Abstract. Throughout the years, many model description languages have been used in different model-based testing tools, however, all these languages are quite unfamiliar to test engineers. In this paper, we propose TTCN-3 (Testing and Test Control Notation 3), the nowadays most popular and widely spread test definition language to be used for this purpose and give two alternative approaches how this could be carried out. TTCN-3 as modelling language can support test generation tools by means of the annotations we introduce in the paper.

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This paper proposes methods for improving the performance of a communicating system that has failed its performance test. The proposed methods extend our earlier published model-driven performance testing method, which automatically determines whether the tested system is able to serve the specified number of requests within a second in worst case while serving a specified number of users simultaneously. The underperformance diagnostic methods presented in this paper are given as an input the formal performance model representing the system under test, which was built up by our performance testing method in the performance testing phase. The presented methods aim at improving the performance of the system under test to the desired level at minimal cost. One of the methods presented in this paper is a binary linear program, while the other is a heuristic method which, according to our simulation results, performs efficiently.

In this paper we introduce automatic methods for restructuring source codes written in test description languages. We modify the structure of these sources without making any changes to their behavior. This technique is called refactorisation. There are many approaches to refactorisation. The goal of our refactorisation methods is to increase the maintainability of source codes. We focus on TTCN-3 (Testing and Test Control Notation), which is a rapidly spreading test description language nowadays. A TTCN-3 source consists of a data description (static) part and a test execution (dynamic) part. We have developed models and refactorisation methods based on these models, separately for the two parts. The static part is mapped into a layered graph structure, while the dynamic part is mapped to a CEFSM (Communicating Extended Finite State Machine) – based model.