Methods And Apparatus For Providing Predictive Analytics For Software Development

• US 20130311968A1
• Filed: 11/09/2012
• Published: 11/21/2013
• Est. Priority Date: 11/09/2011
• Status: Abandoned Application

• Current Assignee: Manoj Sharma
• Original Assignee: Manoj Sharma
• Inventors: Sharma, Manoj
• Application Number:
  US13/673,983
• Publication Number:
  US 20130311968A1
• Time in Patent Office: Days
• US Class Current: 717/101
• CPC Class Codes: G06F 11/008 Reliability or availability analysis
• CPC Class Codes: G06F 11/3692 for test results analysis
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling

Abstract

Managing large software projects is a notoriously difficult task. It is very difficult to project how long it will take to design, develop, and test the software thoroughly enough before it can be shipped to customers. To help with the task of software development, an advanced predictive analytics system is introduced. The predictive analytics system extracts metrics on code complexity, code churn, new features, testing, and bug tracking from a software development project. These extracted metrics are then provided to predictive analysis engine. The predictive analysis engine processes the extracted metrics in view of historical software development experience collected in a representative model. The predictive analysis engine outputs useful predictions such as future bug discover rates, customer found defects, and the probability of hitting a schedule ship date with a desired quality level.

Claims

1. A method of analyzing a computer software development project, said method comprising:

constructing a statistical software development model from previous software development experience;

collecting a set of code complexity metrics, said set of code complexity metrics derived a plurality of source code files;

collecting a set of code churn metrics, said set of code complexity metrics derived from a source code control system;

tracking bugs discovered in said computer software development project;

processing said set of code complexity metrics, said set of code churn metrics, and said bugs with predictive analysis engine using said statistical software development; and

outputting a set of predictions describing the future development trajectory of said computer software development project.

2. The method of analyzing a computer software development project as set forth in claim 1, said method further comprising:

collecting a set of development process metrics;

wherein said system further processes said set of development process with said predictive analysis engine.

3. The method of analyzing a computer software development project as set forth in claim 1, said method further comprising:

collecting a set of testing metrics;

wherein said system further processes said testing metrics with said predictive analysis engine.

4. The method of analyzing a computer software development project as set forth in claim 1 wherein said processing comprises using Bayesian inference.

5. The method of analyzing a computer software development project as set forth in claim 1 wherein said processing comprises using a support vector machine.

6. The method of analyzing a computer software development project as set forth in claim 1 wherein said processing comprises using Principle Component Regression.

7. The method of analyzing a computer software development project as set forth in claim 1 wherein said processing comprises using logistic regression.

8. The method of analyzing a computer software development project as set forth in claim 1 wherein said set of predictions describing the future development trajectory of said computer software development project comprise an internal bug rate.

9. The method of analyzing a computer software development project as set forth in claim 1 wherein said set of predictions describing the future development trajectory of said computer software development project comprise a customer found defect rate.

10. The method of analyzing a computer software development project as set forth in claim 1 wherein said set of predictions describing the future development trajectory of said computer software development project comprise an identification of high-risk source code sections.

11. The method of analyzing a computer software development project as set forth in claim 1, said method further comprising:

displaying a visual representation of said predictive analysis engine that indicates a relative importance of a set of input metrics.

12. The method of analyzing a computer software development project as set forth in claim 11 wherein said relative importance is displayed with color coding.

13. The method of analyzing a computer software development project as set forth in claim 1, said method further comprising:

displaying a visual representation of said predictive analysis engine that indicates a relative importance of said set of code complexity metrics and said set of code churn metrics.

14. The method of analyzing a computer software development project as set forth in claim 13 wherein said relative importance is displayed with color coding.

15. The method of analyzing a computer software development project as set forth in claim 1, said method further comprising:

processing said set of predictions describing the future development trajectory of said computer software development project with an expert system; and

outputting a set of software development recommendations from said expert system.

16. The method of analyzing a computer software development project as set forth in claim 1, said method further comprising:

reading said set of predictions describing the future development trajectory of said computer software development project with an integration layer; and

adjusting bug priority levels in a bug tracking system based on said set of predictions describing the future development trajectory of said computer software development project.

17. A computer readable medium, said computer-readable medium storing a set of computer instructions for analyzing a computer software development project, said computer instructions implementing the steps of:

constructing a statistical software development model from previous software development experience;

collecting a set of code complexity metrics, said set of code complexity metrics derived a plurality of source code files;

collecting a set of code churn metrics, said set of code complexity metrics derived from a source code control system;

tracking bugs discovered in said computer software development project;

processing said set of code complexity metrics, said set of code churn metrics, and said bugs with predictive analysis engine using said statistical software development; and

outputting a set of predictions describing the future development trajectory of said computer software development project.

18. The computer readable medium storing said set of computer instructions as set forth in claim 17, said computer instructions further implementing steps of:

collecting a set of development process metrics;

wherein said system further processes said set of development process with said predictive analysis engine.

19. The computer readable medium storing said set of computer instructions as set forth in claim 17 wherein said processing comprises using Principle Component Regression.

20. The computer readable medium storing said set of computer instructions as set forth in claim 17, said computer instructions further implementing steps of

processing said set of predictions describing the future development trajectory of said computer software development project with an expert system;

and

outputting a set of software development recommendations from said expert system.