scholarly journals Observations in using parallel and sequential evolutionary algorithms for automatic software testing

2008 ◽  
Vol 35 (10) ◽  
pp. 3161-3183 ◽  
Author(s):  
Enrique Alba ◽  
Francisco Chicano
Keyword(s):  
Evolutionary Algorithms ◽  
Software Testing ◽  
Automatic Software ◽  
Automatic Software Testing

Researches on Automatic Software Testing Techniques

2014 ◽  
Vol 687-691 ◽  
pp. 1958-1961
Author(s):  
Wei Mei Zou ◽  
Xin Liu
Keyword(s):  
Software Testing ◽  
Test Model ◽  
Technology Research ◽  
Automatic Test ◽  
Research Directions ◽  
Testing Technology ◽  
Automatic Software ◽  
Testing Techniques ◽  
Automatic Software Testing

This article briefly describes the background and the advantages of the automatic software testing technology research, summarizes the development, the features, and the research directions of the automatic software testing technology, and then example of analyses the testing process and factors of automatic software testing technology based on the C-ATFM automatic test model.

Application of Orthogonal Experimental Design for the Automatic Software Testing

2013 ◽  
Vol 347-350 ◽  
pp. 812-818 ◽  
Author(s):  
Hao Wu
Keyword(s):  
Experimental Design ◽  
Software Testing ◽  
Error Detection ◽  
Orthogonal Experimental Design ◽  
Test Cases ◽  
High Quality ◽  
Detection Ability ◽  
Automatic Software ◽  
Automatic Software Testing ◽  
Testing Case

According to inputting different combination of conditions so as to produce different impacts, software testing designs a large number of test cases. If the implementation of an overall test, due to the limit of the combination of conditions, it is difficult to carry out. In order to generate high quality test cases as early as possible to improve the efficiency of software testing, it is designed a generation tool of the automatic software testing case on orthogonal experimental design. For the test data, the use of that tool design test cases. The practice shows that a small number of test cases are generated, the error detection ability is strong, and it greatly improves the efficiency of software testing.

Application of Genetic Algorithm in Automatic Software Testing

2010 ◽  
pp. 545-552 ◽  
Author(s):  
Faezeh Sadat Babamir ◽  
Alireza Hatamizadeh ◽  
Seyed Mehrdad Babamir ◽  
Mehdi Dabbaghian ◽  
Ali Norouzi
Keyword(s):  
Genetic Algorithm ◽  
Software Testing ◽  
Automatic Software ◽  
Automatic Software Testing

scholarly journals Status Report on Software Testing: Test-Comp 2021

2021 ◽  
pp. 341-357 ◽  
Author(s):  
Dirk Beyer
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Software Test ◽  
Status Report ◽  
Generation Task ◽  
C Programs ◽  
Branch Coverage ◽  
Current State ◽  
Strong Focus ◽  
Automatic Software

AbstractThis report describes Test-Comp 2021, the 3rd edition of the Competition on Software Testing. The competition is a series of annual comparative evaluations of fully automatic software test generators for C programs. The competition has a strong focus on reproducibility of its results and its main goal is to provide an overview of the current state of the art in the area of automatic test-generation. The competition was based on 3 173 test-generation tasks for C programs. Each test-generation task consisted of a program and a test specification (error coverage, branch coverage). Test-Comp 2021 had 11 participating test generators from 6 countries.

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