Selecting best predictors from large software repositories for highly accurate software effort estimation

Volume: 32, Issue: 10
Published: Jun 9, 2020
Abstract
Accurate prediction of software effort is important for planning, scheduling, and allocating resources. However, software effort estimation has been a challenging task. Although numerous estimation models have been proposed, few achieve anything close to accurate prediction of software development effort. To achieve optimal results, machine learning techniques have recently been employed for predicting software development effort using...
Paper Details
Title
Selecting best predictors from large software repositories for highly accurate software effort estimation
Published Date
Jun 9, 2020
Volume
32
Issue
10
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