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An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion
Published 2018“…The algorithms are used to generate test cases for nine different Boolean expressions of different size and complexities. …”
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Automated path testing using the negative selection algorithm
Published 2017“…Negative selection algorithm (NSA) has been used in this paper to generate test data for path testing automatically. …”
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PSAT : a pairwise test data generation tool based on simulated annealing algorithm
Published 2015“…In this research, the test case will be generated based on the SA algorithm to show that the test case can be generated with sufficient.…”
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4
Automatic generation of user-defined test algorithm description file for memory BIST implementation
Published 2022“…This paper presents the development of software that automatically generates a description file of a UDA to be deployed for memory BIST circuit implementation using Tessent memory BIST software. …”
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Test suite generation based on hybrid flower pollination algorithm and hill climbing
Published 2021“…In this research paper, we propose a new software t-way testing tool based on hybrid Flower Pollination Algorithm and Hill Climbing for generating test suite generation, called FPA-HC strategy can be used for generating smaller test suite size. …”
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Faculty timetabling using genetic algorithm
Published 2011“…Faculty Timetabling using Genetic Algorithm (FTGA) is an application that generate optimum timetable for faculty.The target user of this application is faculty staff who responsible in generate timetable.The problem statement of the project is many clashing exist in the timetable.Faculty staff needs to solve the clashing manually.This will waste time and it is a problem for staff to solve the clashing.By implement GA,clashing will be reduced.The objective of the project is to develop aprototype in scheduling application for generates an optimum timetable for a faculty.Genetic algorithm will be implemented.The scope of FTGA is Faculty of Computer Systems & Software Engineering (FCSSE).The methodology use in this project is prototype model.The testing result show 95 out of 100 test cases achieved the maximum fitness value which means there is no clashing in the timetable.The maximum generation is set to 15 generation.Population for each generation is 3 populations.Percentage of FTGA solve the problem is 95%.…”
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Undergraduates Project Papers -
7
Implementing a T-Way Test Generation Strategy Using Bees Algorithm
Published 2013“…In order to ensure software performance as well as software quality, various testing techniques have been used to detect faults as early and as many as possible during the development phase. …”
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Sequence t-way test generation using the barnacles mating optimizer algorithm
Published 2021“…More precisely, we focus on the generation of test cases due to the ordering of inputs (or sequence) using the newly developed Barnacles Mating Optimizer (BMO) Algorithm. …”
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Pairwise test suite generator tool based on harmony search algorithm (HS-PTSGT)
Published 2014“…This thesis is about the research on developing a pairwise test suite generator tool based on Harmony Search Algorithm (HS-PTSGT) to generate optimum test suite. …”
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Development of automated neighborhood pattern sensitive faults syndrome generator for static random access memory
Published 2011“…The algorithms used in this generator are based on March algorithm. …”
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A random search based effective algorithm for pairwise test data generation
Published 2011“…Java program has been used to test the performance of the algorithm. The algorithm is able to support both uniform and non-uniform values effectively with performance better than the existing algorithms/tools in terms of number of generated test cases and time consumption.…”
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An improved algorithm in test case generation from UML activity diagram using activity path
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…A three-dimensional model consisting of the drilling process and pocket milling process was developed using Solidworks software. Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…A three-dimensional model consisting of the drilling process and pocket milling process was developed using Solidworks software. Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…A three-dimensional model consisting of the drilling process and pocket milling process was developed using Solidworks software. Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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MINIMIZATION OF MACHINING PROCESS SEQUENCE BASED ON ANT COLONY ALGORITHM AND CONVENTIONAL METHOD
Published 2023“…A three-dimensional model consisting of the drilling process and pocket milling process was developed using Solidworks software. Matlab software was used to develop the algorithm based on Ant Colony, which was then used to optimize the process sequence. …”
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Repetitive mutations in genetic algorithm for software test data generations
Published 2022“…Generating test data is the most important part of dynamic software testing. …”
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EasyA: Easy and effective way to generate pairwise test data
Published 2013“…Java program has been used to test the performance of the algorithm. The performance is better than the existing algorithms/tools in terms of number of generated test cases and time consumption.…”
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Sequence and sequence-less t-way test suite generation strategy based on the elitist flower pollination algorithm
Published 2018“…In line with the emerging field called Search based Software Engineering, many recently developed t-way strategies have adopted meta-heuristic algorithms as the basis of their implementations such as Simulated Annealing, Genetic Algorithm, Ant Colony Optimization Algorithm, Particle Swarm Optimization, Harmony Search and Cuckoo Search, owing their superior performance in term of test size reduction as compared to general computational based strategies, such as General t-way, Test Vector Generator, In Parameter Order General, Jenny, and Automatic Efficient Test Generator. …”
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