Comparing Software Prediction Techniques Using Simulation
IEEE Transactions on Software Engineering - Special section on the seventh international software metrics symposium
Measuring Effort Estimation Uncertainty to Improve Client Confidence
Software Quality Control
Combining data from reading experiments in software inspections: a feasibility study
Lecture notes on empirical software engineering
Experimental validation of new software technology
Lecture notes on empirical software engineering
A Procedure for Assessing the Influence of Problem Domain on Effort Estimation Consistency
Software Quality Control
Empirical Software Engineering
Experimental context classification: incentives and experience of subjects
Proceedings of the 27th international conference on Software engineering
Accumulation and presentation of empirical evidence: problems and challenges
REBSE '05 Proceedings of the 2005 workshop on Realising evidence-based software engineering
Software engineering article types: An analysis of the literature
Journal of Systems and Software
Systematic literature reviews in software engineering - A systematic literature review
Information and Software Technology
Replicating software engineering experiments: a poisoned chalice or the Holy Grail
Information and Software Technology
Assessing multiview framework (MF) comprehensibility and efficiency: A replicated experiment
Information and Software Technology
Empirical software engineering: teaching methods and conducting studies
Proceedings of the 2006 international conference on Empirical software engineering issues: critical assessment and future directions
Replications types in experimental disciplines
Proceedings of the 2010 ACM-IEEE International Symposium on Empirical Software Engineering and Measurement
Replication of software engineering experiments
Empirical Software Engineering and Verification
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Deriving reliable empirical results from a single experiment is an unlikely event. Hence to progress multiple experiments must be undertaken per hypothesis and the subsequent results effectively combined to produce a single reliable conclusion. Other disciplines use meta-analytic techniques to achieve this result. The treatise of this paper is: can meta-analysis be successfully applied to current Software Engineering experiments?The question is investigated by examining a series of experiments, which themselves investigate - which defect detection technique is best? Applying meta-analysis techniques to the Software Engineering data is relatively straightforward, but unfortunately the results are highly unstable, as the meta-analysis shows that the results are highly disparate and don't lead to a single reliable conclusion.The reason for this deficiency is the excessive variation within various components of the experiments. Finally the paper describes a number of recommendations for controlling and reporting empirical work to advance the discipline towards a position where meta-analysis can be profitably employed.