Effort estimation in software development using story point: a machine learning approach
نویسندگان
چکیده
منابع مشابه
A Survey of Software Effort Estimation Techniques Using Machine Learning
Software effort estimation is an aspect of software engineering involving evaluation of numerous different changing factors related to the creation of a system. Historically, estimation methods have relied on construction cost models (COCOMO) and function point analysis (FPA) to deliver accurate estimation values. We explored recently published works from 2016, describing the incorporation of m...
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Agile software development process represents a major departure from traditional, plan-based approaches to software engineering. Estimating effort of agile software accurately in early stage of software development life cycle is a major challenge in the software industry. For improving the estimation accuracy, various optimization techniques are used. The Support Vector Regression (SVR) is one ...
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For a successful project development, it is important for any software organization that the project should be completed within time and budget, and the project should have requisite quality. This paper presents an Ensemble learning based Adaptive Neuro-Fuzzy Approach for Software Development Time Estimation. The concept behind this technique is based on ensemble learning methods. This techniqu...
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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. ...
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ژورنال
عنوان ژورنال: International Journal of Knowledge Engineering and Soft Data Paradigms
سال: 2020
ISSN: 1755-3210,1755-3229
DOI: 10.1504/ijkesdp.2020.112630