TY - GEN
T1 - One size does not fit all
T2 - 5th International Conference in Software Engineering Research and Innovation, CONISOFT 2017
AU - Ayala-Rivera, Vanessa
AU - Kaczmarski, Maciej
AU - Murphy, John
AU - Darisa, Amarendra
AU - Portillo-Dominguez, A. Omar
N1 - Publisher Copyright:
© 2018 Association for Computing Machinery.
PY - 2018/3/30
Y1 - 2018/3/30
N2 - The identification of workload-dependent performance issues, as well as their root causes, is a time-consuming and complex process which typically requires several iterations of tests (as this type of issues can depend on the input workloads), and heavily relies on human expert knowledge. To improve this process, this paper presents an automated approach to dynamically adapt the workload (used by a performance testing tool) during the test runs. As a result, the performance issues of the tested application can be revealed more quickly; hence, identifying them with less effort and expertise. Our experimental evaluation has assessed the accuracy of the proposed approach and the time savings that it brings to testers. The results have demonstrated the benefits of the approach by achieving a significant decrease in the time invested in performance testing (without compromising the accuracy of the test results), while introducing a low overhead in the testing environment.
AB - The identification of workload-dependent performance issues, as well as their root causes, is a time-consuming and complex process which typically requires several iterations of tests (as this type of issues can depend on the input workloads), and heavily relies on human expert knowledge. To improve this process, this paper presents an automated approach to dynamically adapt the workload (used by a performance testing tool) during the test runs. As a result, the performance issues of the tested application can be revealed more quickly; hence, identifying them with less effort and expertise. Our experimental evaluation has assessed the accuracy of the proposed approach and the time savings that it brings to testers. The results have demonstrated the benefits of the approach by achieving a significant decrease in the time invested in performance testing (without compromising the accuracy of the test results), while introducing a low overhead in the testing environment.
KW - Analysis
KW - Automation
KW - Performance
KW - Testing
KW - Workload
UR - https://www.scopus.com/pages/publications/85051113822
U2 - 10.1145/3184407.3184418
DO - 10.1145/3184407.3184418
M3 - Conference contribution
AN - SCOPUS:85051113822
T3 - ICPE 2018 - Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering
SP - 211
EP - 222
BT - ICPE 2018 - Proceedings of the 2018 ACM/SPEC International Conference on Performance Engineering
PB - Association for Computing Machinery (ACM)
Y2 - 25 October 2017 through 27 October 2017
ER -