TY - GEN
T1 - Improving Estimation Accuracy Prediction of Software Development Effort
T2 - 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020
AU - Mahmood, Yasir
AU - Kama, Nazri
AU - Azmi, Azri
AU - Ali, Mazlan
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Software effort estimation is an essential feature of software engineering for effective planning, controlling and delivering successful software projects. The overestimation and underestimation both are the key challenges for future software development. The failure to acknowledge the effort estimation accuracy may lead to customer disappointment, inaccurate estimation and hence, contribute to either poor software development process or project failure. The main aim of this research is to optimize the estimation accuracy prediction of software development effort to support software development firms and practitioners. In this paper, we propose an ensemble software effort estimation model based on Use Case Points (UCP), expert judgment and Case-Based Reasoning (CBR) techniques. This research is conducted through primary (a multi-case involving software companies) study to make an ensemble model. The estimation accuracy prediction of the proposed model will be evaluated by selecting projects from primary studies as case selections in applying a quantitative approach through industrial experts, archival data about estimates and evaluation metrics. The proposed model produced at the end of this research will be used by software development firms and practitioners as an instrument to estimate the effort required to develop new software projects at an earlier stage.
AB - Software effort estimation is an essential feature of software engineering for effective planning, controlling and delivering successful software projects. The overestimation and underestimation both are the key challenges for future software development. The failure to acknowledge the effort estimation accuracy may lead to customer disappointment, inaccurate estimation and hence, contribute to either poor software development process or project failure. The main aim of this research is to optimize the estimation accuracy prediction of software development effort to support software development firms and practitioners. In this paper, we propose an ensemble software effort estimation model based on Use Case Points (UCP), expert judgment and Case-Based Reasoning (CBR) techniques. This research is conducted through primary (a multi-case involving software companies) study to make an ensemble model. The estimation accuracy prediction of the proposed model will be evaluated by selecting projects from primary studies as case selections in applying a quantitative approach through industrial experts, archival data about estimates and evaluation metrics. The proposed model produced at the end of this research will be used by software development firms and practitioners as an instrument to estimate the effort required to develop new software projects at an earlier stage.
KW - effort estimation accuracy
KW - ensemble effort estimation
KW - ensemble model
KW - Software development
UR - https://www.scopus.com/pages/publications/85091921644
UR - https://www.scopus.com/pages/publications/85091921644#tab=citedBy
U2 - 10.1109/ICECCE49384.2020.9179279
DO - 10.1109/ICECCE49384.2020.9179279
M3 - Conference contribution
AN - SCOPUS:85091921644
T3 - 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020
BT - 2nd International Conference on Electrical, Communication and Computer Engineering, ICECCE 2020
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 12 June 2020 through 13 June 2020
ER -