%0 Report %D 2014 %T Pareto Efficient Multi-Objective Regression Test Suite Prioritisation %A Michael G. Epitropakis %A Shin Yoo %A Mark Harman %A Edmund K. Burke %X 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. %I Department of Computer Science, University College London %C Gower Street, London %P 1--16 %8 04/2014 %G eng