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Title: Search-based software engineering: A search-based approach for testing from extended finite state machine (EFSM) models
Authors: Kalaji, AbdulSalam
Advisors: Hierons, RM
Swift, S
Keywords: Search-based software engineering;Testing from extended finite state machine (EFSM);Generating feasible transition paths (FTPs);Fitness metric;Test data generation for testing from EFSMs
Issue Date: 2010
Publisher: Brunel University, School of Information Systems, Computing and Mathematics
Abstract: The extended finite state machine (EFSM) is a powerful modelling approach that has been applied to represent a wide range of systems. Despite its popularity, testing from an EFSM is a substantial problem for two main reasons: path feasibility and path test case generation. The path feasibility problem concerns generating transition paths through an EFSM that are feasible and satisfy a given test criterion. In an EFSM, guards and assignments in a path‟s transitions may cause some selected paths to be infeasible. The problem of path test case generation is to find a sequence of inputs that can exercise the transitions in a given feasible path. However, the transitions‟ guards and assignments in a given path can impose difficulties when producing such data making the range of acceptable inputs narrowed down to a possibly tiny range. While search-based approaches have proven efficient in automating aspects of testing, these have received little attention when testing from EFSMs. This thesis proposes an integrated search-based approach to automatically test from an EFSM. The proposed approach generates paths through an EFSM that are potentially feasible and satisfy a test criterion. Then, it generates test cases that can exercise the generated feasible paths. The approach is evaluated by being used to test from five EFSM cases studies. The achieved experimental results demonstrate the value of the proposed approach.
Description: This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.
Appears in Collections:Brunel University Theses
Computer Science
Dept of Computer Science Theses

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