Empirically Comparing the Test Suite Reduction Techniques in Continuous Integration Process

2021 ◽  
Author(s):  
Jutarporn Intasara ◽  
Chu-Ti Lin
Keyword(s):  
Test Suite ◽  
Integration Process ◽  
Continuous Integration ◽  
Reduction Techniques ◽  
Test Suite Reduction

scholarly journals Test Case Optimization for Enhancing System Software Quality using Genetic Algorithm

2019 ◽  
Vol 8 (12) ◽  
pp. 68-75
Keyword(s):  
Genetic Algorithm ◽  
Optimization Problems ◽  
Test Suite ◽  
Test Case ◽  
Product Lines ◽  
Reduction Techniques ◽  
Mutation Operators ◽  
Effective Manner ◽  
Software Programs ◽  
Test Suite Reduction

Software Product Lines (SPLs) embraces an enormous capacity of feature mixtures which cause challenges for evaluating software programs. Testsuite optimization plays major role to develope the quality of SPLs. In combinatorial testing (CT), pair wise fault coverage maximization and test case reduction accomplishes a substantial role for shrinking the testing cost of software programs. Many research works have been developed and designed for CT using different test suite reduction techniques. However Fuzzy clustering and TSRSO techniques do not provide a finest solution for test suite optimization problem. For that, Genetic Algorithm (GA) Technique is recommended and designed for test suite reduction in CT. Metaheuristic genetic algorithm delivers optimum solution in an effective manner. GA chooses and consolidates the testcases in a testsuite based on some principles such that maximum faults covered with minimum execution time. In Proposed GA, finest individuals are nominated for reproduction in order to create descendants of the succeeding generation. In addition, GA is a superior type of evolutionary algorithms generate finest solutions to optimization problems using selection, crossover and mutation operators. Consequently, GA is applied for resolving test suite reduction problem in CT

Investigating Different Metrics for Evaluation and Selection of Mutation Operators for Java

2021 ◽  
Vol 31 (03) ◽  
pp. 311-336
Author(s):  
Shweta Rani ◽  
Bharti Suri
Keyword(s):  
Cost Reduction ◽  
Test Suite ◽  
Cost Benefits ◽  
Powerful Technique ◽  
Reduction Techniques ◽  
Mutation Operators ◽  
Different Types ◽  
Java Programs ◽  
Selective Mutation ◽  
Selection Of

Mutation testing is a successful and powerful technique, specifically designed for injecting the artificial faults. Although it is effective at revealing the faults, test suite assessment and its reduction, however, suffer from the expense of executing a large number of mutants. The researchers have proposed different types of cost reduction techniques in the literature. These techniques highly depend on the inspection of mutation operators. Several metrics have been evolved for the same. The selective mutation technique is most frequently used by the researchers. In this paper, the authors investigate different metrics for evaluating the traditional mutation operators for Java. Results on 13 Java programs indicate how grouping few operators can impact the effectiveness of an adequate and minimal test suite, and how this could provide several cost benefits.

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

scholarly journals A review on Continuous Integration, Delivery and Deployment using Jenkins

2021 ◽  
Vol 23 (06) ◽  
pp. 919-922
Author(s):  
Arpita S.K ◽  
◽  
Amrathesh Amrathesh ◽  
Dr. Govinda Raju M ◽  
◽  
...  
Keyword(s):  
Software Development ◽  
Software Tools ◽  
Integration Process ◽  
Continuous Integration ◽  
Software Deployment ◽  
Development Cycle ◽  
Continuous Delivery ◽  
Standard Practices ◽  
Development Methods ◽  
The Given

Continuous Integration (CI) is the technique of integrating small changes made to the code more often rather than waiting till the end of the development cycle for integration. The software practice wherein the software deployment can be done anytime to the market is called Continuous Delivery (CD). With continuous integration and continuous delivery, the problem of taking time to find and resolve the bug can be reduced to a large extent. As the time to find the bugs and fix them gets reduced, many releases adhering to the given timeline can be made by an organization. Various software tools have been developed for the continuous integration process which includes Jenkins, Bitbucket, TeamCity. In this paper, a review on the standard practices, approaches, challenges faced while using the continuous integration/delivery in the software development, methods of solving them, and using Jenkins for the implantation of continuous integration/delivery is done.

scholarly journals Test Case Reduction Using Ant Colony Optimization for Object Oriented Program

2015 ◽  
Vol 5 (6) ◽  
pp. 1424
Author(s):  
Sudhir Kumar Mohapatra ◽  
Srinivas Prasad
Keyword(s):  
Ant Colony Optimization ◽  
System Development ◽  
Object Oriented ◽  
Ant Colony ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Reduction Techniques ◽  
Maintenance Stage ◽  
The Cost

Software testing is one in all the vital stages of system development. In software development, developers continually depend upon testing to reveal bugs. Within the maintenance stage test suite size grow due to integration of new functionalities. Addition of latest technique force to make new test case which increase the cost of test suite. In regression testing new test case could also be added to the test suite throughout the entire testing process. These additions of test cases produce risk of presence of redundant test cases. Because of limitation of time and resource, reduction techniques should be accustomed determine and take away. Analysis shows that a set of the test case in a suit should satisfy all the test objectives that is named as representative set. Redundant test case increase the execution price of the test suite, in spite of NP-completeness of the problem there are few sensible reduction techniques are available. During this paper the previous GA primarily based technique proposed is improved to search out cost optimum representative set using ant colony optimization.

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