SESAME (Software Environment for Software Analysis by Mutation Effects) is a fault injection tool using mutation as the target fault model. It has been used for 15 years to support dependability research at LAAS-CNRS. A salient feature of SESAME is that it is multi-language. This made it possible to inject faults into software written in assembly languages, procedural languages (Pascal, C), a data-flow language (LUSTRE), as well as in a declarative language for temporal planning in robotics. This paper provides an overview of the tool, and reports on its use in experimental research addressing either fault removal or fault tolerance topics.

The fault revealing power of different test patterns derived from ten structural test criteria currently referred to in unit testing is investigated. Experiments performed on four programs that are pieces of a real-life software system from the nuclear field are reported. Three test input generation techniques are studied: (1) deterministic choice, (2) random selection based on an input probability distribution determined according to the adopted structural test criterion, and (3) random selection from a uniform distribution on the input domain. Mutation analysis is used to assess the test set efficiency with respect to error detection. The experimental results involve a total of 2914 mutants. They show that structural statistical testing, which exhibits the highest mutation scores, leaving alive only six from 2816 nonequivalent mutants within short testing times, is the most efficient. A regards unit testing of programs whose structure remains tractable, the experiments show the adequacy of a fault removal strategy combining statistical and deterministic test patterns