Evaluation of various training algorithms in a neural network model for software engineering applications

Authors:
K. K. Aggarwal;Yogesh Singh;Pravin Chandra;Manimala Puri
Affiliations:
GGS Indraprastha University, Delhi, India;GGS Indraprastha University, Delhi, India;GGS Indraprastha University, Delhi, India;D.Y.Patil, COE, Pune, India
Venue:
ACM SIGSOFT Software Engineering Notes
Year:
2005

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Abstract

Software Engineering as a discipline emerged in response to the software crisis perceived by the industry. It is a well known fact that at the beginning of any project, the software industry needs to know how much will it cost to develop and what would be the time required. Resource estimation in software engineering is more challenging than resource estimation in any other industry. A number of resource estimation methods are currently available and the neural network model is one of them. This paper proposes to evaluate various training algorithms in a neural network model and shows which is the best suited for software engineering applications.