Using artificial bee colony for code coverage based test suite prioritization

© 2015 IEEE. The goal of test suite prioritization is maximizing fault detection and code coverage rate. Several nature inspired optimization algorithms such as Swarm Intelligence (SI) have been studied for the optimization of such problems. The studies revealed the benefits of Artificial Bee Colony...

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Main Authors: Konsaard P., Ramingwong L.
Format: Conference Proceeding
Published: 2017
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964680319&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42162
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Institution: Chiang Mai University
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spelling th-cmuir.6653943832-421622017-09-28T04:25:32Z Using artificial bee colony for code coverage based test suite prioritization Konsaard P. Ramingwong L. © 2015 IEEE. The goal of test suite prioritization is maximizing fault detection and code coverage rate. Several nature inspired optimization algorithms such as Swarm Intelligence (SI) have been studied for the optimization of such problems. The studies revealed the benefits of Artificial Bee Colony (ABC) over other algorithms. ABC and its variations were implemented in software testing areas, test suite prioritization in particular. However, most SI based approaches focus on fault detection ability which is difficult to predict. In this paper, the standard ABC algorithm is used to prioritize test suites based on code coverage. The results reveal that ABC shows promising results and, hence, is a great candidate for prioritizing test suites. It also suggests that a modification to the standard ABC algorithm or combination of ABC and another SI algorithm should yield an even better result. 2017-09-28T04:25:32Z 2017-09-28T04:25:32Z 2016-01-04 Conference Proceeding 2-s2.0-84964680319 10.1109/ICISSEC.2015.7371038 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964680319&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42162
institution Chiang Mai University
building Chiang Mai University Library
country Thailand
collection CMU Intellectual Repository
description © 2015 IEEE. The goal of test suite prioritization is maximizing fault detection and code coverage rate. Several nature inspired optimization algorithms such as Swarm Intelligence (SI) have been studied for the optimization of such problems. The studies revealed the benefits of Artificial Bee Colony (ABC) over other algorithms. ABC and its variations were implemented in software testing areas, test suite prioritization in particular. However, most SI based approaches focus on fault detection ability which is difficult to predict. In this paper, the standard ABC algorithm is used to prioritize test suites based on code coverage. The results reveal that ABC shows promising results and, hence, is a great candidate for prioritizing test suites. It also suggests that a modification to the standard ABC algorithm or combination of ABC and another SI algorithm should yield an even better result.
format Conference Proceeding
author Konsaard P.
Ramingwong L.
spellingShingle Konsaard P.
Ramingwong L.
Using artificial bee colony for code coverage based test suite prioritization
author_facet Konsaard P.
Ramingwong L.
author_sort Konsaard P.
title Using artificial bee colony for code coverage based test suite prioritization
title_short Using artificial bee colony for code coverage based test suite prioritization
title_full Using artificial bee colony for code coverage based test suite prioritization
title_fullStr Using artificial bee colony for code coverage based test suite prioritization
title_full_unstemmed Using artificial bee colony for code coverage based test suite prioritization
title_sort using artificial bee colony for code coverage based test suite prioritization
publishDate 2017
url https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84964680319&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/42162
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