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Showing 1 - 20 results of 306 for search '(((( data deer algorithm ) OR ( based testing algorithm ))) OR ( element could algorithm ))', query time: 0.12s Refine Results
  1. 1
    Genetic algorithm based test data generator

    Genetic algorithm based test data generator by Hermadi, Irman

    Published 2004
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  2. 2
    Metaheuristic Algorithm for State-Based Software Testing

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

    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. 3
    Web Applications Security Testing: Genetic Algorithms Based Test Data Generator

    Web Applications Security Testing: Genetic Algorithms Based Test Data Generator by unknown

    Published 2020
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  4. 4
    Efficient static test compaction algorithms for combinational circuits based on test relaxation

    Efficient static test compaction algorithms for combinational circuits based on test relaxation by Osais, Yahya Esmail

    Published 2003
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  5. 5
    Test Vector Decomposition Based Static Compaction Algorithms for Combinational Circuits

    Test Vector Decomposition Based Static Compaction Algorithms for Combinational Circuits by El-Maleh, Aiman H.

    Published 2003
    “…In this paper, a new approach to static compaction for combinational circuits, referred to as test vector decomposition (TVD), is proposed. In addition, two new TVD based static compaction algorithms are presented. …”
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  6. 6
    Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines

    Incremental and Heuristic Algorithms for Deriving Adaptive Distinguishing Test Cases for Nondeterministic Finite State Machines by Saleh, Ayat

    Published 2017
    Subjects: “…Model Based Testing…”
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  7. 7
    Automated Mutation-Based Test Data Generation: Genetic Algorithm Game-Like Approach

    Automated Mutation-Based Test Data Generation: Genetic Algorithm Game-Like Approach by unknown

    Published 2020
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  8. 8
    Empirical comparison of regression test selection algorithms

    Empirical comparison of regression test selection algorithms by Mansour, Nashat

    Published 2001
    “…In this paper, we empirically compare five representative regression test selection algorithms, which include: Simulated Annealing, Reduction, Slicing, Dataflow, and Firewall algorithms. …”
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  9. 9
    Natural optimization algorithms for optimal regression testing

    Natural optimization algorithms for optimal regression testing by Mansour, Nashat

    Published 1997
    “…The algorithms are based on an integer programming problem formulation and the program's control-flow graph. …”
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  10. 10
    A comparative study of five regression testing algorithms

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

    Published 1997
    “…We compare five regression testing algorithms that include: slicing, incremental, firewall, genetic and simulated annealing algorithms. …”
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  11. 11
    Simulated Annealing and Genetic Algorithms for Optimal Regression Testing

    Simulated Annealing and Genetic Algorithms for Optimal Regression Testing by Mansour, Nashat

    Published 1999
    “…The algorithms are based on an integer programming problem formulation and the program’s control flow graph. …”
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  12. 12
    An incremental approach for test scheduling and synthesis using genetic algorithms

    An incremental approach for test scheduling and synthesis using genetic algorithms by Harmanani, H.

    Published 2017
    “…The method is based on a genetic algorithm that efficiently explores the testable design space. …”
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  13. 13
    Concurrent BIST Synthesis and Test Scheduling Using Genetic Algorithms

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

    Published 2007
    “…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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  14. 14
    A genetic algorithm for corrective retesting. (c1995)

    A genetic algorithm for corrective retesting. (c1995) by Fakih, Khaled A.

    Published 1995
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  15. 15
    Metaheuristic algorithm for testing web 2.0 applications. (c2012)

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

    Published 2012
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  16. 16
    Evolutionary algorithms for state justification in sequential automatic test pattern generation

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

    Published 2005
    “…Sequential circuit test generation using deterministic, fault-oriented algorithms is highly complex and time consuming. …”
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  17. 17
    Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests

    Trial-based dominance for comparing both the speed and accuracy of stochastic optimizers with standard non-parametric tests by Kenneth V. Price (17877002)

    Published 2023
    “…<p>Non-parametric tests can determine the better of two stochastic optimization algorithms when benchmarking results are ordinal—like the final fitness values of multiple trials—but for many benchmarks, a trial can also terminate once it reaches a prespecified target value. …”
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  18. 18
    Regression testing web services-based applications

    Regression testing web services-based applications by Tarhini, Abbas

    Published 2006
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  19. 19
    UML-based regression testing for OO software

    UML-based regression testing for OO software by Mansour, Nashat

    Published 2010
    “…When working with large and complex object-oriented systems, source code-based regression testing is usually costly. This paper proposes a programming-language-independent technique for regression test selection for object-oriented software based on Unified Modeling Language (UML 2.0) design diagrams. …”
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  20. 20
    A hybrid distributed test generation method using deterministic and genetic algorithms

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

    Published 2017
    “…The deterministic phase is based on the D-algorithm and generates an initial set of test vectors that are evolved in the genetic phase in order to achieve high fault coverage in a short time. …”
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