文章基本信息

标题：A GA-Based Approach to Automatic Test Data Generation for ASP.NET Web Applications
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作者：Islam T. Elgendy ; Moheb R. Girgis ; Adel A. Sewisy 等
期刊名称：IAENG International Journal of Computer Science
印刷版ISSN：1819-656X
电子版ISSN：1819-9224
出版年度：2020
卷号：47
期号：3
语种：English
出版社：IAENG - International Association of Engineers
摘要：One of the major challenges in software testing is the generation of test data automatically that satisfy a specified adequacy criterion. This paper presents a GA-based approach and a supporting tool for data-flow test data generation for ASP.NET web applications. The proposed tool accepts as input the web application under test, instruments it, and performs static analysis to compute the definition-use pairs. The proposed GA conducts its search by constructing new test data from previously generated test data that are evaluated as effective test data. In this GA, the chromosome is a collection of user interface control objects, where each control is considered as a gene. Therefore, novel crossover and mutation operators are developed to manipulate the chromosome, which are called block crossover and control-based mutation operators. The proposed GA accepts as input the instrumented version, the list of definition-use pairs to be covered, and input controls related information. The tool produces a set of test cases, the set of definition-use pairs covered by each test case, and a list of uncovered definition-use pairs, if any. Also the paper presents a case study to illustrate how the tool works. Finally, it presents the results of the empirical evaluation that is performed to evaluate the effectiveness of the generated test data in exposing web application errors.
关键词：Software testing;Data Flow Testing;Automatic test data generation;Automated Testing Tool;Web Applications Testing