A random forest model for early-stage software effort estimation for the SEERA dataset-Reference-Cited by-同舟云学术

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A random forest model for early-stage software effort estimation for the SEERA dataset

Published:2024-05 Issue: Volume:169 Page:107413
ISSN:0950-5849
Container-title:Information and Software Technology
language:en
Short-container-title:Information and Software Technology

Author:

Mustafa Emtinan I.,Osman Rasha^ORCID

Publisher

Elsevier BV

Reference69 articles.

1. Negative results for software effort estimation;Menzies;Empir. Software Engineer.,2017

2. A systematic review of software development cost estimation studies;Jørgensen;IEEE Transac. Software Engineer.,2007

3. A flexible method to estimate the software development effort based on the classification of projects and localization of comparisons;Bardsiri;Empir. Software Engineer.,2014

4. Active learning and effort estimation: finding the essential content of software effort estimation data;Kocagunel;IEEE Trans. Software Eng.,2013

5. Experience: quality benchmarking of datasets used in software effort estimation;Bosu;J. Data Inform. Quality,2019

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Preliminary Estimation for Software Development Projects Empowered with a Method of Recommending Optimal Duration and Team Composition;Applied System Innovation;2024-04-23

2. TSoptEE: two-stage optimization technique for software development effort estimation;Cluster Computing;2024-04-12

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