Journal of Software Engineering and Applications

Journal of Software Engineering and Applications

ISSN Print: 1945-3116
ISSN Online: 1945-3124
www.scirp.org/journal/jsea
E-mail: jsea@scirp.org
"Test Effort Estimation Using Neural Network"
written by Chintala Abhishek, Veginati Pavan Kumar, Harish Vitta, Praveen Ranjan Srivastava,
published by Journal of Software Engineering and Applications, Vol.3 No.4, 2010
has been cited by the following article(s):
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[1] Machine learning techniques for software testing effort prediction
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[2] Software Testing Effort Estimation and Related Problems: A Systematic Literature Review
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[3] Evolutionary neural network classifiers for software effort estimation
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[4] Investigation on Test Effort Estimation of Mobile Applications: Systematic Literature Review and Survey
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[5] Effort Estimation for Performance Testing of Software Applications
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[6] Bankacılık Alanında Kişisel Yazılım Test Eforunu Tahmin Etmek İçin Proxy Tabanlı Bir Metot Ve Vaka Çalışması
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[7] Systematic Literature Review of Mobile Application Development and Testing Effort Estimation
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[12] An empirical study of test effort estimation based on bat algorithm
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[13] Test effort: A pre-conceptual-schema-based representation
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[14] Un método para medir la productividad del equipo de pruebasen la estimación del esfuerzo de pruebas de software
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[15] A Survey of Software Test Estimation Techniques
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[17] A Software Measurement Using Artificial Neural Network and Support Vector Machine
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[19] Software test effort estimation: a model based on cuckoo search
International Journal of Bio-Inspired Computation, 2012
[20] Functional Link Artificial Neural Networks for Software Cost Estimation
International Journal of Applied Evolutionary Computation (IJAEC), 2012
[21] Optimal Software Release Using Time and Cost Benefits via Fuzzy Multi-Criteria and Fault Tolerance.
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[22] Effort Analysis of Unit Testing Conducted by Non-Developer of Source Code
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[23] Neuroph: An open source software framework for neural network development
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[24] Optimal software release using time and cost benefits via fuzzy multi-criteria and fault tolerance
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[25] 원개발자 부재에 따른 원시코드 기반의 단위테스트 노력 분석
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