TY - GEN
T1 - PREP
T2 - 2022 International Conference on Data and Software Engineering, ICoDSE 2022
AU - Madya, Gusti Raditia
AU - Budiardjo, Eko K.
AU - Mahatma, Kodrat
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Effort estimation in the software development process using Scrum is performed to determine the time the development team needs to complete user stories and the sprint's complexity level. Inaccurate effort estimation can result in user stories from the previous sprint having to be carried over to the next sprint, budget overruns, project delivery delays, and incorrect schedule estimates. The inaccurate estimation occurs in one product development in company XYZ, with average estimation performance for only 57.12%. This performance is less than expected, 75%. This study designs a method that the development team can use to improve the accuracy of the effort estimation, focusing on improving the quality of user stories and the estimation process in an e-commerce company in Indonesia, XYZ. The effort estimation method design developed, PREP (Post-Requirements Estimation Procedure), is then evaluated by looking at the reduction in the number of bugs and calculating the estimation accuracy with Balanced Relative Error bias (BREbias). The PREP method experiment in product development in XYZ shows bug reduction from 46.7% to 15.9% and increases the accuracy of the estimates by 23.63%. The effort estimation method validation shows a positive trend for delight, effort, and functionality aspects but requires a high level of understanding and more time to implement it.
AB - Effort estimation in the software development process using Scrum is performed to determine the time the development team needs to complete user stories and the sprint's complexity level. Inaccurate effort estimation can result in user stories from the previous sprint having to be carried over to the next sprint, budget overruns, project delivery delays, and incorrect schedule estimates. The inaccurate estimation occurs in one product development in company XYZ, with average estimation performance for only 57.12%. This performance is less than expected, 75%. This study designs a method that the development team can use to improve the accuracy of the effort estimation, focusing on improving the quality of user stories and the estimation process in an e-commerce company in Indonesia, XYZ. The effort estimation method design developed, PREP (Post-Requirements Estimation Procedure), is then evaluated by looking at the reduction in the number of bugs and calculating the estimation accuracy with Balanced Relative Error bias (BREbias). The PREP method experiment in product development in XYZ shows bug reduction from 46.7% to 15.9% and increases the accuracy of the estimates by 23.63%. The effort estimation method validation shows a positive trend for delight, effort, and functionality aspects but requires a high level of understanding and more time to implement it.
KW - Balanced Relative Error
KW - effort estimation
KW - PREP
KW - Scrum
KW - user stories
UR - http://www.scopus.com/inward/record.url?scp=85145771016&partnerID=8YFLogxK
U2 - 10.1109/ICoDSE56892.2022.9972012
DO - 10.1109/ICoDSE56892.2022.9972012
M3 - Conference contribution
AN - SCOPUS:85145771016
T3 - Proceedings of 2022 International Conference on Data and Software Engineering, ICoDSE 2022
SP - 132
EP - 137
BT - Proceedings of 2022 International Conference on Data and Software Engineering, ICoDSE 2022
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 2 November 2022 through 3 November 2022
ER -