A comparative study for estimating software development effort intervals
Software Quality Control
Software effort estimation based on optimized model tree
Proceedings of the 7th International Conference on Predictive Models in Software Engineering
Local bias and its impacts on the performance of parametric estimation models
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KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part II
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Evidence-based reasoning is becoming common in many fields. It's widely enshrined in the practice and teaching of medicine, law, and management, for example. Evidence-based approaches demand that, among other things, practitioners systematically track down the best evidence relating to some practice; critically appraise that evidence for validity, impact, and applicability; and carefully document it. One proponent of evidence-based software engineering is David Budgen of Durham University. In the Internet age, he argues, many sources of supposed knowledge--Google, Wikipedia, digg.com, and so on--surround us. At his keynote address at the 2006 Conference on Software Engineering Education and Training, Budgen asks, how should we train students to assess all that information and to separate the sense from the nonsense? In his view, before we can denounce some inaccuracy in, say, Wikipedia, we must first look to our own work and audit our own results.