Method and apparatus for estimating computer software development effort

• US 6,810,392 B1
• Filed: 07/31/1998
• Issued: 10/26/2004
• Est. Priority Date: 07/31/1998
• Status: Expired due to Term

• Current Assignee: Northrop Grumman Systems Corporation (Northrop Grumman Corporation)
• Original Assignee: Northrop Grumman Corporation
• Inventors: Piggott, Bryan Norman
• Primary Examiner(s): STARKS, WILBERT L
• Application Number:
  US09/126,817
• Time in Patent Office: 2,279 Days
• Field of Search: 704/4, 704/8, 704/9
• US Class Current: 706/12
• CPC Class Codes: G06F 8/30 Creation or generation of source code

Abstract

The use of a natural language engine to locate software functionality in a free text document such as a requirements document is disclosed. An electronic version of a free text document is created. A natural language engine is trained to locate function points. The natural language engine performs an analysis of the electronic version of the free text document to locate function points in the electronic version of the free text document. Advantageously, the natural language engine eliminates human subjectivity from the identification of and counting of function points. Other types of functional counting methodologies can also be used in the present invention such as feature points.

Claims

1. A method of analyzing a textual document to determine the amount of effort required to develop software code to meet functionality requirements requested in the textual document, comprising:

training a natural language engine to recognize and search for phrases in textual documents which are representative of software functionality;

analyzing the textual document using the trained natural language engine to determine software functionality requirements requested in the textual document.

2. The method of claim 1, wherein the natural language engine is PAKTUS.

3. The method of claim 1, wherein the software functionality requirements are function points.

4. The method of claim 3, comprising labeling portions of the textual document as one of EI, EO, ILF, EIF and IQ.

5. The method of claim 1, comprising identifying function points.

6. The method of claim 4, comprising counting function points.

7. The method of claim 1, wherein the textual document is source code.

8. The method of claim 1, wherein the textual document is free text.

9. The method of claim 8, wherein the textual document is in the English language.

10. The method of claim 7, comprising comparing the text against the actual source code generated to further train the natural language engine.

11. The method of claim 1, comprising providing electronically encoded data representative of the textual document.

12. The method of claim 1, further comprising outputting a table of phrases representing software functionality requirements.

13. The method of claim 1, further comprising highlighting portions of the textual document which include software functionality requirements.

14. The method of claim 4, comprising relating EI, EO, ILF, EIF and IQ to each other and providing information that the relationship between EI, EO, ILF, EIF and IQ is insufficient to define a function point.

15. An article, comprising:

at least one sequence of machine executable instructions;

a medium bearing the executable instructions in machine readable form, which execution of the instructions by one or more processors causes the one or more processors to;

train a natural language engine to recognize and search for phrases in textual documents which are representative of software functionality;

analyze the textual document using the trained natural language engine to determine software functionality requirements requested in the textual document.

16. A computer architecture for analyzing a textual document to determine the amount of effort required to develop software code to meet functionality requirements requested in the textual document, comprising:

training means for training a natural language engine to recognize and search for phrases in textual documents which are representative of software functionality;

analyzing means for analyzing the textual document using the trained natural language engine to determine software functionality requirements requested in the textual document.

17. A computer system comprising:

a processor; and

a memory coupled to said processor, the memory having stored therein sequences of instructions, which, when executed by said processor, cause said processor to perform the steps of;

training a natural language engine to recognize and search for phrases in textual documents which are representative of software functionality;

analyzing the textual document using the trained natural language engine to determine software functionality requirements requested in the textual document.