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Uncaught exceptions, and in particular null pointer exceptions (NPEs), constitute a major cause of crashes for software systems. Although tools for the static identification of potential NPEs exist, there is need for proper approaches able to identify system execution scenarios causing NPEs. This paper proposes a search-based test data generation approach aimed at automatically identify NPEs. The...
Software testing is the important means that guarantee software quality and reliability. Improving the automation ability of software testing is very important for ensuring software's quality and reducing development cost, and improving the automation ability of test cases generation is the key point for the entire process. This paper discusses the methods and techniques of genetic algorithm as the...
We propose an approach in the form of a light weight smart fuzzer to generate string based inputs to detect buffer overflow vulnerability in C code. The approach is based on an evolutionary algorithm which is a combination of genetic algorithm and evolutionary strategies. In this preliminary work we focus on the problem that there are constraints on string inputs that must be satisfied in order to...
Generation of test data for path coverage is an important issue of software testing, but previous methods are only suitable for the case that a program only has a small number of paths. We focus on the problem of generating test data for many paths coverage in this paper, and present a method of evolutionary generation of test data for many paths coverage. First, target paths are divided into several...
A Class is not only a template of objects with the same data structure, but also it could be deployed as component and web service in J2EE and .Net platforms. Therefor, Class testing is the key to ensure the quality of a distributed application. Genetic algorithm(GA) has been used to generate test data for class testing. But it has some defects, for example, some individuals would be generated and...
A new method called EPDG-GA which utilizes the edge partitions dominator graph (EPDG) and genetic algorithm (GA) for branch coverage testing is presented in this paper. First, a set of critical branches (CBs) are obtained by analyzing the EPDG of the tested program, while covering all the CBs implies covering all the branches of the control flow graph (CFG). Then, the fitness functions are instrumented...
Fuzzing was successfully used to discover security bugs in popular programs, though released without source code. It becomes a major tool in security analysis, but needs large input space, ineffective. This paper presents a new method for the identification of vulnerabilities in executable program called GAFuzzing (genetic algorithm fuzzing), which combines static and dynamic analysis to extend random...
A major issue in software testing is the automatic generation of the inputs to be applied to the programme under test. To solve this problem, a number of approaches based on search methods have been developed in the last few years, offering promising results for adequacy criteria like, for instance, branch coverage. We devise branch coverage as the satisfaction of a number of constraints. This allows...
Software specification is an important element of the software development process. However, in most cases the specifications are out-of-date or even missing. One solution for this kind of problem is to use some process that infers the specification automatically. Work by Ernst et al (2000 ; 2002) has shown how specifications can be generated using program execution traces. These approaches are dependent...
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