Coverage-Based Clustering and Scheduling Approach for Test Case Prioritization

Wenhao FU; Huiqun YU; Guisheng FAN; Xiang JI

doi:10.1587/transinf.2016EDP7356

Coverage-Based Clustering and Scheduling Approach for Test Case Prioritization

Wenhao FU, Huiqun YU, Guisheng FAN, Xiang JI

Full Text Views

0

Share
Cite this

Summary :

Regression testing is essential for assuring the quality of a software product. Because rerunning all test cases in regression testing may be impractical under limited resources, test case prioritization is a feasible solution to optimize regression testing by reordering test cases for the current testing version. In this paper, we propose a novel test case prioritization approach that combines the clustering algorithm and the scheduling algorithm for improving the effectiveness of regression testing. By using the clustering algorithm, test cases with same or similar properties are merged into a cluster, and the scheduling algorithm helps allocate an execution priority for each test case by incorporating fault detection rates with the waiting time of test cases in candidate set. We have conducted several experiments on 12 C programs to validate the effectiveness of our proposed approach. Experimental results show that our approach is more effective than some well studied test case prioritization techniques in terms of average percentage of fault detected (APFD) values.

Publication: IEICE TRANSACTIONS on Information Vol.E100-D No.6 pp.1218-1230

Publication Date: 2017/06/01

Publicized: 2017/03/03

Online ISSN: 1745-1361

DOI: 10.1587/transinf.2016EDP7356

Type of Manuscript: PAPER

Category: Software Engineering

Authors

Wenhao FU
  East China University of Science and Technology
Huiqun YU
  East China University of Science and Technology
Guisheng FAN
  East China University of Science and Technology
Xiang JI
  East China University of Science and Technology

Keyword

regression testing, test case prioritization, clustering algorithm, scheduling algorithm

Cite this

Copy

Wenhao FU, Huiqun YU, Guisheng FAN, Xiang JI, "Coverage-Based Clustering and Scheduling Approach for Test Case Prioritization" in IEICE TRANSACTIONS on Information, vol. E100-D, no. 6, pp. 1218-1230, June 2017, doi: 10.1587/transinf.2016EDP7356.
Abstract: Regression testing is essential for assuring the quality of a software product. Because rerunning all test cases in regression testing may be impractical under limited resources, test case prioritization is a feasible solution to optimize regression testing by reordering test cases for the current testing version. In this paper, we propose a novel test case prioritization approach that combines the clustering algorithm and the scheduling algorithm for improving the effectiveness of regression testing. By using the clustering algorithm, test cases with same or similar properties are merged into a cluster, and the scheduling algorithm helps allocate an execution priority for each test case by incorporating fault detection rates with the waiting time of test cases in candidate set. We have conducted several experiments on 12 C programs to validate the effectiveness of our proposed approach. Experimental results show that our approach is more effective than some well studied test case prioritization techniques in terms of average percentage of fault detected (APFD) values.
URL: https://globals.ieice.org/en_transactions/information/10.1587/transinf.2016EDP7356/_p

Copy

@ARTICLE{e100-d_6_1218,
author={Wenhao FU, Huiqun YU, Guisheng FAN, Xiang JI, },
journal={IEICE TRANSACTIONS on Information},
title={Coverage-Based Clustering and Scheduling Approach for Test Case Prioritization},
year={2017},
volume={E100-D},
number={6},
pages={1218-1230},
abstract={Regression testing is essential for assuring the quality of a software product. Because rerunning all test cases in regression testing may be impractical under limited resources, test case prioritization is a feasible solution to optimize regression testing by reordering test cases for the current testing version. In this paper, we propose a novel test case prioritization approach that combines the clustering algorithm and the scheduling algorithm for improving the effectiveness of regression testing. By using the clustering algorithm, test cases with same or similar properties are merged into a cluster, and the scheduling algorithm helps allocate an execution priority for each test case by incorporating fault detection rates with the waiting time of test cases in candidate set. We have conducted several experiments on 12 C programs to validate the effectiveness of our proposed approach. Experimental results show that our approach is more effective than some well studied test case prioritization techniques in terms of average percentage of fault detected (APFD) values.},
keywords={},
doi={10.1587/transinf.2016EDP7356},
ISSN={1745-1361},
month={June},}

Copy

TY - JOUR
TI - Coverage-Based Clustering and Scheduling Approach for Test Case Prioritization
T2 - IEICE TRANSACTIONS on Information
SP - 1218
EP - 1230
AU - Wenhao FU
AU - Huiqun YU
AU - Guisheng FAN
AU - Xiang JI
PY - 2017
DO - 10.1587/transinf.2016EDP7356
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E100-D
IS - 6
JA - IEICE TRANSACTIONS on Information
Y1 - June 2017
AB - Regression testing is essential for assuring the quality of a software product. Because rerunning all test cases in regression testing may be impractical under limited resources, test case prioritization is a feasible solution to optimize regression testing by reordering test cases for the current testing version. In this paper, we propose a novel test case prioritization approach that combines the clustering algorithm and the scheduling algorithm for improving the effectiveness of regression testing. By using the clustering algorithm, test cases with same or similar properties are merged into a cluster, and the scheduling algorithm helps allocate an execution priority for each test case by incorporating fault detection rates with the waiting time of test cases in candidate set. We have conducted several experiments on 12 C programs to validate the effectiveness of our proposed approach. Experimental results show that our approach is more effective than some well studied test case prioritization techniques in terms of average percentage of fault detected (APFD) values.
ER -