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Software test effort estimation: a model based on cuckoo search

Authors:

Praveen Ranjan Srivastava,

Abhishek Varshney,

Xin-She YangAuthors Info & Claims

International Journal of Bio-Inspired Computation, Volume 4, Issue 5

Pages 278 - 285

https://doi.org/10.1504/IJBIC.2012.049888

Published: 01 October 2012 Publication History

Abstract

Test effort estimation is the process of predicting effort for testing the software. It has always been a fascinating area for software engineering researchers. "How long will it take to test the system?" is the most promising question in minds of testers before the testing process actually starts. Many factors such as the productivity of the test team, strategy chosen for testing, the size and complexity of the system, technical factors, and expected quality can affect test effort estimation. Testing requires a good amount of time and effort in the entire software development life cycle. Several researches have attempted to develop test effort estimation models but still it is not possible to achieve accurate forecasting. A new model based on a metaheuristic technique called, cuckoo search, for estimating the test effort is proposed in this paper. The proposed model is used to assign weights to the various factors involved based on past results, and, is then used for predicting the test effort for new projects of similar kind.

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Cited By

Kaur AKaur K(2022)A COSMIC function points based test effort estimation model for mobile applicationsJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2019.03.00134:3(946-963)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.jksuci.2019.03.001
Kaur AKaur K(2022)Systematic literature review of mobile application development and testing effort estimationJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2018.11.00234:2(1-15)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.jksuci.2018.11.002
Bluemke IMalanowska A(2021)Software Testing Effort Estimation and Related ProblemsACM Computing Surveys10.1145/344269454:3(1-38)Online publication date: 17-Apr-2021
https://dl.acm.org/doi/10.1145/3442694
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Published In

cover image International Journal of Bio-Inspired Computation

International Journal of Bio-Inspired Computation Volume 4, Issue 5

October 2012

73 pages

ISSN:1758-0366

EISSN:1758-0374

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Publisher

Inderscience Publishers

Geneva 15, Switzerland

Publication History

Published: 01 October 2012

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Cited By

Kaur AKaur K(2022)A COSMIC function points based test effort estimation model for mobile applicationsJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2019.03.00134:3(946-963)Online publication date: 1-Mar-2022
https://dl.acm.org/doi/10.1016/j.jksuci.2019.03.001
Kaur AKaur K(2022)Systematic literature review of mobile application development and testing effort estimationJournal of King Saud University - Computer and Information Sciences10.1016/j.jksuci.2018.11.00234:2(1-15)Online publication date: 1-Feb-2022
https://dl.acm.org/doi/10.1016/j.jksuci.2018.11.002
Bluemke IMalanowska A(2021)Software Testing Effort Estimation and Related ProblemsACM Computing Surveys10.1145/344269454:3(1-38)Online publication date: 17-Apr-2021
https://dl.acm.org/doi/10.1145/3442694
Kaur AKaur K(2019)Investigation on test effort estimation of mobile applicationsInformation and Software Technology10.1016/j.infsof.2019.02.003110:C(56-77)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1016/j.infsof.2019.02.003
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https://dl.acm.org/doi/10.1504/IJBIC.2018.093328
de Sousa Ade Sousa Santos IAragão Bde Castro Andrade RMalucelli AReinehr S(2018)Towards an automatic approach to estimating test effortProceedings of the XVII Brazilian Symposium on Software Quality10.1145/3275245.3275273(305-314)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3275245.3275273
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https://dl.acm.org/doi/10.1504/IJISTA.2016.076102
Djelloul HLayeb AChikhi S(2015)Quantum inspired cuckoo search algorithm for graph colouring problemInternational Journal of Bio-Inspired Computation10.1504/IJBIC.2015.0695547:3(183-194)Online publication date: 1-May-2015
https://dl.acm.org/doi/10.1504/IJBIC.2015.069554
Zhang YZhang S(2014)Software quality evaluation and forecast based on unascertained-SVR modelInternational Journal of Wireless and Mobile Computing10.1504/IJWMC.2014.0597167:2(194-199)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1504/IJWMC.2014.059716
Yang XCui Z(2014)Bio-inspired computationInternational Journal of Bio-Inspired Computation10.1504/IJBIC.2014.0599696:1(1-6)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1504/IJBIC.2014.059969
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