer system according to claim 43, wherein said program instructions further cause the computer to automatically update said steps of identifying, extracting, and classifying when a new resource is stored in said storage device.

45. The computer system according to claim 43, wherein said storage device comprises a plurality of storage devices linked in a communications network.

46. The computer system according to claim 43, wherein said step of extracting is performed with a language specific parser.

47. The computer system according to claim 46, wherein said program instructions further cause the execution unit to group information obtained in said step of extracting according to a plurality of language specific groups.

48. The computer system according to claim 47, wherein said predefined set of rules comprises a plurality of sets of rules, each of said sets of rules being applied to a different one of said language specific groups.

49. The system according to claim 43, wherein said names comprise a parent name of said class.

50. The system according to claim 49, wherein said parent name defines an inheritance relation characteristic of said class.

51. The system according to claim 43, wherein said names comprise at least one of a system name of a system in said class and a member function name of a member function in said class.

52. The system according to claim 43, wherein the system further comprises a display monitor, and wherein said program instructions further cause said execution unit to perform the step of:

displaying said stored information on said display monitor in a tree view having a first hierarchy of said classified textual and semantic information and a second hierarchy of said classified textual and semantic information, wherein nodes that are represented in said tree view comprise nodes of said first hierarchy and nodes of said second hierarchy.

53. The computer system according to claim 52, wherein said step of displaying further comprises the steps of:

selecting a displayed element in said first display area; and

in a second display area of said display monitor displaying all categories of said stored information in which a selected element is classified.

54. The computer system according to claim 53, wherein said selected element is classified according to a category relevancy score.

55. The computer system according to claim 52, wherein said first hierarchy comprises categories of a computer programming language that were identified in said step of classifying, and said second hierarchy comprises a hierarchy of instances of said categories.

56. The computer system according to claim 55, wherein said second hierarchy comprises a class package.

57. The computer system according to claim 55, wherein said second hierarchy comprises a name space.

58. The system according to claim 43, wherein a syntax of rules in said predefined set of rules is “

<

condition>

→

<

category>

@<

weight-factor>

”

.