scholarly journals Multi-Objective Test Case Selection: Local Search Approaches for the NSGA-II algorithm

2020 ◽  
Author(s):  
Luciano Soares De Souza
Keyword(s):  
Local Search ◽  
Software Testing ◽  
Search Algorithms ◽  
Selection Problem ◽  
Objective Test ◽  
Test Case ◽  
Nsga Ii ◽  
Test Case Selection ◽  
Multi Objective ◽  
Case Selection

The software testing process can be very expensive and it is important to find ways in order to reduce its costs. Test case selection techniques can be used in order to reduce the amount of tests to execute and this way reducing the costs. Search algorithms are very promising approach to deal with the test case selection problem. This work proposes new hybrid algorithms for multiobjective test case selection by adding local search mechanisms into the NSGAII algorithm. The results showed that some of the mechanisms were capable of improve the NSGA-II algorithm.

scholarly journals A Stochastic Method for Test Case Selection in Software Testing

2020 ◽  
Vol 8 (4S5) ◽  
pp. 265-271
Keyword(s):  
Software Development ◽  
Software Testing ◽  
Test Case ◽  
Test Cases ◽  
Nsga Ii ◽  
Code Coverage ◽  
Test Case Selection ◽  
Redundant Data ◽  
Case Selection ◽  
Selection Of

The quality of the software is a very important aspect in the development of software application. In order to make sure there is the software of good quality, testing is a critical activity of software development. Thus, software testing is the activity which focuses on the computation of an attribute or the ability of either a system or program that decides if user requirements are met. There is a proper strategy for the design of software for which testing has to be adopted. The techniques of test case selection attempt at reduction of the test cases that need to be executed at the same time satisfying the needs of testing that has been denoted by the test criteria. In the time of software testing, and the resource will be the primary constraints at the time of testing since this has been a highly neglected phase in the Software Development Life Cycle (SDLC). The optimizing of a test suite is very critical for the reduction of the testing phase and also the selection of the test cases that eliminate unwanted or redundant data. All work in literature will make use of techniques of single objective optimization that does not have to be efficient as the code coverage will play an important role at the time of selection of test case. As the test case choice is Non-Deterministic, the work also proposes a novel and multi-objective algorithm like the Non-Dominated Sorting Genetic Algorithm II (NSGA II) and the Stochastic Diffusion Search (SDS) algorithm that makes use of the cost of execution and code coverage as its objective function. The results prove a faster level of convergence of the algorithm with better coverage of code in comparison to the NSGA II.

scholarly journals A Hybrid Algorithm for Multi-Objective Test Case Selection

2018 ◽  
Author(s):  
Takfarinas Saber ◽  
Florian Delavernhe ◽  
Mike Papadakis ◽  
Michael Oneill ◽  
Anthony Ventresque
Keyword(s):  
Hybrid Algorithm ◽  
Objective Test ◽  
Test Case ◽  
Test Case Selection ◽  
Multi Objective ◽  
Case Selection

Improving Multi-Objective Test Case Selection by Injecting Diversity in Genetic Algorithms

2015 ◽  
Vol 41 (4) ◽  
pp. 358-383 ◽  
Author(s):  
Annibale Panichella ◽  
Rocco Oliveto ◽  
Massimiliano Di Penta ◽  
Andrea De Lucia
Keyword(s):  
Genetic Algorithms ◽  
Objective Test ◽  
Test Case ◽  
Test Case Selection ◽  
Multi Objective ◽  
Case Selection
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