Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms by Harmanani, H. M.

“…The method is based on a genetic algorithm that efficiently explores the testable design space and finds a sub-optimal test registers assignment for each k-test session. …”
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An incremental approach for test scheduling and synthesis using genetic algorithms by Harmanani, H.

“…This paper presents a new and an efficient method for concurrent BIST synthesis and test scheduling. This method maximizes concurrent testing of modules while performing the allocation of functional units, test registers, and multiplexers. …”
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A method for test scheduling using an evolutionary approach. (c2000) by Noujaim, Jad

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An incremental approach for test synthesis and scheduling using genetic algorithms. (c2002) by Hajar, Aouni

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A hybrid distributed test generation method using deterministic and genetic algorithms by Harmanani, H.

“…The algorithm is parallelized based on a cluster of workstations using the message passing interface (MPI) library. …”
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Power-constrained system-on-a-chip test scheduling using a genetic algorithm by Harmanani, Haidar M.

“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. …”
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Spatially-Distributed Missions With Heterogeneous Multi-Robot Teams by Eduardo Feo-Flushing (23276023)

“…Both combine a generic MILP solver and a genetic algorithm, resulting in efficient anytime algorithms. …”

Empirical comparison of regression test selection algorithms by Mansour, Nashat

“…The empirical results show that the five algorithms can be used for different requirements of regression testing. …”
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Metaheuristic Algorithm for State-Based Software Testing by Haraty, Ramzi A.

“…We formulate the 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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Natural optimization algorithms for optimal regression testing by Mansour, Nashat

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Tensile Test Optimization Using the Design of Experiment and Soft Computing by Mehdi Moayyedian (14880358)

A comparative study of five regression testing algorithms by Mansour, N.

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Test case generation for path coverage. (c2000) by Salame, Miran

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CoLoSSI: Multi-Robot Task Allocation in Spatially-Distributed and Communication Restricted Environments by Ishaq Ansari (22047902)

“…<p dir="ltr">In our research, we address the problem of coordination and planning in heterogeneous multi-robot systems for missions that consist of spatially localized tasks. Conventionally, this problem has been framed as a task allocation problem that maps tasks to robots. …”

Evolutionary algorithms for state justification in sequential automatic test pattern generation by El-Maleh, Aiman H.

“…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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Metaheuristic algorithm for testing web 2.0 applications. (c2012) by Zeitunlian, Hratch Michel

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Simulated annealing and improved genetic algorithms for path testing. (c1997) by Joumaa, Rania

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A multiobjective optimization method for the SOC Test Time, TAM, and power optimization using a strength pareto evolutionary algorithm by Harmanani, Haidar M.

“…This paper presents a multiobjective optimization approach for the SOC test scheduling problem. The method uses a Strength Pareto Evolutionary Algorithm that minimizes the overall test application time in addition to power, wrapper design and TAM assignment. …”
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Image-Based Air Quality Estimation Using Convolutional Neural Network Optimized by Genetic Algorithms: A Multi-Dataset Approach by Arshad Ali Khan (23152516)

“…This paper proposes a new approach using convolutional neural networks with genetic algorithms for estimating air quality directly from images. …”

Leveraging Machine and Deep Learning Algorithms for hERG Blocker Prediction by Syed Mohammad (21075689)

“…The current study utilises state-of-the-art ML and DL models for predicting the hERG-blocking ability of chemical compounds using a dataset of 8337 molecules. …”