This paper applies the Evolutionary Strategy (ES) metaheuristic to the automatic test data generation problem. The problem consists in creating automatically a set of input data to test a program. This is a required step in software development and a time consuming task in all software companies. We describe our proposal and study the influence of some parameters of the algorithm in the results...

In recent work, we have proposed an approach to Test Data Generation (TDG) of imperative bytecode by partial evaluation (PE) of CLP which consists in two phases: (1) the bytecode program is first transformed into an equivalent CLP program by means of interpretive compilation by PE, (2) a second PE is performed in order to supervise the generation of test-cases by execution of the CLP decompiled...

Floating-point computations are quickly finding their way in the design of safetyand mission-critical systems, despite the fact that designing floating-point algorithms is significantly more difficult than designing integer algorithms. For this reason, verification and validation of floating-point computations is a hot research topic. An important verification technique, especially in some indu...

s and proceedings: Vilhelmsen, T.N., Christensen, S., Testing MODFLOW-LGR for simulating flow around buried Quaternary valleys – synthetic test cases, AGU fall meeting 2009, San Francisco, U.S.A., 14-18 December 2009 Vilhelmsen, T.N., Christensen, S., Test af to versioner af MODFLOW-LGR til simulering af grundvandsstrømninger i områder med begravede dale – syntetisk studie, ATV vintermøde 2010,...

Automatic assessment of programming exercises is typically based on testing approach. Most automatic assessment frameworks execute tests and evaluate test results automatically, but the test data generation is not automated. No matter that automatic test data generation techniques and tools are available. We have researched how the Java PathFinder software model checker can be adopted to the sp...

Software testing is an important part of the software development process. Much work been has done on automating various parts of testing. In previous work, we had proposed a knowledge-based approach to generate test scenarios for Web applications. However, our previous work did not account for generation of actual test data. Thus, in order to execute the test scenarios, the user would need to ...

The application of genetic algorithms in automatically generating test data has aroused broad concerns and obtained delightful achievements in recent years. However, the efficiency of genetic algorithm-based test data generation for path testing needs to be further improved. In this paper, we establish a mathematical model of generating test data for multiple paths coverage. Then, a multipopula...

Effective and efficient test data generation is one of the major challenging and time-consuming tasks within the software testing process. Researchers have proposed different methods to generate test data automatically, however, those methods suffer from different drawbacks. In this paper we present a Genetic Algorithm-based approach that tries to generate a set of test data that is expected to...

This paper presents a practical approach to parallelize the test data generation algorithm by which computing resources can be fully used. The test data generation approach that we are using is based on the dynamic symbolic execution (concolic testing). The basic idea of parallelizing the algorithm is to distribute analysis processes of different paths to different computing units. Although a c...

This paper considers the problem of test data generation for the core level verification of micro processors; namely, the problem of constructing a test program on the basis of its abstract form (test tem plate). To solve this problem, we propose an algorithm reducing it to a problem of resolving constraints. This paper addresses the verification of memory handling instructions (taking into acc...