Authors:
Hrvoje Karna
and
Sven Gotovac
Affiliation:
Faculty of Electrical Engineering, Mechanical Engineering and Naval Arhitecture and University of Split, Croatia
Keyword(s):
Software Effort Estimation, Human-Judgment, Data Mining, Neural Networks.
Related
Ontology
Subjects/Areas/Topics:
Decision Support Systems
;
Enterprise Software Technologies
;
Project Management Software
;
Project Planning, Monitoring and Control
;
Scheduling and Estimating
;
Software Engineering
;
Software Metrics
;
Software Project Management
Abstract:
Effort estimation is an important part of software project management. Accurate estimates ensure planned project execution and compliance with the set time and budget constraints. Despite attempts to produce accurate estimates by using formal models there is no substantial evidence that these methods guarantee better estimates than those experts make. In order to improve the effort estimation process it is crucial to enhance understanding of the human estimator. When producing estimates each expert exhibits mental effort. In such situation estimator relies on his personal characteristics, some of which are, in context of effort estimation, more important than others. This research tries to identify these characteristics and their relative influences. Data for the research have been collected from projects executed in large company specialized for development of IT solutions in telecom domain. For identification of expert characteristics data mining approach is used (the multilayer pe
rceptron neural network). We considered the use of this method as it is similar to the way human brain operates. Data sets used in modelling contain more than 2000 samples collected from analysed projects. The obtained results are highly intuitive and later could be used in the assessment of reliability of each estimator and estimates he produces.
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