A fuzzy logic model for predicting the development effort of short scale programs based upon two independent variables

  • Authors:

  • Cuauhtemoc Lopez-Martin

  • Affiliations:

  • Information Systems Department, CUCEA, Guadalajara University, Jalisco, P.O. Box 45100, Mexico

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2011

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Abstract

Fuzzy models have been recently used for estimating the development effort of software projects and this practice could start with short scale programs. In this paper, new and changed (N&C) as well as reused code were gathered from small programs developed by 74 programmers using practices of the Personal Software Process; these data were used as input for a fuzzy model for estimating the development effort. Accuracy of this fuzzy model was compared with the accuracy of a statistical regression model. Two samples of 163 and 68 programs were used for verifying and validating respectively the models; the comparison criterion was the Mean Magnitude of Error Relative to the estimate (MMER). In verification and validation stages, fuzzy model kept a MMER lower or equal than that regression model and an accuracies comparison of the models based on ANOVA, did not show a statistically significant difference amongst their means. This result suggests that fuzzy logic could be used for predicting the effort of small programs based upon these two kinds of lines of code.