Item Type Article Authors Papadopoulos, Y.; Walker, M.; Parker, D.; Sharvia, S.; Bottaci, L.; Kabir, Sohag; Azevedo, L.; Sorokos, I. Citation Papadopoulos Y, Walker M, Parker D et al (2016) A synthesis of logic and bio-inspired techniques in the design of dependable systems. Annual Reviews in Control. 41: 170-182.
RightsAbstract: The technologies of model-based design and dependability analysis in the design of dependable systems, including software intensive systems, have advanced in recent years. Much of this development can be attributed to the application of advances in formal logic and its application to fault forecasting and verification of systems. In parallel, work on bio-inspired technologies has shown potential for the evolutionary design of engineering systems via automated exploration of potentially large design spaces. We have not yet seen the emergence of a design paradigm that effectively combines these two techniques, schematically founded on the two pillars of formal logic and biology, throughout the design lifecycle. Such a design paradigm would apply these techniques synergistically and systematically from the early stages of design to enable optimal refinement of new designs which can be driven effectively by dependability requirements. The paper sketches such a model-centric paradigm for the design of dependable systems that brings these technologies together to realise their combined potential benefits.
Abstract. Several researchers are using evolutionary search methods to search for test data with which to test a program. The fitness or cost function depends on the test goal but almost invariably an important component of the cost function is an estimate of the cost of satisfying a predicate expression as might occur in branches, exception conditions, etc. This paper reviews the commonly used cost functions and points out some deficiencies. Alternative cost functions are proposed to overcome these deficiencies. The evidence from an experiment is that they are more reliable.
It is commonly accepted that strong typing is useful for revealing programmer errors and so the use of dynamically typed languages increases the importance of software testing. Mutation analysis is a demanding software testing criterion. Although mutation analysis has been applied to procedural languages, and object oriented languages, little work has been done on the mutation analysis of programs written in dynamically typed languages.Mutation analysis depends on the substitution and modification of program elements. In a strongly typed language, the declared type of the mutated element, a variable or operator, can be used to avoid generating type-incorrect substitutions or modifications. In a dynamically typed language, this type information is not available and so a much greater range of mutations are potentially applicable but many of the resulting mutants are likely to be incompetent (too easily killed). This paper describes a mutation analysis method in which the definition of mutants is performed at run-time when type information is available. The type information can be used to avoid generating incompetent mutants.
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