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1
Natural optimization algorithms for optimal regression testing
Published 1997“…The optimal regression testing problem is that of determining the minimum number of test cases needed for revalidating modified software in the maintenance phase. …”
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2
Metaheuristic Algorithm for State-Based Software Testing
Published 2018“…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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3
A comparative study of five regression testing algorithms
Published 1997“…The comparison is based on the following ten quantitative and qualitative criteria: execution time, number of selected retests, precision, inclusiveness, user parameters, handling of global variables, type of maintenance, type of testing, level of testing, and type of approach. The experimental results show that the five algorithms are suitable for different requirements of regression testing. …”
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4
Simulated Annealing and Genetic Algorithms for Optimal Regression Testing
Published 1999“…The experimental results, which include a comparison with previous algorithms, show that the simulated annealing and genetic algorithms find the optimal or near-optimal number of retests within a reasonable time. …”
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5
A genetic algorithm for corrective retesting. (c1995)
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6
Simulated annealing and improved genetic algorithms for path testing. (c1997)
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7
Test Vector Decomposition Based Static Compaction Algorithms for Combinational Circuits
Published 2003“…Experimental results for benchmark circuits demonstrate the effectiveness of the two new static compaction algorithms.…”
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8
Metaheuristic algorithm for testing web 2.0 applications. (c2012)
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Power-constrained system-on-a-chip test scheduling using a genetic algorithm
Published 2006“…This paper presents an efficient approach for the test scheduling problem of core-based systems based on a genetic algorithm. …”
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11
Performance assessment and exhaustive listing of 500+ nature-inspired metaheuristic algorithms
Published 2023“…All the experimental results are analyzed by several nonparametric statistical methods, including the Bayesian rank-sum test, Friedman test, Wilcoxon signed-rank test, critical difference plot and Bayesian signed-rank test. …”
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A multiobjective optimization method for the SOC Test Time, TAM, and power optimization using a strength pareto evolutionary algorithm
Published 2017“…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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Test time minimization for system-on-chip with test bus assignment and sizin
Published 2017“…In this paper, we propose a genetic algorithm to design test access architectures while investigating test bus sizing concurrently with assigning cores to test buses. …”
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15
Predicting Compression Modes and Split Decisions for HEVC Video Coding Using Machine Learning Techniques
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16
Optimization metaheuristic for software testing
Published 2013“…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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17
Experimental Investigation and Comparative Evaluation of Standard Level Shifted Multi-Carrier Modulation Schemes With a Constraint GA Based SHE Techniques for a Seven-Level PUC Inv...
Published 2019“…For better understanding, the converter topology is tested under different dynamic conditions. Mathematical background developed on the theoretical basis is verified by numerical simulation software and also validated on the developed laboratory-scale prototype experimental setup.…”
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Robustness testing of composed real-time systems
Published 2010“…Each tester is dedicated to test a single SUT component. A test execution algorithm is presented. …”
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Large language models for code completion: A systematic literature review
Published 2024“…Different techniques can achieve code completion, and recent research has focused on Deep Learning methods, particularly Large Language Models (LLMs) utilizing Transformer algorithms. …”
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Test bus assignment, sizing, and partitioning for system-on-chip
Published 2007“…Efficient TAM design is of critical importance in system-on-chip integration since it directly impacts testing time and hardware cost. In this paper, an efficient genetic algorithm for designing test access architectures while investigating test bus sizing and concurrently assigning cores to test buses is proposed. …”
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