Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…This article presents a metaheuristic algorithm for testing software, especially web applications, which can be modeled as a state transition diagram. …”
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Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines by Saleh, Ayat

Subjects: “…Model Based Testing…”
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Modeling, testing, and regression testing of web applications. (c2006) by Al Shaar, Hamzeh K.

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Metaheuristic algorithm for testing web 2.0 applications. (c2012) by Zeitunlian, Hratch Michel

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Modeling and automated blackbox regression testing of web applications by Haraty, Ramzi

“…Having discovered, as well, that there is no automated black box regression testing technique, we also propose a methodology and algorithm to create a tool capable of applying black box regression testing automatically…”
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Design and Implementation of an Advanced Control and Guidance Algorithm of a Single Rotor Helicopter by Al-Omari, Muhannad A. R. I.

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New fault models and efficient BIST algorithms for dual-portmemories by Amin, A.A.

“…New fault models are proposed, and efficient O(n) test algorithms are described for both the memory array and the address decoders. …”
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Combining and adapting software quality predictive models by genetic algorithms by Azar, D.

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Effective uncertain fault diagnosis technique for wind conversion systems using improved ensemble learning algorithm by Khadija Attouri (18024307)

“…<p>This paper introduces a pioneering fault diagnosis technique termed Interval Ensemble Learning based on Sine Cosine Optimization Algorithm (IEL- SCOA), tailored to tackle uncertainties prevalent in wind energy conversion (WEC) systems. …”

Machine Learning-Driven Prediction of Corrosion Inhibitor Efficiency: Emerging Algorithms, Challenges, and Future Outlooks by Najam Us Sahar Riyaz (22927843)

“…At the same time, virtual sample augmentation and genetic algorithm feature selection elevate sparse data performance, raising k-nearest neighbor models from R² = 0.05 to 0.99 in a representative thiophene set. …”

A Hybrid Deep Learning Model Using CNN and K-Mean Clustering for Energy Efficient Modelling in Mobile EdgeIoT by Dhananjay Bisen (19482454)

“…This research proposed a hybrid model for energy-efficient cluster formation and a head selection (E-CFSA) algorithm based on convolutional neural networks (CNNs) and a modified k-mean clustering (MKM) method for MEC. …”

Heuristic Algorithm for Obtaining Approximate Optimum Stratification With Mixture of Ratio and Product Estimators by S. E. H. Rizvi (22052105)

Optimization metaheuristic for software testing by Mansour, Nashat

“…We formulate the web application testing problem as an optimization problem and use a simulated annealing (SA) metaheuristic algorithm to generate test cases as sequences of events while keeping the test suite size reasonable. …”
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Power System Transient Stability Assessment Based on Machine Learning Algorithms and Grid Topology by Senyuk, Mihail

“…This work employs machine learning methods to develop and test a technique for dynamic stability analysis of the mathematical model of a power system. …”
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Design of adaptive arrays based on element position perturbations by Dawoud, M.M.

“…The authors report on the design of a digital feedback control system to provide null steering by controlling the array element positions automatically. …”
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Particle swarm optimization based algorithm for protein structure prediction in the 3D HP model. (c2008) by Kanj, Fatima Hassan

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Modeling and Guidance of an Underactuated Autonomous Underwater Vehicle by Wadi, Ali H M

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Machine Learning Approach for the Design of an Assessment Outcomes Recommendation System by Abu Zitar, Raed

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Logistics Optimization Using Hybrid Genetic Algorithm (HGA): A Solution to the Vehicle Routing Problem With Time Windows (VRPTW) by Ayesha Maroof (17984053)

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The role of Reinforcement Learning in software testing by Amr Abo-eleneen (17032284)

“…</p><h3>Results</h3><p dir="ltr">This study highlights different software testing types to which RL has been applied, commonly used RL algorithms and architecture for learning, challenges faced, advantages and disadvantages of using RL, and the performance comparison of RL-based models against other techniques.…”