scholarly journals Regression Test Suite Prioritization using Residual Test Coverage Algorithm and Statistical Techniques

2016 ◽  
Vol 6 (5) ◽  
pp. 32-39
Author(s):  
Abhinandan H. Patil ◽  
◽  
Neena Goveas ◽  
Krishnan Rangarajan
Keyword(s):  
Test Suite ◽  
Statistical Techniques ◽  
Test Coverage ◽  
Regression Test

USING RULE STRUCTURE TO EVALUATE THE COMPLETENESS OF RULE-BASED SYSTEM TESTING: A CASE STUDY

2010 ◽  
Vol 20 (07) ◽  
pp. 975-986 ◽  
Author(s):  
STEPHEN C. MEDDERS ◽  
EDWARD B. ALLEN ◽  
EDWARD A. LUKE
Keyword(s):  
Test Suite ◽  
Application Framework ◽  
Test Coverage ◽  
Prior Work ◽  
Rule Based ◽  
Coverage Metrics ◽  
Rule Based System ◽  
Regression Test ◽  
Rule Based Systems

Rule-based systems are typically tested using a set of inputs which will produce known outputs. However, one does not know how thoroughly the software has been exercised. Traditional test-coverage metrics do not account for the dynamic data-driven flow of control in rule-based systems. Our literature review found that there has been little prior work on coverage metrics for rule-based systems. This paper proposes test-coverage metrics for rule-based systems derived from metrics defined by prior work, and presents an industrial scale case study. We conducted a case study to evaluate the practicality and usefulness of the proposed metrics. The case study applied the metrics to a system for computational fluid-dynamics models based on a rule-based application framework. These models were tested using a regression-test suite. The data-flow structure built by the application framework, along with the regression-test suite, provided case-study data. The test suite was evaluated against three kinds of coverage. The measurements indicated that complete coverage was not achieved, even at the lowest level definition. Lists of rules not covered provided insight into how to improve the test suite. The case study illustrated that structural coverage measures can be utilized to measure the completeness of rule-based system testing.

scholarly journals Regression Test Suite Execution Time Analysis using Statistical Techniques

2016 ◽  
Vol 6 (3) ◽  
pp. 33-41
Author(s):  
Abhinandan H. Patil ◽  
◽  
Neena Goveas ◽  
Krishnan Rangarajan
Keyword(s):  
Execution Time ◽  
Test Suite ◽  
Statistical Techniques ◽  
Time Analysis ◽  
Regression Test

Comparison of Multi-Objective Evolutionary Algorithms to Prioritize Regression Test Cases

2021 ◽  
Vol 9 (12) ◽  
pp. 1445-1454
Keyword(s):  
Fault Detection ◽  
Evolutionary Algorithms ◽  
Fitness Function ◽  
Optimal Solution ◽  
Test Suite ◽  
Test Case ◽  
Test Cases ◽  
Nsga Ii ◽  
Multi Objective ◽  
Regression Test

Regression testing is one of the most critical testing activities among software product verification activities. Nevertheless, resources and time constraints could inhibit the execution of a full regression test suite, hence leaving us in confusion on what test cases to run to preserve the high quality of software products. Different techniques can be applied to prioritize test cases in resource-constrained environments, such as manual selection, automated selection, or hybrid approaches. Different Multi-Objective Evolutionary Algorithms (MOEAs) have been used in this domain to find an optimal solution to minimize the cost of executing a regression test suite while obtaining maximum fault detection coverage as if the entire test suite was executed. MOEAs achieve this by selecting set of test cases and determining the order of their execution. In this paper, three Multi Objective Evolutionary Algorithms, namely, NSGA-II, IBEA and MoCell are used to solve test case prioritization problems using the fault detection rate and branch coverage of each test case. The paper intends to find out what’s the most effective algorithm to be used in test cases prioritization problems, and which algorithm is the most efficient one, and finally we examined if changing the fitness function would impose a change in results. Our experiment revealed that NSGA-II is the most effective and efficient MOEA; moreover, we found that changing the fitness function caused a significant reduction in evolution time, although it did not affect the coverage metric.

Towards a Shift in Regression Test Suite Development Approach in Agile

2021 ◽  
Vol 14 ◽  
Author(s):  
Sarika Sharma ◽  
Deepak Kumar
Keyword(s):  
Literature Review ◽  
Software Maintenance ◽  
Research Work ◽  
Regression Testing ◽  
Test Suite ◽  
Agile Methodology ◽  
Regression Test ◽  
Testing Algorithms ◽  
Development Approach ◽  
Agile Software

Objective: From the literature review, it is evident that the concept of “regression testing” inherited in agile software testing originates from software maintenance practices. Therefore, the existing algorithms for regression testing revolve around the software maintenance principles rather than agile methodology. The objective of this paper is to evaluate the degree of fitness of the existing regression test-suite development algorithms for performing the regression testing in agile. Methods: This paper performs a systematic literature review for research work published from 2006 to 2018, which includes survey of the existing regression testing algorithms to identify and overcome the challenges associated with them while performing regression testing in agile. This research paper considers the four research questions into scope for analyzing the fitness of existing regression test-suite development algorithm for performing regression testing under agile methodology. Further, this paper attempts to propose approach for the development of the regression test-suite suitable for regression testing under agile methodology. Results: The current regression test-suite development algorithm were found unsuitable for performing the regression testing under agile methodology due to the newly identified four key challenges associated with them. Conclusion: The current regression test-suite development algorithms aligned with software maintenance principles rather than agile methodology. In addition, the newly proposed approach for regression test-suite development found to be easily adaptable by agile teams as it aligns with agile methodology principles. Finally, this paper recommends the adoption of agile principle through the newly proposed approach for developing regression test-suite for performing regression testing under agile methodology.

An Effective Regression Test Case Selection Using Hybrid Whale Optimization Algorithm

2020 ◽  
Vol 11 (1) ◽  
pp. 53-67 ◽  
Author(s):  
Arun Prakash Agrawal ◽  
Ankur Choudhary ◽  
Arvinder Kaur
Keyword(s):  
Cost Reduction ◽  
Test Suite ◽  
Test Case ◽  
Test Cost ◽  
Test Case Selection ◽  
Case Selection ◽  
Test Cost Reduction ◽  
Whale Optimization ◽  
Regression Test ◽  
Test Suite Optimization

Test suite optimization is an ever-demanded approach for regression test cost reduction. Regression testing is conducted to identify any adverse effects of maintenance activity on previously working versions of the software. It consumes almost seventy percent of the overall software development lifecycle budget. Regression test cost reduction is therefore of vital importance. Test suite optimization is the most explored approach to reduce the test suite size to re-execute. This article focuses on test suite optimization as a regression test case selection, which is a proven N-P hard combinatorial optimization problem. The authors have proposed an almost safe regression test case selection approach using a Hybrid Whale Optimization Algorithm and empirically evaluated the same on subject programs retrieved from the Software Artifact Infrastructure Repository with Bat Search and ACO-based regression test case selection approaches. The analyses of the obtained results indicate an improvement in the fault detection ability of the proposed approach over the compared ones with significant reduction in test suite size.

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