Analysis and assessment of weighted combinatorial criterion for test suite reduction

2021 ◽  
Author(s):  
Chi‐Lun Chiang ◽  
Chin‐Yu Huang ◽  
Chang‐Yu Chiu ◽  
Kai‐Wen Chen ◽  
Chen‐Hua Lee
Keyword(s):  
Test Suite ◽  
Test Suite Reduction

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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