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Procedia Computer Science
Article . 2016
License: CC BY NC ND
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Optimized Regression Test Using Test Case Prioritization

Authors: Ansari, Ahlam; Khan, Anam; Khan, Alisha; Mukadam, Konain;

Optimized Regression Test Using Test Case Prioritization

Abstract

AbstractRegression testing ensures that changes made in the fixes or any enhancement changes do not impact the previously working functionality. Whenever software is modified, a set of test cases are run to assure that changes don’t affect the other parts of the software. Hence all existing test cases need to be tested as well as new test cases need to be created. It is nonviable to re-execute every test case for a given software, because if there are more number of test cases to be tested, the more effort and time is required. This problem can be solved by prioritizing test cases. Test case prioritization techniques reorder the priority of a test case in an attempt to ensure that maximum faults are uncovered by the high prioritized test cases. In this paper we propose an optimized test case prioritization technique using Ant Colony Optimization (ACO) to reduce the cost, effort and time taken to perform regression testing and also uncover maximum faults.

Keywords

Ant colony optimization, Test case prioritization, Regression testing

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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
30
Top 10%
Top 10%
Top 10%
gold