<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>27</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Michael G. Epitropakis</style></author><author><style face="normal" font="default" size="100%">Shin Yoo</style></author><author><style face="normal" font="default" size="100%">Mark Harman</style></author><author><style face="normal" font="default" size="100%">Edmund K. Burke</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Pareto Efficient Multi-Objective Regression Test Suite Prioritisation</style></title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2014</style></date></pub-dates></dates><publisher><style face="normal" font="default" size="100%">Department of Computer Science, University College London</style></publisher><pub-location><style face="normal" font="default" size="100%">Gower Street, London</style></pub-location><pages><style face="normal" font="default" size="100%">1--16</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Test suite prioritisation seeks a test case ordering that maximises the likelihood of early fault revelation. Previous prioritisation techniques have tended to be single objective, for which the additional greedy algorithm is the current state-of-the-art. We study multi objective test suite prioritisation, evaluating it on multiple versions of five widely-used benchmark programs and a much larger real world system of over 1MLoC. Our multi objective algorithms find faults significantly faster and with large effect size for 20 of the 22 versions. We also introduce a non-lossy coverage compact algorithm that dramatically scales the performance of all algorithms studied by between 2 and 4 orders of magnitude, making prioritisation practical for even very demanding problems.</style></abstract></record></records></xml>