Generating realistic test data is a major problem for software testers. Realistic test data generation for certain input types is hard to automate and therefore laborious. We propose a novel automated solution to test data generation that exploits existing web services as sources of realistic test data. Our approach is capable of generating realistic test data and also generating data based on ...

This article considers different automatic control paradigms allowing for varying degrees of agent cooperation and autonomy. In order to support the automatic verification of safety-relevant software controllers, it proposes the use of a generic testing pattern which can be instantiated such as to allow to optimize automatic test data generation with respect to the specific targets of the appli...

Recent research on search-based test data generation for Object-Oriented software has relied heavily on typed Genetic Programming for representing and evolving test data. However, standard typed Genetic Programming approaches do not allow Object Reuse; this paper proposes a novel methodology to overcome this limitation. Object Reuse means that one instance can be passed to multiple methods as a...

A challenging problem in path-oriented test data generation is the presence of infeasible paths. Timely detecting these infeasible paths cannot only save test resources but also improve test efficiency. A popular method of detecting infeasible paths is to determine branch correlations, which is a difficult task and usually cannot be done timely and exactly. In this study, the authors propose a ...

This paper presents a method for automatically testing interactive multimodal systems. The method is based on the Lutess testing environment, originally dedicated to synchronous software specified using the Lustre language. The behaviour of synchronous systems, consisting of cycles starting by reading an external input and ending by issuing an output, is to a certain extent similar to the one o...

Random testing can be fully automated, eliminates subjectiveness in constructing test cases, and increases the diversity of test data. However, randomly generated tests may not satisfy program’s assumptions (e.g., method preconditions). While constraint solving can satisfy such assumptions, it does not necessarily generate diverse tests and is hard to apply to large programs. We blend these tec...

As time continues to advance, the need for robust security threat mitigation has become increasingly vital in software. It is a constant struggle maximize test coverage through optimal data generation. We conducted explanatory research of requirements as modeled structured misuse case description (SMCD). The acceptance designed threats. Mal activity from SMCD upon which constraints are specifie...

Three approaches to the problem of testing synchronous data-flow programs written in LUSTRE are presented. LUSTRE is a language well-adapted to both the specification and the development of reactive software. The first approach automatically transforms a set of LUSTRE invariant properties characterizing the environment of the reactive program into a constrained random generator of test data seq...