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It doesn't matter what you do, but it does matter who does it!

It doesn't matter what you do, but it does matter who does it!. Martin Shepperd, Brunel U Tracy Hall, Brunel U David Bowes, U. of Hertfordshire. Overview. Many empirical studies (200+) to predict software faults No technique dominates

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It doesn't matter what you do, but it does matter who does it!

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  1. It doesn't matter what you do, but it does matter who does it! Martin Shepperd, Brunel U Tracy Hall, Brunel U David Bowes, U. of Hertfordshire

  2. Overview • Many empirical studies (200+) to predict software faults • No technique dominates • Conduct a meta-analysis to explain variation in the results • Used factors of (i) classifier (ii) metric type (iii) data set (iv) research group

  3. Systematic Review • Conducted by Tracy Hall and David Bowes • T. Hall, S. Beecham, D. Bowes, D. Gray, and S. Counsell. “A systematic literature review on fault prediction performance in software engineering”, Accepted for publication in TSE (download from BURA). • Located 208 relevant primary studies • Due to reporting requirements used 18 studies that contain 194 results • binary classifiers, confusion matrix, context details

  4. (i) Classifier

  5. (ii) Metric Type • Delta • Static • Process • Other • Combinations

  6. (iii) Data Set ECLIP :93 EMTEL :26 MOZ :25 COS :16 EXCL : 9 VISTA : 4 (Other):21

  7. (iv) Research Group

  8. Response variable Response variable – Matthews correlation coefficient (MCC) • stable (uses all 4 cells of the confusion matrix) • easy to interpret (0=random) • easy to compare • related to chi-squared test

  9. Matthews correlation coefficient

  10. ANOVA model 4-way linear random effects model with interactions

  11. ANOVA Results Factor % of var Author group 61% Metric family 3% Author/metric 9% Everything else 8% (but not significant) Residuals 19%

  12. Confounders? • autocorrelation • system age • pre /post-release data collection not significant • Homogeneity of variances robust Levene test p=0.51 • Normality of the RV slight +ve skew (0.12) and leptokurtosis (0.26)

  13. Conclusions • There are problems with how research is replicated • expertise • bias • Search to • de-skill • de-bias

  14. Final word We cannot ignore the fact that the main determinant of a validation study result is which research group undertakes it.

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