Search Results - (( programming using prioritization algorithm ) OR ( java data optimization algorithm ))

Refine Results
  1. 1
  2. 2

    Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2015
    “…And even though several of the code based addresses procedural programs. Some researchers addressed the issue of test case prioritization using Genetic Algorithm, but the authors do not select modification-revealing before prioritization and used the same fault severity. …”
    Get full text
    Get full text
    Conference or Workshop Item
  3. 3
  4. 4

    A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
    Get full text
    Get full text
    Get full text
    Undergraduates Project Papers
  6. 6

    Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

    Published 2022
    “…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
    Get full text
    Get full text
    Article
  7. 7
  8. 8

    The effect of replacement strategies of genetic algorithm in regression test case prioritization of selected test cases by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2015
    “…Design-based regression testing approaches have been proposed to address changes at higher levels of abstraction, these approaches may not detect changes in the method body and several of the code based addresses procedural programs. This study presents an optimized regression test case prioritization of selected test cases for object-oriented software using Genetic algorithm with different replacement strategies. …”
    Get full text
    Get full text
    Get full text
    Article
  9. 9

    Regression test case selection & prioritization using dependence graph and genetic algorithm by Musa, Samaila, Md Sultan, Abu Bakar, Abd Ghani, Abdul Azim, Baharom, Salmi

    Published 2014
    “…The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
    Get full text
    Get full text
    Article
  10. 10

    A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2011
    “…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  11. 11
  12. 12
  13. 13
  14. 14

    EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

    Published 2013
    “…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  15. 15

    An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

    Published 2015
    “…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Prioritizing event sequences test cases based on faults by Baharom, Salmi, Ahmad, Johanna, Zulzalil, Hazura, Din, Jamilah, Abd Ghani, Abdul Azim

    Published 2018
    “…An experiment has been conducted using one subject program taken from the benchmark source for a comparative study. …”
    Get full text
    Get full text
    Get full text
    Article
  18. 18
  19. 19

    Late Acceptance Hill Climbing Based Strategy for Test Redundancy Reduction and Prioritization by Rohani, Abu Bakar, Kamal Z., Zamli, Basem, Al-Kazemi

    Published 2015
    “…LAHCS is the first known strategy that adopts Late Acceptance Hill Climbing Algorithm for test redundancy reduction and prioritization.…”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  20. 20

    A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm by Ba-Quttayyan, Bakr Salim Abdullah

    Published 2024
    “…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis