2015/07/31 by Wei Lin Du, Wei Du, Du, Wei Lin +4
Computer Science · #Software Engineering Research #Software Engineering Techniques and Practices #Software Reliability and Analysis Research #cs.SE
paper · pdf · doi:10.48550/arxiv.1508.00032
25th International Forum on COCOMO and Systems/Software Cost Modeling, Los Angeles, CA, 7 pages, 2010. arXiv admin note: substantial text overlap with arXiv:1507.06917
arxiv created 2015/07/31 · arxiv updated 2015/08/04
Software effort estimation is a critical part of software engineering. Although many techniques and algorithmic models have been developed and implemented by practitioners, accurate software effort prediction is still a challenging endeavor. In order to address this issue, a novel soft computing framework was previously developed. Our study utilizes this novel framework to develop an approach combining the neuro-fuzzy technique with the System Evaluation and Estimation of Resource - Software Estimation Model (SEER-SEM). Moreover, our study assesses the performance of the proposed model by designing and conducting evaluation with published industrial project data. After analyzing the performance of our model in comparison to the SEER-SEM effort estimation model alone, the proposed model demonstrates the ability of improving the estimation accuracy, especially in its ability to reduce the large Mean Relative Error (MRE). Furthermore, the results of this research indicate that the general neuro-fuzzy framework can work with various algorithmic models for improving the performance of software effort estimation.