Natural Language Processing and Machine Learning Methods for Software Development Effort Estimation
نویسندگان
چکیده
منابع مشابه
Natural Language Processing and Machine Learning Methods for Software Development Effort Estimation
The growing complexity and number of software projects requires both increasingly more experienced developers, testers and other specialists as well as a larger number of persons to fill these roles. This leads to increased personnel and management costs and also makes effort and cost estimation at task and activity levels more difficult for software development companies. An automated solution...
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In this study we aimed to draw a big comparative picture of the state of the art machine learning approaches for the software effort estimation problem. For this purpose, several datasets which were obtained from Promise data repository were used for testing various machine learning techniques. The results showed that, decision trees or rule induction based classifiers (i.e. M5P trees) gave par...
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Accurate estimating is one of the most important activities in the field of software project management. Different aspects of software projects must be estimated among which time and effort are of significant importance to efficient project planning. Due to complexity of software projects and lack of information at the early stages of project, reliable effort estimation is a challenging issue. ...
متن کاملAn Improved Algorithmic Method for Software Development Effort Estimation
Accurate estimating is one of the most important activities in the field of software project management. Different aspects of software projects must be estimated among which time and effort are of significant importance to efficient project planning. Due to complexity of software projects and lack of information at the early stages of project, reliable effort estimation is a challenging issue. ...
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We show that the methodology currently in use for comparing symbolic supervised learning methods applied to human language technology tasks is unreliable. We show that the interaction between algorithm parameter settings and feature selection within a single algorithm often accounts for a higher variation in results than differences between different algorithms or information sources. We illust...
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ژورنال
عنوان ژورنال: Studies in Informatics and Control
سال: 2017
ISSN: 1220-1766,1841-429X
DOI: 10.24846/v26i2y201710