NDLI: Generating a Test Strategy with Bayesian Networks and Common Sense

Content Provider	IEEE Xplore Digital Library
Author	Gras, J.-J. Rishabh Gupta Perez-Minana, E.
Copyright Year	2006
Abstract	Testing still represents an important share of the overall development effort and, coming late in the software life cycle, it is on the critical path both from a schedule and quality perspective. In an effort to conduct smarter software testing, Motorola Labs have developed the Bayesian test assistant (BTA), an advanced decision support tool to optimize all verification and validation activities, in development and system testing. With Bayesian networks, the theory underlying BTA, Motorola Labs built a library of causal models to predict, from key process, people and product factors, the quality of artefacts at each step of the software development. In this paper we present how BTA links the predictions from development models by mapping dependencies between components or subsystems to predict the level of risk in each system feature. As a result, and well before system testing starts, BTA generates a test strategy that optimizes the writing of test cases. During system test, BTA scores test cases to select an optimum set for each test step, leading to a faster discovery of defects. We also describe how BTA was deployed on large telecomm system releases in several Motorola organizations and the improvement driven so far in system testing
Sponsorship	IEEE CPS
Starting Page	29
Ending Page	40
File Size	492215
Page Count	12
File Format	PDF
ISBN	0769526721
DOI	10.1109/TAIC-PART.2006.10
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-29
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Software testing System testing defect prediction. software testing Life testing Bayesian Predictive models Programming Scheduling networks Software libraries Bayesian methods Software quality test strategy Writing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Libarray of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

A critique of software defect prediction models

A Bayesian approach for software quality prediction

Bayesian analysis of software cost and quality models

Research on software defect prediction based on data mining

Release date prediction for telecommunication software using Bayesian Belief Networks

Research of Software Defect Prediction Model Based on Gray Theory

Software defect prediction using Bayesian networks

Bayesian analysis of empirical software engineering cost models

On prediction of defect rates

Generating a Test Strategy with Bayesian Networks and Common Sense

Similar Documents

A critique of software defect prediction models

A Bayesian approach for software quality prediction

Bayesian analysis of software cost and quality models

Research on software defect prediction based on data mining

Release date prediction for telecommunication software using Bayesian Belief Networks

Research of Software Defect Prediction Model Based on Gray Theory

Software defect prediction using Bayesian networks

Bayesian analysis of empirical software engineering cost models

On prediction of defect rates

Generating a Test Strategy with Bayesian Networks and Common Sense