Frameworks for Performing on Cloud Automated Software Testing Using Swarm Intelligence Algorithm: Brief Survey

Hossain, Mohammad Motaher; Abufardeh, Sameer; Kumar, Sumeet

doi:10.25046/aj030229

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…These algorithms are used to reduce the time and cost of testing in general and regression testing in particular. Two such widely used algorithms for prioritizing test cases are the ant colony algorithm and the bee colony optimization [21].…”

Section: Review Of the Scientific Literature On The Subject Of Resear...mentioning

confidence: 99%

Research of intelligent methods of software testing

Kazimov

Bayramova

Malikova

2021

SRIT

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This article presents the examination of several techniques and tools used in the automated software testing process. Considering the ever-growing importance of software testing, several possible implications of implementation of artificial intelligence into this area are also discussed. The main objective of this study is to examine the field of test automation by categorising related test activities, to which artificial intelligence tools can be applied for increased efficiency, and evaluate the impact of the application. The main software testing methods are white-box, black-box, and grey-box methods; an effort has been made to determine a connection between the given testing methods and artificial intelligence methods. A brief summary of several artificial intelligence engine tools used to automate testing was also provided. Lastly, the possible future benefits from usage of AI in software testing was investigated.

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Section: Review Of the Scientific Literature On The Subject Of Resear...mentioning

confidence: 99%

Research of intelligent methods of software testing

Kazimov

Bayramova

Malikova

2021

SRIT

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A Modern Perspective on Cloud Testing Ecosystems

Vijayaraghavan

Singh

Sucharita

2020

Computer Communications and Networks

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Big Data Clustering Mining Based on Swarm Intelligence Algorithm in Cloud Environment

Yan

2022

Mobile Information Systems

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As science and technology progress and develop rapidly in this day and age, various industry applications have changed the data in a new way, and the explosive growth of data has made traditional data mining unable to perform the current data mining work. The aim of this paper is to study the aggregation digging of big data based around flocking automation algorithms under circumstances of cloud. There is a fuzzy-mean aggregation arrangement with mixed frog leaping in this paper. Through simulation analysis of different clustering algorithms, hybrid frog-hopping and as well as the merging arrangement introduced in this paper, it is concluded that the merging algorithm achieves an improvement of up to 90% accuracy on the iritual membrane dataset. It was demonstrated that the arrangement provides effective agglomerations. When the number of iterations is 500, the fitness value of the algorithm on Dataset 1 is 1.59 × 104, and its convergence speed is faster than the other algorithms.

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Frameworks for Performing on Cloud Automated Software Testing Using Swarm Intelligence Algorithm: Brief Survey

Cited by 3 publications

References 25 publications

Research of intelligent methods of software testing

Research of intelligent methods of software testing

A Modern Perspective on Cloud Testing Ecosystems

Big Data Clustering Mining Based on Swarm Intelligence Algorithm in Cloud Environment

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