Direct comparison of the relative efficiency on intuitive and analytical cognition
IEEE Transactions on Systems, Man and Cybernetics
Robust regression for developing software estimation models
Journal of Systems and Software
An empirical study of software maintenance tasks
Journal of Software Maintenance: Research and Practice
An assessment and comparison of common software cost estimation modeling techniques
Proceedings of the 21st international conference on Software engineering
Understanding strategy selection
International Journal of Human-Computer Studies
Comparing Software Prediction Techniques Using Simulation
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
On Building Prediction Systems for Software Engineers
Empirical Software Engineering
Predicting Maintenance Effort with Function Points
ICSM '97 Proceedings of the International Conference on Software Maintenance
METRICS '99 Proceedings of the 6th International Symposium on Software Metrics
An Empirical Study of Software Project Bidding
IEEE Transactions on Software Engineering
Anchoring and adjustment in software estimation
Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
Journal of Cognitive Neuroscience
Inconsistency of expert judgment-based estimates of software development effort
Journal of Systems and Software
The Impact of Lessons-Learned Sessions on Effort Estimation and Uncertainty Assessments
IEEE Transactions on Software Engineering
A review of studies on expert estimation of software development effort
Journal of Systems and Software
Hi-index | 0.00 |
We currently know little about the factors that motivate the selection and change of strategy in judgment-based effort estimation. A better understanding of these issues may lead to more accurate judgment-based effort estimates and motivates the four experiments reported in this paper. The experiments' two main results are the identification of the importance of ''estimation surprises'' (large estimation errors) to motivate estimation strategy change and the large individual variation in the initial choice of estimation strategy. The individual variation seems not only to be a result of differences in previous experiences, but also a result of differences in the mental ''accessibility'' of the strategies. We found, for example, that the use of a type of strategy was increased when we instructed a developer to use the same type of strategy on unrelated tasks immediately before.