RT Journal Article
T1 Parallel mutation testing for large scale systems
A1 Cerro Cañizares, Pablo
A1 Núñez Covarrubias, Alberto
A1 Filgueira, Rosa
A1 de Lara, Juan
AB Mutation testing is a valuable technique for measuring the quality of test suites in terms of detecting faults. However, one of its main drawbacks is its high computational cost. For this purpose, several approaches have been recently proposed to speed-up the mutation testing process by exploiting computational resources in distributed systems. However, bottlenecks have been detected when those techniques are applied in large-scale systems. This work improves the performance of mutation testing using large-scale systems by proposing a new load distribution algorithm, and parallelising different steps of the process. To demonstrate the benefits of our approach, we report on a thorough empirical evaluation, which analyses and compares our proposal with existing solutions executed in large-scale systems. The results show that our proposal outperforms the state-of-the-art distribution algorithms up to 35% in three different scenarios, reaching a reduction of the execution time of—at best—up to 99.66%.
PB Springer
YR 2023
FD 2023-06-20
LK https://hdl.handle.net/20.500.14352/105660
UL https://hdl.handle.net/20.500.14352/105660
LA eng
NO Proyectos del MINECO/FEDER con referencias PID2021-122270OB-I00, TED2021-129381B-C21 y PID2019-108528RB-C22
NO Proyecto de la Comunidad de Madrid "FORTE-CM" con referencia S2018/TCS-4314
NO Proyecto "BLOQUES-CM", con referencia S2018/TCS-4339, cofinanciado por los Fondos EIE de la Unión Europea y la Comunidad de Madrid
NO Proyecto de HPC-EUROPA3 (referencia INFRAIA-2016-1-730897), con el apoyo de la Acción de Investigación e Innovación de la CE en el marco del Programa H2020
DS Docta Complutense
RD 19 abr 2025