Rozmie Razif Othman
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Preferred name
Rozmie Razif Othman
Official Name
Rozmie Razif, Othman
Alternative Name
Razif Othman, Rozmie
Othman, Rozmie R.
Othman, Rozmie Razif Bin
Othman, R. R.
Razif bin Othman, Rozmie
Main Affiliation
Scopus Author ID
36873148100
Researcher ID
GCW-7915-2022

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  • Publication
    Adopting Ant Colony Optimization Algorithm for Pairwise T-Way Test Suite Generation Strategy
    ( 2021-07-26)
    Nuraminah Ramli
    ;
    Rozmie Razif Othman
    ;
    Hendradi R.
    ;
    Fauzi S.S.M.
    ;
    Ismail I.
    ;
    Mohd Zamri Zahir Ahmad
    ;
    Mohd Wafi Nasrudin
    Combinatorial testing or t-way testing (t represents strength) is useful to detect faults due to interactions. Pairwise testing is one type of t-way testing. The technique is effective in reducing the number of test cases without decreasing the level of coverage. Besides, its purpose is to overcome the problem of exhaustive testing that produces a great number of test cases and is impossible to be implemented due to time and cost constraints. Pairwise T-way Test Suite Generation Strategy based on Ant Colony Optimization (pTTSGA) is introduced to generate a near-optimum test suite size. Experiments have been conducted to evaluate the ability of this strategy for pairwise testing. The results are compared to benchmark results. Overall, pTTSGA produces a comparable test suite size.
  • Publication
    Ant colony algorithm to generate t-way test suite with constraints
    ( 2020-06-17)
    Nuraminah Ramli
    ;
    Rozmie Razif Othman
    ;
    Khalib Z.I.A.
    ;
    Mohd Zamri Zahir Ahmad
    ;
    Fauzi S.S.M.
    T-way testing is one of the testing techniques offered to generate test suites. It focuses on interactions of input parameters based on strength. Besides that, t-way is used to overcome exhaustive testing problem. Another important aspect in t-way is constraints. It forbids certain interactions of input parameters. Therefore, the final test suite contains only valid interactions. T-way testing is NP-hard problem. No single strategy can always generates the best test suite size at all time for all configurations. Thus, Const-TTSGA strategy has been developed to generate test suites. The strategy supports constraints variable strength. Const-TTSGA is a metaheuristic strategy which applies ant colony algorithm to generate the best test cases. Two types of experiments have been conducted; constraints uniform and variable strength which consists of few other configurations. Results obtained are compared to benchmarked results. Const-TTSGA outperformed other strategy for costraints uniform strength experiments except for one configuration. However, the strategy outperformed other strategies for constraints variable strength experiments.
  • Publication
    Ant colony algorithm to generate t-way test suite with constraints
    ( 2020-06-17)
    Nuraminah Ramli
    ;
    Rozmie Razif Othman
    ;
    Zahereel Ishwar Abdul Khalib
    ;
    Zahereel Ishwar Abdul Khalib
    ;
    Fauzi S.S.M.
    T-way testing is one of the testing techniques offered to generate test suites. It focuses on interactions of input parameters based on strength. Besides that, t-way is used to overcome exhaustive testing problem. Another important aspect in t-way is constraints. It forbids certain interactions of input parameters. Therefore, the final test suite contains only valid interactions. T-way testing is NP-hard problem. No single strategy can always generates the best test suite size at all time for all configurations. Thus, Const-TTSGA strategy has been developed to generate test suites. The strategy supports constraints variable strength. Const-TTSGA is a metaheuristic strategy which applies ant colony algorithm to generate the best test cases. Two types of experiments have been conducted; constraints uniform and variable strength which consists of few other configurations. Results obtained are compared to benchmarked results. Const-TTSGA outperformed other strategy for costraints uniform strength experiments except for one configuration. However, the strategy outperformed other strategies for constraints variable strength experiments.
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