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  1. 1
    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs

    Evolutionary cost-cognizant regression test case prioritization for object-oriented programs by Bello, AbdulKarim

    Published 2019
    “…Therefore, this study proposed a cost-cognizant TCP approach for object-oriented software that uses path-based integration testing to identify the possible execution path extracted from the Java System Dependence Graph (JSDG) model of the source code using forward slicing technique. …”
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  2. 2
    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer

    Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer by Ahmad Nezer, Nurul Aqilah

    Published 2017
    “…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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  3. 3
    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization

    Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

    Published 2019
    “…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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  4. 4
    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment

    Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment by Shaliza Hayati A. Wahab, Nordin Saad, Azali Saudi, Ali Chekima

    Published 2021
    “…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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  5. 5
    Smart appointment organizer for mobile application / Mohd Syafiq Adam

    Smart appointment organizer for mobile application / Mohd Syafiq Adam by Adam, Mohd Syafiq

    Published 2009
    “…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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  6. 6
    CSC126 - Fundamentals of Algorithms and Computer Problem Solving / Faculty of Computer And Mathematical Sciences

    CSC126 - Fundamentals of Algorithms and Computer Problem Solving / Faculty of Computer And Mathematical Sciences by UiTM, Faculty of Computer And Mathematical Sciences

    Published 2023
    “…This course is an introduction to problem solving using a computer programming language. …”
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    Teaching Resource
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  7. 7
    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language

    Algorithm As A Problem Solving Technique For Teaching And Learning Of The Malay Language by Jano, Zanariah, Omar, Norliza, Nazir, Faridah

    Published 2019
    “…The students were to arrange the basic words into grammatical sentences based on the scratch program and write a cake recipe using an algorithmic technique, a series of instructions contained in the scratch program. …”
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  8. 8
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Faridah Nazir, Zanariah Jano, Norliza Omar

    Published 2019
    “…The students were to arrange the basic words into grammatical sentences based on the scratch program and write a cake recipe using an algorithmic technique, a series of instructions contained in the scratch program. …”
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  9. 9
    Algorithm as a problem solving technique for teaching and learning of the Malay language

    Algorithm as a problem solving technique for teaching and learning of the Malay language by Nazir, Faridah, Jano, Zanariah, Omar, Norliza

    Published 2019
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    Proceeding Paper
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  10. 10
    Comparison Between Linear Programming And Integer Linear Programming: A Review

    Comparison Between Linear Programming And Integer Linear Programming: A Review by Sam, Mei Lee, Saptari, Adi, Salleh, Mohd Rizal, Mohamad, Effendi

    Published 2018
    “…Three criteria were used to evaluate the characteristics: time complexity, problem size and computational time. …”
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  11. 11
    Development of dynamic programming algorithm for maintenance scheduling problem

    Development of dynamic programming algorithm for maintenance scheduling problem by Zafira Adlia, Mohd Fauzi

    Published 2020
    “…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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  12. 12
    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO)

    System program management environment in cloud computing using hybrid Genetic Algorithm and Moth Flame Optimization (GA-MFO) by Mohd Erwan Mazalan

    Published 2022
    “…Optimization algorithms can be used to solve Non-deterministic Polynomial (NP) hard problem like system management. …”
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    Academic Exercise
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  13. 13
    Using genetic algorithm for solving N-Queens problem

    Using genetic algorithm for solving N-Queens problem by Turky A.M., Ahmad M.S.

    Published 2023
    Conference paper
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  14. 14
    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms

    Optimal power flow based on fuzzy linear programming and modified Jaya algorithms by Alzihaymee, Warid Sayel Warid

    Published 2017
    “…The first proposed approach is a multi-objective fuzzy linear programming optimization (MFLP) algorithm to solve the MOOPF problem. …”
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  15. 15
    Building an Algorithm for Measuring C Programming Assignments Quality

    Building an Algorithm for Measuring C Programming Assignments Quality by Muhd Zulhafriz Aadel bin Marzuki, Muhd Zulhafriz

    Published 2008
    “…The tested programming language is C considering the problems in grading programming assignments are directly related with this subject in UTP.…”
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    Final Year Project
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  16. 16
    Overview of metaheuristic: classification of population and trajectory

    Overview of metaheuristic: classification of population and trajectory by Zainul Rashid, Zarina

    Published 2010
    “…Algorithms are used to find the solutions through the computer program. …”
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    Monograph
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  17. 17
    Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq

    Modeling a problem solving approach through computational thinking for teaching programming / Zebel Al Tareq by Zebel , Al Tareq

    Published 2021
    “…This study aims to investigate teaching issues in solving programming problems and find the right approach to teach programming using a suitable problem solving approach method. …”
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  18. 18
    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
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  19. 19
    Agent-based extraction algorithm for computational problem solving

    Agent-based extraction algorithm for computational problem solving by Rajabi, Maryam

    Published 2015
    “…Modeling Computational Problem Solving (CPS) is the main issue in teaching programming where the given text is needed to be transformed into a model then later into a programming language. …”
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  20. 20
    Different mutation and crossover set of genetic programming in an automated machine learning

    Different mutation and crossover set of genetic programming in an automated machine learning by Masrom, S., Mohamad, M., Hatim, S.M., Baharun, N., Omar, N., Abd. Rahman, A.S.

    Published 2020
    “…As a family of evolutionary based algorithm, the effectiveness of Genetic Programming in providing the best machine learning pipelines for a given problem or dataset is substantially depending on the algorithm parameterizations including the mutation and crossover rates. …”
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