Optimizing Probabilities of Real-Time Test Case Execution

NICOLÁS WOLOVICK; PEDRO R. D'ARGENIO; HONGYANG QU

Denver

Conferencia; 2nd International Conference on Software Testing, Verification, and Validation; 2009

Model-based test derivation for real-time system has been proven to be a hard problem for exhaustive test suites. Therefore, techniques for real-time testing do not aim to exhaustiveness but instead respond to particular coverage criteria. Since it is not feasible to generate complete test suites for real time systems, it is very important that test cases are executed in a way that they can achieve the best possible result. As a consequence, it is imperative to increase the probability of success of a test case execution (by ´success´ we actually mean ´the test finds an error´). This work presents a technique to guide the execution of a test case towards a particular objective with the highest possible probability. The technique takes as a starting point a model described in terms of an input/output stochastic automata, where input actions are fully controlled by the tester and the occurrence time of output action responds to uniform distributions. Derived test cases are sequences of inputs and outputs actions. This work discusses several techniques to obtain the optimum times in which the tester must feed the inputs of the test case in order to achieve maximum probability of success in a test case execution. In particular, we show this optimization problem is equivalent to maximizing the sectional volume of a convex polytope when the probability distributions involved are uniform.