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008			191105t20192019my a|||fram|| 000 0 eng d
020			_aTHE0008184(Local) _qhardback
040			_aUMP _beng _cUMP _erda
090			_aFSKKP .N67 2019 r Thesis
100	0		_aNorasyikin Safieny, _eauthor.
245	1	0	_aHybrid test redundancy reduction strategy based on global neighbourhood algorithm and simulated annealing / _cNorasyikin Safieny
264		1	_aKuantan, Pahang : _bUMP, _c2019
264		4	_c© 2019
300			_axii, 90 pages : _billustrations ; _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 & Software Engineering
502			_aThesis (Master of Science) -- Universiti Malaysia Pahang – 2019
504			_aIncludes bibliographical references
520	3		_aSoftware testing is a critical part of software development. Often, test suite sizes grow significantly with subsequent modifications to the software over time resulting into potential redundancies. Test redundancies are undesirable as they incur costs and are not helpful to detect new bugs. Owing to time, resource constraints, test suite minimization strategies are often sought to remove those redundant test cases in an effort to ensure that each test can cover as much requirements as possible. There are already many works in the literature exploiting the greedy computational algorithms as well as the meta-heuristic algorithms, but no single strategies can claim dominance in term of test reduction over their counterparts. Furthermore, despite much useful work, existing strategies has not sufficiently addressed the hybrid based meta-heuristic strategy for test redundancies application. In order to improve the performance of existing strategies, hybridization is seen as the key to exploit the strength of more than one meta-heuristic algorithm. Given such prospects, this research explores a hybrid test redundancy reduction strategy based on Global Neighbourhood Algorithm and Simulated Annealing (GNA_SA), called tReductGNA_SA. For comparative purposes, this research also implements a non-hybrid GNA test redundancy reduction strategy, called tReductGNA, to ascertain that our hybrid strategy outperforms the non-hybrid ones. Additionally, this work also considers realistic combinations of high numbers of requirements and high number of test cases as case studies. Overall, tReductGNA_SA offers more reduction in most cases and give more diversified solutions as compared tReductGNA and many existing works. Specifically, tReductGNA_SA outperforms others with 66.67% (i.e. 2 out of 3 entries) as compared to others strategy at 33.33% (i.e. 1 out of 3 entries).
610	2	0	_aFaculty of Computer System and Software Engineering _xDissertations
650		0	_aUniversities and colleges _xDisertations
650		0	_aTheses
942			_2lcc _cRESTRICT