Research of Optimization Algorithm for Path-Based Regression Testing Suit

Jiang, Bing; Mu, Yongmin; Zhang, Zhihua

doi:10.1109/etcs.2010.365

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…The method reduced the regression cost and scalability for test sequence optimization. Jiang et al [9] defined the change point based minimum set formation for improving the regression testing with application specification. The path coverage testing was defined by the author.…”

Section: Related Workmentioning

confidence: 99%

Design of Proposed Test Case Prioritization Model for Test Sequence Generation and Validating Performance against Existing Methods

Priti*¹,

Kavita²

2019

IJRTE

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Regression testing is an effective tool or technique used for minimizing the efforts and resource consumption when a new version or the modification in the software project is tested. In such project, the testing is performed only on the selected modules or testcases. The sequence of the testcase execution also matter in regression testing. Researchers used various evolutionary, swarm based and mathematical methods for testcase prioritization and optimization. Researchers also used the fault based or coverage based measures for testcase prioritization. In this paper, the functional contribution of the recent research is provided. The research method, projects and the contribution of the work is discussed in this paper. In this paper, the framework of the proposed dynamic programming based weighted method is provided. The paper defined the work stages of the proposed model. The algorithm for test sequence generation is also provided in this paper. The analysis results of the work are provided against the greedy and dynamic programming based methods. The results are derived for cost and the number of testcases processed by the method. The results show that the proposed model improved the performance effectively.

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Section: Related Workmentioning

confidence: 99%

Design of Proposed Test Case Prioritization Model for Test Sequence Generation and Validating Performance against Existing Methods

Priti*¹,

Kavita²

2019

IJRTE

View full text Add to dashboard Cite

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“…As we all know, any valid testing contains the path testing, the implementation of the path testing for simple procedures is easy. However, largescale programs have many branches and loops and the number of path will dramatically increase ,which cause the path testing become completely impossible, so in the preliminary study of our project team proposes, the testing theory based on the function call path [2,3,4,5] and develops an automated testing tool-Regression Test For C 1.0 version, which goal is to determine the subset of the path of the actual process, that it use the least testing cases to find the most errors in the program. In C++ program, overload, dynamic polymorphism, templates, and so on make the problem of function call uncertain in the static analysis, which increase the redundancy of function call path, increase the testing costs and reduce the efficiency of software testing.…”

Section: Introductionmentioning

confidence: 99%

Research on Determination of Overloaded Function Uniqueness for Regression Testing Oriented

Sheng

Zhang

et al. 2010

2010 2nd International Conference on Information Engineering and Computer Science

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Function call path testing is based on static analysis of source code. The relationship between the definitions of the overloaded function and the call points is uncertain in the static analysis, which will produce a great deal of redundant paths and increase the cost of the testing. In order to determine the paths of the actual process and get function call relation, firstly, we need to determine the uniqueness of the overloaded function. We analyze the form of the overloaded function call from several aspects, design the algorithm of DUOF(determining the uniqueness of the overloaded function) , ultimately determine its unique, by analyzing the realization mechanism of overloaded functions and applying the theory of compile and objectoriented. The experiment's result shows that the result of its implementation is not only accurate but also can improve the efficiency of regression testing, efficiency of the algorithm is more significant especially when the amount of code is larger.

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