.png){kind=icon}
返回
Test suite reduction methods that decrease regression testing costs by identifying irreplaceable tests
.png){kind=icon}
PRE
AI
DOI：10.1016/j.infsof.2014.04.013.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
Context: In software development and maintenance, a software system may frequently be updated to meet rapidly changing user requirements. New test cases will be designed to ensure the correctness of new or modified functions, thus gradually increasing the test suite's size. Test suite reduction techniques aim to decrease the cost of regression testing by removing the redundant test cases from the test suite and then obtaining a representative set of test cases that still yield a high level of code coverage. Objective: Most of the existing reduction algorithms focus on decreasing the test suite's size. Yet, the differences in execution costs among test cases are usually significant and it may take a lot of execution time to run a test suite consisting of a few long-running test cases. This paper presents and empirically evaluates cost-aware algorithms that can produce the representative sets with lower execution costs. Method: We first use a cost-aware test case metric, called Irreplaceability, and its enhanced version, called Elrreplaceability, to evaluate the possibility that each test case can be replaced by others during test suite reduction. Furthermore, we construct a cost-aware framework that incorporates the concept of test irreplaceability into some well-known test suite reduction algorithms. Results: The effectiveness of the cost-aware framework is evaluated via the subject programs and test suites collected from the Software-artifact Infrastructure Repository - frequently chosen benchmarks for experimentally evaluating test suite reduction methods. The empirical results reveal that the presented algorithms produce representative sets that normally incur a low cost to yield a high level of test coverage. Conclusion: The presented techniques indeed enhance the capability of the traditional reduction algorithms to reduce the execution cost of a test suite. Especially for the additional Greedy algorithm, the presented techniques decrease the costs of the representative sets by 8.10-46.57%. (C) 2014 Elsevier B.V. All rights reserved.
Keyword:
Software testing
Regression testing
Test suite reduction
Code coverage
Test irreplaceability
期刊
IF:
4.3
论文数:
3.8K
被引数:
7.7K
机构
引用论文
Microscale forced combustion: Pyrolysis-combustion flow calorimetry (PCFC)微尺度强制燃烧: 热解-燃烧流量量热法 (PCFC)
.png){kind=icon}
PREAI
分享收藏
分享收藏分享收藏Test-suite reduction and prioritization for modified condition/decision coverage减少测试套件并确定修改条件/决策覆盖的优先级
PREAI
分享收藏
查看更多内容