Prediction Models and Metrics in Software Engineering 2015/2016

Prediction Models and Metrics in Software Engineering 2015/2016

Lectures:

Lectures (base)

Resources:

[n1] Lech Madeyski and Marian Jureczko, “Which Process Metrics Can Significantly Improve Defect Prediction Models? An Empirical Study“, Software Quality Journal, Springer 2014 (accepted). DOI: 10.1007/s11219-014-9241-7 Paper in PDF (preprint) link to the paper

[1] Marco D’Ambros, Michele Lanza, Romain Robbes: Evaluating defect prediction approaches: a benchmark and an extensive comparison. Empirical Software Engineering 17(4-5): 531-577 (2012) http://dx.doi.org/10.1007/s10664-011-9173-9

[2] Marco D’Ambros, Michele Lanza, Romain Robbes: An extensive comparison of bug prediction approaches. MSR 2010: 31-41

http://dx.doi.org/10.1109/MSR.2010.5463279 http://www.old.inf.usi.ch/phd/dambros/publications/msr10.pdf

[3] Nachiappan Nagappan, Andreas Zeller, Thomas Zimmermann, Kim Herzig, Brendan Murphy: Change Bursts as Defect Predictors. ISSRE 2010:309-318 http://dx.doi.org/10.1109/ISSRE.2010.25

http://www.st.cs.uni-saarland.de/publications/files/nagappan-issre-2010.pdf

[4] Marian Jureczko, Lech Madeyski, Predykcja defektów na podstawie metryk oprogramowania – identyfikacja klas projektów, w: Inżynieria Oprogramowania w Procesach Integracji Systemów Informatycznych, Wydawnictwo Komunikacji i Łączności, 2010.

http://madeyski.e-informatyka.pl/download/JureczkoMadeyski10e.pdf

[5] Marian Jureczko, Lech Madeyski, Towards identifying software project clusters with regard to defect prediction, ACM International Conference Proceeding Series, Proceedings of the 6th International Conference on Predictor Models in Software Engineering (PROMISE’2010), ACM Digital Library, 2010.

http://madeyski.e-informatyka.pl/download/JureczkoMadeyski10f.pdf

http://dx.doi.org/10.1145/1868328.1868342

[6] Marian Jureczko, Lech Madeyski, A review of process metrics in defect prediction studies, Methods of Applied Computer Science (Metody Informatyki Stosowanej), Volume 30, Issue 5, 2011, Pages 133-145, 2011 (ISSN 1898-5297)

http://madeyski.e-informatyka.pl/download/Madeyski11.pdf

[7] Marian Jureczko, Metody zarządzania zapewnianiem jakości oprogramowania wykorzystujące modele predykcji defektów, 2012.

http://staff.iiar.pwr.wroc.pl/marian.jureczko/rozprawa.pdf

[8] W.N. Venables, D. M. Smith and the R Core Team, An Introduction to R.

http://cran.r-project.org/doc/manuals/R-intro.pdf (dostarczany z domyślną instalacją)

[9] W.J. Oven, The R Guide http://cran.r-project.org/doc/contrib/Owen-TheRGuide.pdf

[10] D. G. Rossiter, Introduction to the R Project for Statistical Computing for use at ITC http://cran.r-project.org/doc/contrib/Rossiter-RIntro-ITC.pdf

[11] Books related to R http://www.r-project.org/doc/bib/R-books.html

[12] Quick-R: Books and Tutorials http://www.statmethods.net/about/books.html

[13] KNIME Quickstart Guide http://tech.knime.org/files/KNIME_quickstart.pdf

[14] KNIME Introduction to the workbench http://tech.knime.org/workbench

[15] KNIME Developer Guide http://tech.knime.org/developer-guide

[16] KNIME JavaDoc API http://tech.knime.org/javadoc-api

[17] KNIME Example implementation http://tech.knime.org/developer/example

Note: If you are ambitious software engineer and would like to involve in an open source project, you are invited to join IC-DePress (ImpressiveCode-Defect Prediction in Software Systems).

See: http://madeyski.e-informatyka.pl/tools/software-defect-prediction/ and https://github.com/ImpressiveCode/ic-depress