Software Engineering Economics
Software Engineering Economics
A meta-model for software development resource expenditures
ICSE '81 Proceedings of the 5th international conference on Software engineering
A model for estimating program size and its evaluation
ICSE '82 Proceedings of the 6th international conference on Software engineering
Software metrics using deviation value
ICSE '87 Proceedings of the 9th international conference on Software Engineering
Perceptual congruence and information systems cost estimating
SIGCPR '95 Proceedings of the 1995 ACM SIGCPR conference on Supporting teams, groups, and learning inside and outside the IS function reinventing IS
Towards an adaptation of the COCOMO cost model to the software measurement theory
ESEC '97/FSE-5 Proceedings of the 6th European SOFTWARE ENGINEERING conference held jointly with the 5th ACM SIGSOFT international symposium on Foundations of software engineering
Estimating Software Project Effort Using Analogies
IEEE Transactions on Software Engineering
A Procedure for Analyzing Unbalanced Datasets
IEEE Transactions on Software Engineering
IEEE Transactions on Software Engineering
A Rule-Based Approach to Developing Software Development Prediction Models
Automated Software Engineering
A Causal Model for Software Cost Estimating Error
IEEE Transactions on Software Engineering
Continuous Productivity Assessment and Effort Prediction Based on Bayesian Analysis
COMPSAC '04 Proceedings of the 28th Annual International Computer Software and Applications Conference - Volume 01
Perceptual Congruence and Systems Development Cost Estimation
Information Resources Management Journal
IMPROVING THE PREDICTION ACCURACY OF SOFTWARE DEVELOPMENT COST MODELS
Journal of Integrated Design & Process Science
Hi-index | 0.00 |
This paper gives the results of our efforts to evaluate and tailor a software cost estimation model called COCOMO.1 The precise data for the analysis was collected from the records of 33 completed projects. We evaluate the original COCOMO model, which overestimates the efforts required to develop software in our environment. Then we tailor the model according to the COCOMO tailoring methodology. To increase the precision and stability of the tailored model, we delete some unnecessary cost drivers in a heuristic manner with the aid of nonparametric statistical method. As a result, we can greatly improve the model. Finally we suggest a method to tailor the COCOMO effort multipliers. We believe we maintain the same direction as the originator's philosophy, and that our efforts can contribute to the progress of the COCOMO tailoring methodology.