Regression testing in the presence of non-code changes

Nanda, Agastya; Mani, Senthil; Sinha, Saurabh; Harrold, Mary Jean; Orso, Alessandro

doi:10.1109/icst.2011.60

Cited by 38 publications

(26 citation statements)

References 23 publications

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“…The size of Regression Test Suites is reduced by the Minimization Technique depending on the objective functions [2]. Test Cases are ranked or prioritized in the Prioritization Technique to achieve required goals, for example to detect faults earlier [6]; whereas a Regression Test Suite is selected based on the modified portions of the software in the Selection Techniques of Regression Testing [9]. Researchers have used the minimization, selection and prioritization techniques [6][7] …”

Section: Techniques For Rtomentioning

confidence: 99%

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Exploration and analysis of regression test suite optimization

Anwar¹,

Ahsan²

2014

SIGSOFT Softw. Eng. Notes

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Regression Test Suite Optimization (RTO) is an active research area. A Regression Test Suite is always growing due to changes in software, which increases testing time. To save time and resources optimization of regression test suites is mandatory. Researchers have optimized test suites using conventional and Computational Intelligence based approaches and achieve optimization of regression test suites through selection techniques, minimization or reduction techniques and ranking or prioritization techniques. This paper surveys existing techniques for regression test suite optimization, various tools and mathematical models being used for RTO. During this survey we found many interesting facts about regression test suite optimization that will be shared in the conclusion.

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Section: Techniques For Rtomentioning

confidence: 99%

“…Brief descriptions of various heuristic approaches are given in Table 1. Regression Test Suite Optimization using minimization techniques of regression testing [6,9,[12][13][14][15][16][17][18][19] and are given in Table 2. Test suite size is reduced, this technique is safe up to step 5 after this step it becomes unsafe.…”

Section: Heuristic Approaches For Rtomentioning

confidence: 99%

Exploration and analysis of regression test suite optimization

Anwar¹,

Ahsan²

2014

SIGSOFT Softw. Eng. Notes

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“…In Fuzzy Logic optimization objectives are represented in the form of input variables that were selected after literature reviews [12,17,[19][20][21][22] and discussion with software testing experts. Details and calculation of these variables are as follow:…”

Section: B Input Variablesmentioning

confidence: 99%

Multi-objective regression test suite optimization with Fuzzy logic

Anwar¹,

Ahsan²

2013

Inmic

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Regression Testing is performed on already tested programs to ensure that modifications have not revealed defects into the unmodified portions of programs. Regression Test Suites are always growing due to addition of Test Cases. Many broken and redundant test cases are also part of regression test suites. Running the all regression test suite is always not feasible; therefore optimization of regression test suites is required to meet the constraints. In this work we proposed multi-objective optimization of regression test suites with Fuzzy Logic (Sugeno Model) for Black Box based testing methods. Proposed approach was implemented on two published case studies. Results indicates that optimization can be achieved by using Fuzzy Logic that is a safe technique for optimization and we can reduce the execution time and size of regression test suites up to 50%.

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“…However, regression testing is costly as it runs a large number of tests. Some studies [13,15,21,38,43] estimate that regression testing can take up to 80% of the testing budget and up to 50% of the software maintenance cost. The cost of regression testing increases as software grows.…”

Section: Introductionmentioning

confidence: 99%

Practical regression test selection with dynamic file dependencies

Gligoric

Eloussi

Marinov

2015

Proceedings of the 2015 International Symposium on Software Testing and Analysis

174

158

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Regression testing is important but can be time-intensive. One approach to speed it up is regression test selection (RTS), which runs only a subset of tests. RTS was proposed over three decades ago but has not been widely adopted in practice. Meanwhile, testing frameworks, such as JUnit, are widely adopted and well integrated with many popular build systems. Hence, integrating RTS in a testing framework already used by many projects would increase the likelihood that RTS is adopted.We propose a new, lightweight RTS technique, called Ekstazi, that can integrate well with testing frameworks. Ekstazi tracks dynamic dependencies of tests on files, and unlike most prior RTS techniques, Ekstazi requires no integration with version-control systems. We implemented Ekstazi for Java and JUnit, and evaluated it on 615 revisions of 32 open-source projects (totaling almost 5M LOC) with shorter-and longer-running test suites. The results show that Ekstazi reduced the end-to-end testing time 32% on average, and 54% for longer-running test suites, compared to executing all tests. Ekstazi also has lower end-to-end time than the existing techniques, despite the fact that it selects more tests. Ekstazi has been adopted by several popular open source projects, including Apache Camel, Apache Commons Math, and Apache CXF.

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Regression testing in the presence of non-code changes

Cited by 38 publications

References 23 publications

Exploration and analysis of regression test suite optimization

Exploration and analysis of regression test suite optimization

Multi-objective regression test suite optimization with Fuzzy logic

Practical regression test selection with dynamic file dependencies

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