State of Practical Applicability of Regression Testing Research: A Live Systematic Literature Review

被引:8
作者
Greca, Renan [1 ,2 ]
Miranda, Breno
Bertolino, Antonia [2 ,3 ]
机构
[1] Gran Sasso Sci Inst, Laquila, Italy
[2] CNR, ISTI, Pisa, Italy
[3] Univ Fed Pernambuco, Recife, PE, Brazil
关键词
Regression Testing; test case selection; test case prioritization; test suite reduction; test suite amplification; systematic literature review; TEST-CASE PRIORITIZATION; TEST SELECTION; INDUSTRIAL;
D O I
10.1145/3579851
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Context: Software regression testing refers to rerunning test cases after the system under test is modified, ascertaining that the changes have not (re-)introduced failures. Not all researchers' approaches consider applicability and scalability concerns, and not many have produced an impact in practice. Objective: One goal is to investigate industrial relevance and applicability of proposed approaches. Another is providing a live review, open to continuous updates by the community. Method: A systematic review of regression testing studies that are clearly motivated by or validated against industrial relevance and applicability is conducted. It is complemented by follow-up surveys with authors of the selected papers and 23 practitioners. Results: A set of 79 primary studies published between 2016-2022 is collected and classified according to approaches and metrics. Aspects relative to their relevance and impact are discussed, also based on their authors' feedback. All the data are made available from the live repository that accompanies the study. Conclusions: While widely motivated by industrial relevance and applicability, not many approaches are evaluated in industrial or large-scale open-source systems, and even fewer approaches have been adopted in practice. Some challenges hindering the implementation of relevant approaches are synthesized, also based on the practitioners' feedback.
引用
收藏
页数:36
相关论文
共 130 条
[1]   TCP-Net: Test Case Prioritization using End-to-End Deep Neural Networks [J].
Abdelkarim, Mohamed ;
ElAdawi, Reem .
2022 IEEE 15TH INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS (ICSTW 2022), 2022, :122-129
[2]   Value-based cost-cognizant test case prioritization for regression testing [J].
Ahmed, Farrukh Shahzad ;
Majeed, Awais ;
Khan, Tamim Ahmed ;
Bhatti, Shahid Nazir .
PLOS ONE, 2022, 17 (05)
[3]   Application of Mahalanobis-Taguchi Method and 0-1 Programming Method to Cost-Effective Regression Testing [J].
Aman, Hirohisa ;
Tanaka, Yuta ;
Nakano, Takashi ;
Ogasawara, Hideto ;
Kawahara, Minoru .
2016 42ND EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA), 2016, :240-244
[4]   ReTEST: A Cost Effective Test Case Selection Technique for Modern Software Development [J].
Azizi, Maral ;
Do, Hyunsook .
2018 29TH IEEE INTERNATIONAL SYMPOSIUM ON SOFTWARE RELIABILITY ENGINEERING (ISSRE), 2018, :144-154
[5]   Coverage-Based Reduction of Test Execution Time: Lessons from a Very Large Industrial Project [J].
Bach, Thomas ;
Andrzejak, Artur ;
Pannemans, Ralf .
10TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE TESTING, VERIFICATION AND VALIDATION WORKSHOPS - ICSTW 2017, 2017, :3-12
[6]   Reinforcement Learning for Test Case Prioritization [J].
Bagherzadeh, Mojtaba ;
Kahani, Nafiseh ;
Briand, Lionel .
IEEE TRANSACTIONS ON SOFTWARE ENGINEERING, 2022, 48 (08) :2836-2856
[7]  
Bajaj A., 2019, P 4 INT C COMP COMM, P1, DOI DOI 10.1109/CCAA.2018.8777692
[8]   A Systematic Literature Review of Test Case Prioritization Using Genetic Algorithms [J].
Bajaj, Anu ;
Sangwan, Om Prakash .
IEEE ACCESS, 2019, 7 :126355-126375
[9]   Resurgence of Regression Test Selection for C plus [J].
Fu, Ben ;
Misailovic, Sasa ;
Gligoric, Milos .
2019 IEEE 12TH CONFERENCE ON SOFTWARE TESTING, VALIDATION AND VERIFICATION (ICST 2019), 2019, :323-334
[10]   Learning-to-Rank vs Ranking-to-Learn: Strategies for Regression Testing in Continuous Integration [J].
Bertolino, Antonia ;
Guerriero, Antonio ;
Miranda, Breno ;
Pietrantuono, Roberto ;
Russo, Stefano .
2020 ACM/IEEE 42ND INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING (ICSE 2020), 2020, :1-12