Browsing by Author "Amir Ngah"

Now showing 1 - 3 of 3
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    Designing a Tool for Software Maintenance
    (International Scholarly and Scientific Research & Innovation, 2015) Amir Ngah; Masita Abdul Jalil; Zailani Abdullah
    The aim of software maintenance is to maintain the software system in accordance with advancement in software and hardware technology. One of the early works on software maintenance is to extract information at higher level of abstraction. In this paper, we present the process of how to design an information extraction tool for software maintenance. The tool can extract the basic information from old programs such as about variables, based classes, derived classes, objects of classes, and functions.
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    IncSPADE
    (Springer International Publishing Switzerland, 2016) Omer Adam; Zailani Abdullah; Amir Ngah; Kasypi Mokhtar; Wan Muhamad Amir Wan Ahmad; Tutut Herawan; Noraziah Ahmad; Mustafa Mat Deris; Abdul Razak Hamdan; Jemal H. Abawajy
    In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. In order to evaluate this algorithm, we conducted the experiments against three different artificial datasets. The result shows that IncSPADE outperformed the benchmarked algorithm called SPADE up to 20%.
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    Regression test selection by exclusion
    (United Kingdom : Durham University, 2012-05) Amir Ngah
    This thesis addresses the research in the area of regression testing. Software systems change and evolve over time. Each time a system is changed regression tests have to be run to validate these changes. An important issue in regression testing is how to minimise reuse the existing test cases of original program for modified program. One of the techniques to tackle this issue is called regression test selection technique. The aim of this research is to significantly reduce the number of test cases that need to be run after changes have been made. Specifically, this thesis focuses on developing a model for regression test selection using the decomposition slicing technique.