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47 results for “Software Metric”
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Research ArticleOpen accessIn the keywordsQ-Optimizer: An AI-Based Optimization Framework for Efficient SDN Routing and QoS EnhancementDeepthi Goteti, Vurrury Krishna ReddyWith their rigid layers, traditional networks do not meet evolving traffic demands. As a result, they tend to face congestion along with un-optimized routing. SDN controls traffic management by introducing a programmable control plane, enabling dynamic and intelligent network management. However, older routing techniques, such as Dijkstra's and Multipath, suffer from low adaptability, leading to a rise in latency and … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 2,227 accessesView PDFCite
Research ArticleOpen accessIn the abstractUncertainty-Aware Ensemble Models for Improved Defect Detection in Noisy DataMadhavi Perla, Gadi Lava Raju, A Radha Krishna et al.Software defect prediction plays a crucial role in ensuring software quality and reliability, especially as modern systems become more complex and data rich. This study introduces an uncertainty-aware ensemble learning framework aimed at improving defect classification performance in noisy and imbalanced datasets, particularly those from the PROMISE and NASA KC1 repositories. The proposed model integrates multiple classifiers in a multi-learner … …Journal of Computer Science, Vol. 22, Issue 4 · 27 Apr 2026 · 1,542 accessesView PDFCite
Research ArticleOpen accessIn the abstractIntelligent Software Testing for Test Case Analysis Framework Using ChatGPT with Natural Language Processing and Deep Learning IntegrationAlaa Najmi, Mohamed El-DosukyEffective testing scenarios are necessary to guarantee the dependability and Caliber of software. Conventional techniques for creating these scenarios frequently involve a great deal of manual labor and might not fully cover all software requirements. In order to improve the automation and Caliber of software testing scenario development, this study investigates the combination of Natural Language Processing (NLP) and Deep … …Journal of Computer Science, Vol. 21, Issue 5 · 1 May 2025 · 97,719 accessesView PDFCite
Review ArticleOpen accessIn the abstractDDoS Mitigation Using Machine Learning in Software-Defined NetworksAhmed Gaber Abu Abd-Allah, Noureldin Omar Mohamed, Mohamed Samir Mohamed et al.With the escalating frequency and sophistication of Distributed Denial of Service (DDoS) attacks, the realm of cyber security has witnessed a paradigm shift towards innovative solutions. This review explores the potential of machine learning as a powerful defense mechanism in the field of DDoS mitigation within Software-Defined Networks (SDNs). The study methodically examines a variety of machine learning algorithms used … …Journal of Computer Science, Vol. 21, Issue 4 · 23 Mar 2025 · 6,774 accessesView PDFCite
Research ArticleOpen accessIn the abstractSoftware Development Effort Estimation Using Relational Database and Optimized Learning MechanismRavi Kumar B. N., Yeresime SureshAccurately estimating the cost of software development is crucial for effective project planning and resource allocation. However, traditional cost estimation methods rely heavily on expert judgment and historical data, which can be time consuming and prone to errors. This study suggests a learning-based cost estimation model that leverages relational databases to improve accuracy. The proposed approach estimates project cost based … …Journal of Computer Science, Vol. 19, Issue 4 · 7 Apr 2023 · 6,313 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review of Software Defect Prediction Using Deep LearningAhmed Bahaa, Enas Mohamed Fathy, Ahmed Sharaf Eldin et al.The approaches associated with software defect prediction are used to reduce the time and cost of discovering software defects in source code and to improve the software quality in the organizations. There are two approaches to reveal the software defects in the source code. The first approach is concentrated on the traditional features such as lines of code, code complexity, … …Journal of Computer Science, Vol. 17, Issue 5 · 22 May 2021 · 10,967 accessesView PDFCite
Research ArticleOpen accessIn the abstractSystem Error Estimate using Combination of Classification and Optimization TechniqueKhalid AlattasThe representation of software must produce flawless significances without any inadequacies. Software imperfection evaluations scheme determines defective mechanisms in software. The eventual creation would have minor or negligible shortcomings to harvest great eminence software. Software quality metrics are a division of software metrics that spotlight the quality aspects of the product. The software flaw prediction system helps in the early … …Journal of Computer Science, Vol. 17, Issue 3 · 1 Apr 2021 · 6,588 accessesView PDFCite
Review ArticleOpen accessIn the abstractMachine Learning Techniques for Software Bug Prediction: A Systematic ReviewSyahana Nur’Ain Saharudin, Koh Tieng Wei, Kew Si NaThe goal of software bug prediction is to identify the software modules that will have the likelihood to get bugs by using some fundamental project resources before the real testing starts. Due to high cost in correcting the detected bugs, it is advisable to start predicting bugs at the early stage of development instead of at the testing phase. There … …Journal of Computer Science, Vol. 16, Issue 11 · 14 Nov 2020 · 9,377 accessesView PDFCite
Research ArticleOpen accessIn the abstractA VF-IMF Cohesion Metric for Object-Oriented ClassesJoy Christy Antony Sami, Umamakeswari ArumugamCohesion in Object Oriented (OO) modules impact reusability, efficiency and complexity of software. OO Programmers are mandated to create software with high cohesion. The testing phase in Software Development Life Cycle (SDLC) is not only concerned about creating error free software but also assess quality of code through software metrics. The metric‘Lack of Cohesion in Methods (LCOM)’ is one of … …Journal of Computer Science, Vol. 16, Issue 4 · 10 Apr 2020 · 8,246 accessesView PDFCite
Research ArticleOpen accessIn the abstractGreedy Algorithm Implementation for Test Case Prioritization in the Regression Testing PhaseAkira Wahyu Putra, Nilo LegowoThis study examines the implementation of Test Case Prioritization (TCP) using the Greedy Algorithm (GA) to enhance regression testing efficiency within a financial technology company's software development cycle. With testing durations increasing significantly, this study aims to address inefficiencies by applying the Greedy Algorithm to optimize test suite size and fault detection. The research methodology involves applying the Greedy Algorithm … …Journal of Computer Science, Vol. 21, Issue 2 · 9 Jan 2025 · 7,558 accessesView PDFCite