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Software integration testing based on communication coverage criteria and partial model generation
This paper considers the problem of integration testing the components of a timed distributed software system. We assume that communication between the components is specified using timed interface automata and use computational tree logic (CTL) to define communication-based coverage criteria that refer to send- and receive-statements and communication paths. The proposed method enables testers to focus during component integration on such parts of the specification, e.g. behaviour specifications or Markovian usage models, that are involved in the communication between components to be integrated. A more specific application area of this approach is the integration of test-models, e.g. a transmission gear can be tested based on separated models for the driver behaviour, the engine condition, and the mechanical and hydraulical transmission states. Given such a state-based specification of a distributed system and a concrete coverage goal, a model checker is used in order to determine the coverage or generate test sequences that achieve the goal. Given the generated test sequences we derive a partial test-model of the components from which the test sequences are derived. The partial model can be used to drive further testing and can also be used as the basis for producing additional partial models in incremental integration testing. While the process of deriving the test sequences could suffer from a combinatorial explosion, the effort required to generate the partial model is polynomial in the number of test sequences and their length. Thus, where it is not feasible to produce test sequences that achieve a given type of coverage it is still possible to produce a partial model on the basis of test sequences generated to achieve some other criterion. As a result, the process of generating a partial model has the potential to scale to large industrial software systems. While a particular model checker, UPPAAL, was used, it should be relatively straightforward to adapt the approach for use with other CTL based model checkers. A potential additional benefit of the approach is that it provides a visual description of the state-based testing of distributed systems, which may be beneficial in other contexts such as education and comprehension
Confluence versus Ample Sets in Probabilistic Branching Time
To improve the efficiency of model checking in general, and probabilistic model checking in particular, several reduction techniques have been introduced. Two of these, confluence reduction and partial-order reduction by means of ample sets, are based on similar principles, and both preserve branching-time properties for probabilistic models. Confluence reduction has been introduced for probabilistic automata, whereas ample set reduction has been introduced for Markov decision processes. In this presentation we will explore the relationship between confluence and ample sets. To this end, we redefine confluence reduction to handle MDPs. We show that all non-trivial ample sets consist of confluent transitions, but that the converse is not true. We also show that the two notions coincide if the definition of confluence is restricted, and point out the relevant parts where the two theories differ. The results we present also hold for non-probabilistic models, as our theorems can just as well be applied in a context where all transitions are non-probabilistic. To show a practical application of our results, we adapt a state space generation technique based on representative states, already known in combination with confluence reduction, so that it can also be applied with partial-order reduction
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