Search Results - (( programming using replication algorithm ) OR ( java based prioritization algorithm ))
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Multi-criteria evolutionary regression test prioritization for dynamic object-oriented programs
Published 2019“…Index terms - Regression testing, multi-criteria, test case, test case prioritization, Python, genetic algorithm.…”
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A framework of test case prioritisation in regression testing using particle swarm-artificial bee colony algorithm
Published 2024“…The developed framework, grounded in fault-based testing theory, comprises three key components: inputs, prioritization factors, and a prioritization algorithm. …”
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Adaptive persistence layer for synchronous replication (PLSR) in heterogeneous system
Published 2011“…The PLSR architecture model, workflow and algorithms are described. The PLSR has been developed using Java Programming language. …”
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Hybrid genetic algorithm for improving fault localization
Published 2018“…The result of the experiment shows that our technique able to detect multiple faults in various java programs but there is a need for improvement especially in prioritize fault that occurs simultaneously.…”
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Evolutionary cost-cognizant regression test case prioritization for object-oriented programs
Published 2019“…Afterward evolutionary algorithm (EA) was employed to prioritize test cases based on the rate severity of fault detection per unit test cost. …”
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A cluster-based hybrid replica control protocol for high availability in data grid
Published 2019“…The performance of CBH protocol is evaluated theoretically and using simulations. A discrete event simulator called GridSim and Java programming language is used to simulate the proposed protocol. …”
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An Enhanced Simulated Annealing Routing Algorithm for Semi-Diagonal Torus Network
Published 2017“…The solution is further refined by re-routing all nets in different orders using simulated annealing method. Through simulation program, our proposed algorithm succeeded in performing complete routing up to 81 nodes with 40 nets in 9×9 SD-Torus network size.…”
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Enhancing teaching and learning through data-driven optimization of servicing code demand and lecturer allocation using WEKA analysis
Published 2025“…Furthermore, classification using the Random Forest algorithm depicted that a 95.3% accuracy (k=0.768), confirming robust predictive capability in identifying course approval status and demand trends. …”
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