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System And Method For Optimizing The Risk During Software Production Release

Abstract: A system and method for optimizing risk during software production release are disclosed. The method includes may involve receiving, one or more project requirements associated with the software project and one or more project defects associated with the software project; identifying, one or more critical project requirements and one or more critical project defects from the one or more project requirements and the one or more project defects; ascertaining, a requirement density for the software project based on the one or more critical project requirements and the one or more project requirements; ascertaining, a defect density based on the one or more critical project defects and the one or more project defects; and determining a cumulative risk score for the software project using the requirement density and the defect density. Fig 1

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Notices, Deadlines & Correspondence

Patent Information

Application #
Filing Date
10 February 2015
Publication Number
09/2015
Publication Type
INA
Invention Field
COMPUTER SCIENCE
Status
Email
ipo@knspartners.com
Parent Application

Applicants

WIPRO LIMITED
Doddakannelli, Sarjapur Road, Bangalore 560035, Karnataka, India.

Inventors

1. DEEPA NATARAJAN
No.4, “Rohit’s Pramodam”, Castle Valley, Vengadamangalam Main Road, Ponmar, Chennai 600127, Tamil Nadu, India.
2. SUMITHRA SUNDARESAN
158, 15th Street, Shankar Nagar, Pammal, Chennai 600075, Tamil Nadu, India.

Specification

CLIAMS:We claim:
1. A method for determining risk associated with a software project, the method comprising:
receiving, by a risk determination engine, one or more project requirements associated with the software project and one or more project defects associated with the software project;
identifying, by the risk determination engine, one or more critical project requirements and one or more critical project defects from the one or more project requirements and the one or more project defects;
ascertaining, by the risk determination engine, a requirement density for the software project based on the one or more critical project requirements and the one or more project requirements;
ascertaining, by the risk determination engine, a defect density based on the one or more critical project defects and the one or more project defects; and
determining, by the risk determination engine, a cumulative risk score for the software project using the requirement density and the defect density.

2. The method of claim 1, wherein the one or more project requirements and the one or more project defects are received from at least one of a test management tool and a user.

3. The method of claim 1, wherein the one or more critical project requirements are identified based on a predefined weightage assigned to the one or more project requirements.

4. The method of claim 1, wherein the one or more critical project defects are identified based on a predefined weightage assigned to the one or more project defects.

5. The method of claim 1, wherein the requirement density is ascertained as a product of the one or more project requirements and the one or more critical project requirements divided by a summation of the one or more project requirements and the one or more critical project requirements.

6. The method of claim 1, wherein the defect density is ascertained as a product of the one or more project defects and the one or more critical project defects divided by a summation of the one or more project defects and the one or more critical project defects.

7. The method of claim 1, wherein the cumulative risk score is determined as a product of the requirement density and the defect density divided by a summation the requirement density and the defect density.

8. The method of claim 1, wherein the software project is prioritized for optimizing risk based on the cumulative risk score.

9. A risk determination engine to determine risk associated with a software project comprising:

a memory;
a processor coupled to the memory storing processor executable instructions which when executed by the processor causes the processor to:
receive one or more project requirements associated with the software project and one or more project defects associated with the software project;
identify one or more critical project requirements and one or more critical project defects from the one or more project requirements and the one or more project defects;
ascertain a requirement density for the software project based on the one or more critical project requirements and the one or more project requirements;
ascertain a defect density based on the one or more critical project defects and the one or more project defects; and
determine a cumulative risk score for the software project using the requirement density and the defect density.

10. The risk determination engine of claim 9, wherein the one or more project requirements and the one or more project defects are received from at least one of a test management tool and a user.

11. The risk determination engine of claim 9, wherein the one or more critical project requirements are identified based on a predefined weightage assigned to the one or more project requirements.

12. The risk determination engine of claim 9, wherein the one or more critical project defects are identified based on a predefined weightage assigned to the one or more project defects.

13. The risk determination engine of claim 9, wherein the requirement density is ascertained as a product of the one or more project requirements and the one or more critical project requirements divided by a summation of the one or more project requirements and the one or more critical project requirements.

14. The risk determination engine of claim 9, wherein the defect density is ascertained as a product of the one or more project defects and the one or more critical project defects divided by a summation of the one or more project defects and the one or more critical project defects.

15. The risk determination engine of claim 9, wherein the cumulative risk score is determined as a product of the requirement density and the defect density divided by a summation the requirement density and the defect density.

16. The risk determination engine of claim 9, wherein the software project is prioritized for optimizing risk based on the cumulative risk score

17. A computer readable medium including executable instructions to :

receive one or more project requirements associated with the software project and one or more project defects associated with the software project;
identify one or more critical project requirements and one or more critical project defects from the one or more project requirements and the one or more project defects;
ascertain a requirement density for the software project based on the one or more critical project requirements and the one or more project requirements;
ascertain a defect density based on the one or more critical project defects and the one or more project defects; and
determine a cumulative risk score for the software project using the requirement density and the defect density.

Dated this 10th day of February 2015

Shwetha A Chimalgi
Of K&S Partners
Agent for the Applicant
,TagSPECI:TECHNICAL FIELD
This disclosure relates generally to a software production release, and more particularly to a system and method for optimizing risk during software production release.

Documents

Application Documents

# Name Date
1 655-CHE-2015 FORM-9 10-02-2015.pdf 2015-02-10
2 655-CHE-2015 FORM-18 10-02-2015.pdf 2015-02-10
3 655-CHE-2015-Request For Certified Copy-Online(12-02-2015).pdf 2015-02-12
4 655CHE2015_CertifiedCopyRequest.pdf ONLINE 2015-02-13
5 abstract 655-CHE-2015.jpg 2015-02-16
6 IP30079-spec.pdf 2015-03-12
7 IP30079-FIG.pdf 2015-03-12
8 FORM 5-IP30079.pdf 2015-03-12
9 FORM 3-IP30079.pdf 2015-03-12
10 655CHE2015_CertifiedCopyRequest.pdf 2015-03-13
11 655-CHE-2015 POWER OF ATTORNEY 16-06-2015.pdf 2015-06-16
12 655-CHE-2015 FORM-1 16-06-2015.pdf 2015-06-16
13 655-CHE-2015 CORRESPONDENCE OTHERS 16-06-2015.pdf 2015-06-16
14 655-CHE-2015-FER.pdf 2019-10-10

Search Strategy

1 RISKOptimisation-SS_20-09-2019.pdf