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Title: Improving fault coverage and minimising the cost of fault identification when testing from finite state machines
Authors: Guo, Qiang
Advisors: Hierons, RM
Harman, M
Issue Date: 2006
Publisher: Brunel University, School of Information Systems, Computing and Mathematics Theses
Abstract: Software needs to be adequately tested in order to increase the confidence that the system being developed is reliable. However, testing is a complicated and expensive process. Formal specification based models such as finite state machines have been widely used in system modelling and testing. In this PhD thesis, we primarily investigate fault detection and identification when testing from finite state machines. The research in this thesis is mainly comprised of three topics - construction of multiple Unique Input/Output (UIO) sequences using Metaheuristic Optimisation Techniques (MOTs), the improved fault coverage by using robust Unique Input/Output Circuit (UIOC) sequences, and fault diagnosis when testing from finite state machines. In the studies of the construction of UIOs, a model is proposed where a fitness function is defined to guide the search for input sequences that are potentially UIOs. In the studies of the improved fault coverage, a new type of UIOCs is defined. Based upon the Rural Chinese Postman Algorithm (RCPA), a new approach is proposed for the construction of more robust test sequences. In the studies of fault diagnosis, heuristics are defined that attempt to lead to failures being observed in some shorter test sequences, which helps to reduce the cost of fault isolation and identification. The proposed approaches and techniques were evaluated with regard to a set of case studies, which provides experimental evidence for their efficacy.
Description: This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.
Appears in Collections:Publications
Computer Science
Software Engineering (B-SERC)
Dept of Computer Science Theses

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