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K. K. Agarwal, P. Chandra, et al., “Evaluation of Various Training Algorithms in a Neural Network Model for Software Engineering Applications,” ACM SIGSOFT Software Engineering Notes, Vol. 30, No. 4, July 2005, pp. 1-4.

has been cited by the following article:

• TITLE: Test Effort Estimation Using Neural Network

  AUTHORS: Chintala Abhishek, Veginati Pavan Kumar, Harish Vitta, Praveen Ranjan Srivastava

  KEYWORDS: Test Effort Estimation, Neural Network, Use Case Points, Halstead Model

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.3 No.4, May 6, 2010

  ABSTRACT: In software industry the major problem encountered during project scheduling is in deciding what proportion of the resources has allocated to the testing phase. In general it has been observed that about 40%-50% of the resources need to be allocated to the testing phase. However it is very difficult to predict the exact amount of effort required to be allocated to testing phase. As a result the project planning goes haywire. The project which has not been tested sufficiently can cause huge losses to the organization. This research paper focuses on finding a method which gives a measure of the effort to be spent on the testing phase. This paper provides effort estimates during pre-coding and post-coding phases using neural network to predict more accurately.