TY - GEN
T1 - Hypervolume-based search for test case prioritization
AU - Di Nucci, Dario
AU - Panichella, Annibale
AU - Zaidman, Andy
AU - De Lucia, Andrea
PY - 2015/1/1
Y1 - 2015/1/1
N2 - Test case prioritization (TCP) is aimed at finding an ideal ordering for executing the available test cases to reveal faults earlier. To solve this problem greedy algorithms and meta-heuristics have been widely investigated, but in most cases there is no statistically significant difference between them in terms of effectiveness. The fitness function used to guide meta-heuristics condenses the cumulative coverage scores achieved by a test case ordering using the Area Under Curve (AUC) metric. In this paper we notice that the AUC metric represents a simplified version of the hypervolume metric used in many objective optimization and we propose HGA, a Hypervolume-based Genetic Algorithm, to solve the TCP problem when using multiple test criteria. The results shows that HGA is more cost-effective than the additional greedy algorithm on large systems and on average requires 36% of the execution time required by the additional greedy algorithm.
AB - Test case prioritization (TCP) is aimed at finding an ideal ordering for executing the available test cases to reveal faults earlier. To solve this problem greedy algorithms and meta-heuristics have been widely investigated, but in most cases there is no statistically significant difference between them in terms of effectiveness. The fitness function used to guide meta-heuristics condenses the cumulative coverage scores achieved by a test case ordering using the Area Under Curve (AUC) metric. In this paper we notice that the AUC metric represents a simplified version of the hypervolume metric used in many objective optimization and we propose HGA, a Hypervolume-based Genetic Algorithm, to solve the TCP problem when using multiple test criteria. The results shows that HGA is more cost-effective than the additional greedy algorithm on large systems and on average requires 36% of the execution time required by the additional greedy algorithm.
KW - Genetic algorithm
KW - Hypervolume
KW - Test case prioritization
UR - http://www.scopus.com/inward/record.url?scp=84951286528&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-22183-0_11
DO - 10.1007/978-3-319-22183-0_11
M3 - Conference contribution
AN - SCOPUS:84951286528
SN - 9783319221823
VL - 9275
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 157
EP - 172
BT - Search-Based Software Engineering - 7th International Symposium, SSBSE 2015, Proceedings
PB - Springer
T2 - 7th International Symposium on Search-Based Software Engineering, SSBSE 2015
Y2 - 5 September 2015 through 7 September 2015
ER -