3 research outputs found
A Mapping Study of scientific merit of papers, which subject are web applications test techniques, considering their validity threats
Progress in software engineering requires (1) more empirical studies of quality, (2) increased focus on synthesizing evidence, (3) more theories to be built and tested, and (4) the validity of the experiment is directly related with the level of confidence in the process of experimental investigation. This paper presents the results of a qualitative and quantitative classification of the threats to the validity of software engineering experiments comprising a total of 92 articles published in the period 2001-2015, dealing with software testing of Web applications. Our results show that 29.4% of the analyzed articles do not mention any threats to validity, 44.2% do it briefly, and 14% do it judiciously; that leaves a question: these studies have scientific value
A Systematic Review of the Application and Empirical Investigation of Search-Based Test Case Generation
Otsingupõhine tarkvara testimine kasutab metaheuristilisi algoritme, et automatiseerida testide genereerimist. Selle töö eesmärgiks on osaliselt taasluua 2010. aastal kirjutatud Ali et al. artikkel, et uurida, kuidas on aastatel 2008-2015 kasutatud metaheuristilisi algoritme testide loomiseks. See töö analüüsib, kuidas on antud artiklid koostatud ning kuidas neis on algoritmide maksumust ja efektiivsust hinnatud. Kogutud tulemusi võrreldakse Ali et al. tulemustega.Search based software testing uses metaheuristic algorithms to automate the generation of test cases. This thesis partially replicates a literature study published in 2010 by Ali et al. to determine how studies published in 2008-2015 use metaheuristic algorithms to automate the generation of test cases. The thesis analyses how these studies were conducted and how the cost-effectiveness is assessed in these papers. The trends detected in the new publications are compared to those presented in Ali et al
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Enhancing Search-Based Techniques with Information Control Dependencies
Software testing is a very important task during software development and it can be used to improve the quality and reliability of the software system. One potential way to reduce the cost and increase the efficiency of software testing is to generate test data automatically. Search-based approaches successfully generate unit tests for object-oriented programs, like Java. However, challenges, such as the large size of the search space, and the presence of complex predicates’ target branches, negatively affect the approaches, and, thus, cannot achieve high structural coverage for certain programs.
The aim of this thesis is to propose enhancement techniques to improve the effectiveness of search based testing approaches and address the challenges posed by the object-oriented programs. Rather than randomly generating a sequence of method calls, our ongoing work is to focus on using static analysis to define the hidden data dependencies on predicates’ target branches (i.e., uncovered branches) and exploit method dependence relations (MDR) approach to precisely identify the method/constructors and its parameters. This method dependence information is employed to reduce the search space and used to guide the search toward regions that lead to full (or at least high) structural coverage