Pattern-based generation of test plans for open distributed processing systems

Abstract

Acceptance testing is a time-consuming task for complex software systems that have to fulfil a large number of requirements. To reduce efforts in acceptance testing, we have developed an approach that exploits redundancies and implicit relations in requirements specifications which are based on multi-viewpoint techniques, such as RM-ODP. We use linguistic analysis techniques, requirements clustering algorithms and pattern-based requirements collection for reducing the total number of test cases that are derived from the requirements specification. In particular, we present new capabilities for automatically deriving semi-formal test plans and acceptance criteria from the clustered informal textual requirements. Tool support for automated detection of redundancies and implicit relations is extended by new functionalities regarding measurement and the generation of quality plans. We apply our solution particularly in planning, procurement and acceptance testing of national electronic identification (eID) systems. In summary, we show that linguistic analysis and clustering techniques can help testers in understanding the relations between requirements and for improving test planning.