NDLI: Automated Regression Test Suite Optimization Based on Heuristics

Content Provider	IEEE Xplore Digital Library
Author	Prasad, D.S.U.M. Chacko, S. Kanakadandi, S.S.P. Durbhaka, G.K.
Copyright Year	2014
Description	Author affiliation: HCL Technol., Noida, India (Prasad, D.S.U.M.; Chacko, S.; Kanakadandi, S.S.P.; Durbhaka, G.K.)
Abstract	In the Software Development Life Cycle, Testing is an integral and important phase. It is estimated that close to 45% of project cost is marked for testing. Defect removal efficiency is directly proportional to the rigor of the testing and number of test cycles. Given this prelude, important optimization dual is to reduce the testing time and cost without compromising on the quality and coverage. We revisit this popular research and industry sought problem, in the historical data perspective. Proposed model has two steps. N Test cases based on multiple heuristics are recommended as part of first step. These heuristics can be derived based on test manager, test lead and/or test director requirements as inputs. The N test cases that are to be recommended will be derived upon executing evolutionary randomized algorithms such as Random Forest / Genetic Algorithm. These algorithms fed with historically derived inputs such as test case execution frequency, test case failure pattern, change feature pattern and bug fixes & associations. The recommended test suite is further optimized based on a 2 dimensional approach during second step. Test case specific vertical constraints such as distribution of environments, distribution of features as well as test suite composition parameters such as golden test cases, sanity test cases, that serves as horizontal constraints.
Starting Page	48
Ending Page	53
File Size	148952
Page Count	6
File Format	PDF
e-ISBN	9781479979103
DOI	10.1109/ICAIET.2014.18
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-12-03
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Radio frequency Sociology Vegetation Predictive models Test coverage; Regression Test Suite; Random Forest; Test failure prediction; Optimisation; Greedy Algorithm Statistics Testing Genetic algorithms
Content Type	Text
Resource Type	Article

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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
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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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