Has Twenty-five Years of Empirical Software Engineering Made a Difference?
APSEC '02 Proceedings of the Ninth Asia-Pacific Software Engineering Conference
A Review of Surveys on Software Effort Estimation
ISESE '03 Proceedings of the 2003 International Symposium on Empirical Software Engineering
Group Processes in Software Effort Estimation
Empirical Software Engineering
Reliability and Validity in Comparative Studies of Software Prediction Models
IEEE Transactions on Software Engineering
A Systematic Review of Software Development Cost Estimation Studies
IEEE Transactions on Software Engineering
How large are software cost overruns? A review of the 1994 CHAOS report
Information and Software Technology
The Rise and Fall of the Chaos Report Figures
IEEE Software
Information and Software Technology
A literature review of expert problem solving using analogy
EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
A review of studies on expert estimation of software development effort
Journal of Systems and Software
Evaluating prediction systems in software project estimation
Information and Software Technology
Influence of confirmation biases of developers on software quality: an empirical study
Software Quality Control
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Background: There has been much research into building formal (metrics-based) prediction systems with the aim of improving resource estimation and planning of software projects. However the 'objectivity' of such systems is illusory in the sense that many inputs need themselves to be estimated by the software engineer. Method: We review the uptake of past software project prediction research and identify relevant cognitive psychology research on expert behaviour. In particular we explore potential applications of recent metacognition research. Results: We find the human aspect is largely ignored, despite the availability of many important results from cognitive psychology. Conclusions: In order to increase the actual use of our metrics research e.g. effort prediction systems we need to have a more integrated view of how such research might be used and who might be using it. This leads to our belief that future research must be more holistic and inter-disciplinary.