Applications of fuzzy logic to software metric models for development effort estimation
Andrew R. Gray,Stephen G. MacDonell +1 more
- pp 394-399
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TLDR
Software metrics are measurements of the software development process and product that can be used as variables (both dependent and independent) in models for project management and the use of alternative techniques, especially fuzzy logic, is investigated and some usage recommendations are made.Abstract:
Software metrics are measurements of the software development process and product that can be used as variables (both dependent and independent) in models for project management. The most common types of these models are those used for predicting the development effort for a software system based on size, complexity, developer characteristics, and other metrics. Despite the financial benefits from developing accurate and usable models, there are a number of problems that have not been overcome using the traditional techniques of formal and linear regression models. These include the nonlinearities and interactions inherent in complex real-world development processes, the lack of stationarity in such processes, over-commitment to precisely specified values, the small quantities of data often available, and the inability to use whatever knowledge is available where exact numerical values are unknown. The use of alternative techniques, especially fuzzy logic, is investigated and some usage recommendations are made.read more
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Software development cost estimation using wavelet neural networks
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Adaptive fuzzy logic-based framework for software development effort prediction
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An Improved Fuzzy Approach for COCOMO’s Effort Estimation Using Gaussian Membership Function
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References
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Book
Software Metrics: A Rigorous Approach
TL;DR: The book has been comprehensively re-written and re-designed to take account of the fast changing developments in software metrics, most notably their widespread penetration into industrial practice.
Journal ArticleDOI
Machine learning approaches to estimating software development effort
K. Srinivasan,Douglas H. Fisher +1 more
TL;DR: Two methods of machine learning are described, which are used to build estimators of software development effort from historical data, which indicate that these techniques are competitive with traditional estimators on one dataset, but also illustrate that these methods are sensitive to the data on which they are trained.
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Software development cost estimation using function points
TL;DR: An assessment of several published statistical regression models that relate software development effort to software size measured in function points finds a problem with the current method for measuring function points that constrains the effective use of function points in regression models and suggests a modification to the approach that should enhance the accuracy of prediction models based on function points.
Journal ArticleDOI
Introducing Objectcharts or how to use Statecharts in object-oriented design
TL;DR: How Objectcharts can be used to find subtyping inheritance relationships between classes and a systematic approach for evolving Objectchart specifications are shown.