Improving the effectiveness of test suite reduction for user-session-based testing of web applications

2012 ◽  
Vol 54 (7) ◽  
pp. 724-738 ◽  
Author(s):  
Sreedevi Sampath ◽  
Renée C. Bryce
Keyword(s):  
Web Applications ◽  
Test Suite ◽  
User Session ◽  
Test Suite Reduction

A Multi-Objective Approach for Test Suite Reduction During Testing of Web Applications

2021 ◽  
Vol 12 (3) ◽  
pp. 81-122
Author(s):  
Munish Khanna ◽  
Naresh Chauhan ◽  
Dilip Kumar Sharma ◽  
Law Kumar Singh
Keyword(s):  
Genetic Algorithm ◽  
Web Applications ◽  
State Of The Art ◽  
Test Suite ◽  
Test Cases ◽  
Nsga Ii ◽  
Multi Objective ◽  
Reduction Problem ◽  
Test Suite Reduction ◽  
Experimental Findings

During the development and maintenance phases of evolving software, new test cases would be needed for the verification of the accuracy of the modifications as well as for new functionalities leading to an increase in the size of the test suite. Various related objectives are to be kept in mind while reducing the original test suite by removing redundancy and generating a practical representative set of the unique test cases, some of which may need to be maximized and the remaining ones minimized. This paper presents a multi-objective approach for the test suite reduction problem in which one objective is to be minimized and the remaining two maximized. In this study, experiments were performed on diverse versions of four web applications. Various state-of-the-art algorithms and their updated versions were compared with non-dominated sorting genetic algorithm-II (NSGA-II) for performance evaluation. Based on experimental findings, it was concluded that NSGA-II outperforms all other algorithms; moreover, the algorithm attempts to satisfy all the objectives without compromising coverage.

scholarly journals A survey on Test Suite Reduction frameworks and tools

2016 ◽  
Vol 36 (6) ◽  
pp. 963-975 ◽  
Author(s):  
Saif Ur Rehman Khan ◽  
Sai Peck Lee ◽  
Raja Wasim Ahmad ◽  
Adnan Akhunzada ◽  
Victor Chang
Keyword(s):  
Test Suite ◽  
Test Suite Reduction

A new heuristic for test suite reduction

1998 ◽  
Vol 40 (5-6) ◽  
pp. 347-354 ◽  
Author(s):  
T.Y. Chen ◽  
M.F. Lau
Keyword(s):  
Test Suite ◽  
Test Suite Reduction

An Effective Approach to Test Suite Reduction and Fault Detection Using Data Mining Techniques

2017 ◽  
Vol 8 (4) ◽  
pp. 1-31 ◽  
Author(s):  
B. Subashini ◽  
D. Jeya Mala
Keyword(s):  
Data Mining ◽  
Attribute Reduction ◽  
Test Suite ◽  
Test Cases ◽  
Data Mining Techniques ◽  
Coverage Analysis ◽  
Quality Product ◽  
Irrelevant Attributes ◽  
Test Suite Reduction ◽  
Using Data

Software testing is used to find bugs in the software to provide a quality product to the end users. Test suites are used to detect failures in software but it may be redundant and it takes a lot of time for the execution of software. In this article, an enormous number of test cases are created using combinatorial test design algorithms. Attribute reduction is an important preprocessing task in data mining. Attributes are selected by removing all weak and irrelevant attributes to reduce complexity in data mining. After preprocessing, it is not necessary to test the software with every combination of test cases, since the test cases are large and redundant, the healthier test cases are identified using a data mining techniques algorithm. This is healthier and the final test suite will identify the defects in the software, it will provide better coverage analysis and reduces execution time on the software.

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