TY - GEN
T1 - On the fault-detection capabilities of adaptive random test case prioritization
T2 - 2012 45th Hawaii International Conference on System Sciences, HICSS 2012
AU - Zhou, Zhi Quan
AU - Sinaga, Arnaldo
AU - Susilo, Willy
PY - 2012
Y1 - 2012
N2 - An adaptive random (AR) testing strategy has recently been developed and examined by a growing body of research. More recently, this strategy has been applied to prioritizing regression test cases based on code coverage using the concepts of Jaccard Distance (JD) and Coverage Manhattan Distance (CMD). Code coverage, however, does not consider frequency; furthermore, comparison between JD and CMD has not yet been made. This research fills the gap by first investigating the fault-detection capabilities of using frequency information for AR test case prioritization, and then comparing JD and CMD. Experimental results show that "coverage" was more useful than " frequency" although the latter can sometimes complement the former, and that CMD was superior to JD. It is also found that, for certain faults, the conventional "additional" algorithm (widely accepted as one of the best algorithms for test case prioritization) could perform much worse than random testing on large test suites.
AB - An adaptive random (AR) testing strategy has recently been developed and examined by a growing body of research. More recently, this strategy has been applied to prioritizing regression test cases based on code coverage using the concepts of Jaccard Distance (JD) and Coverage Manhattan Distance (CMD). Code coverage, however, does not consider frequency; furthermore, comparison between JD and CMD has not yet been made. This research fills the gap by first investigating the fault-detection capabilities of using frequency information for AR test case prioritization, and then comparing JD and CMD. Experimental results show that "coverage" was more useful than " frequency" although the latter can sometimes complement the former, and that CMD was superior to JD. It is also found that, for certain faults, the conventional "additional" algorithm (widely accepted as one of the best algorithms for test case prioritization) could perform much worse than random testing on large test suites.
UR - https://www.scopus.com/pages/publications/84863263726
U2 - 10.1109/HICSS.2012.454
DO - 10.1109/HICSS.2012.454
M3 - Conference contribution
AN - SCOPUS:84863263726
SN - 9780769545257
T3 - Proceedings of the Annual Hawaii International Conference on System Sciences
SP - 5584
EP - 5593
BT - Proceedings of the 45th Annual Hawaii International Conference on System Sciences, HICSS-45
PB - IEEE Computer Society
Y2 - 4 January 2012 through 7 January 2012
ER -