Mutation-based exploration of a method for verifying concurrent Java components

Summary form only given. The Java programming language supports concurrency. Concurrent programs are harder to verify than their sequential counterparts due to their inherent nondeterminism and a number of specific concurrency problems such as interference and deadlock. In previous work, we proposed a method for verifying concurrent Java components based on a mix of code inspection, static analysis tools, and the ConAn testing tool. The method was derived from an analysis of concurrency failures in Java components, but was not applied in practice. In this paper, we explore the method by applying it to an implementation of the well-known readers-writers problem and a number of mutants of that implementation. We only apply it to a single, well-known example, and so we do not attempt to draw any general conclusions about the applicability or effectiveness of the method. However, the exploration does point out several strengths and weaknesses in the method, which enable us to fine-tune the method before we carry out a more formal evaluation on other, more realistic components.

Mutation analysis to verify feature matrices for isolating errors in simulation models

Software simulation models are computer programs that need to be verified and debugged like any other software. In previous work, a method for error isolation in simulation models has been proposed. The method relies on a set of feature matrices that can be used to determine which part of the model implementation is responsible for deviations in the output of the model. Currrently these feature matrices have to be generated by hand from the model implementation, which is a tedious and error-prone task. In this paper, a method based on mutation analysis, as well as prototype tool support for the verification of the manually generated feature matrices is presented. The application of the method and tool to a model for wastewater treatment shows that the feature matrices can be verified effectively using a minimal number of mutants.