000 04028ntm a2200361 i 4500
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005 20251117113404.0
008 180724s2018 my a f a m 000 0 eng d
020 _aTHE0001130(Local)
039 9 _a201905141125
_bnazirah
_c201904181611
_dnazri
_c201808131536
_dfateeha
_y201807241101
_zfateeha
040 _aUMP
_beng
_cUMP
_erda
090 _aFSKKP .H37 2018 r Thesis
100 1 _aHaque, Ariful,
_eauthor.
245 1 3 _aAn experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion /
_cAriful Haque
264 1 _aKuantan, Pahang :
_bUMP,
_c2018
300 _axii, 95 pages :
_billustrations (some color) ;
_c30 cm. +
_e1 CD ROM
336 _atext
_2rdacontent
336 _atext
_2rdacontent
337 _aunmediated
_2rdamedia
337 _acomputer
_2rdamedia
338 _avolume
_2rdacarrier
338 _acomputer disc
_2rdacarrier
347 _atext file
_bPDF
_2rda
500 _aFaculty of Computer Systems and Software Engineering
502 _aThesis (Master of Science (Software Engineering)) -- Universiti Malaysia Pahang – 2018
504 _aIncludes bibliographical references
520 3 _aSoftware testing is an important part of software development as it ensures the proper functionality of software and reduces the risk of failure. In the case when software is being adopted in a mission critical application, failure can lead to loss of life and fortunes. Therefore, it is mandatory to test all possible functional paths of the software exhaustively. Exhaustive testing is costly and time consuming and with the higher number of inputs, the number of test cases increases exponentially. Many researchers suggested the adoption of Modified Condition / Decision Coverage (MC/DC) criterion as a solution to the problem particularly when the inputs involve Boolean variables. Often, MC/DC can reduce the number of test cases dramatically and ensure critical paths are tested. To generate test cases that satisfy MC/DC criterion, many researchers adopt neighborhood based meta-heuristics algorithms (including that of Simulated Annealing and Hill Climbing) as the problem itself is neighborhood based. Although useful, the existing algorithms does not provide any comparative data to select an algorithm based on the problem size and difficulty and the use of other neighborhood algorithms (including Great Deluge and Late Acceptance Hill Climbing) has not been sufficiently explored as well. In order to identify the strength and weakness of these algorithms for MC/DC compliant test cases, this research proposes an experimental study involving four neighborhoods based meta-heuristic algorithms. We have chosen four neighborhood based algorithms which are commonly used in optimization problems and divided them in newly implemented and re-implemented category. Late Acceptance Hill Climbing (LAHC) and the Great Deluge Algorithm (GDA) which are our new implementation, Simulated Annealing (SA) and Hill Climbing (HC) are re-implemented to generate test cases satisfying MC/DC criterion for comparative analysis. The algorithms are used to generate test cases for nine different Boolean expressions of different size and complexities. Performance of each algorithm is compared in terms of number of test cases generated as well as the run time required. Our experience indicates that all the algorithms generate nearly similar number of test cases, but in terms of performance, they differ from one another. The elaborated result of the study will help test engineers to choose the algorithm they need to generate test cases efficiently and optimally.
610 2 0 _aFaculty of Computer Systems and Software Engineering
_xDissertations
650 0 _aUniversities and colleges
_xDisertations
650 0 _aTheses
999 _aVIRTUA40
_c7830
_d7836
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