Defects

Change Bursts as Defect Predictors – ISSRE 2010

by kim August 3, 2010

In software development, every change induces a risk. What happens if code changes again and again in some period of time? In an empirical study on Windows Vista, we found that the features of such change bursts have the highest predictive power for defect-prone components. With precision and recall values well above 90%, change bursts [...]

Making Software: Rough Cuts Version

by kim July 16, 2010
Thumbnail image for Making Software: Rough Cuts Version

Andreas Zeller and myself wrote a book chapter for the book “Making Software” that will be published by O’Reilly Media, Inc. later this year. The editors Andy Oram and Greg Wilson have made “leading thinkers such as Steve McConnell, Barry Boehm, and Barbara Kitchenham offer essays that uncover the truth and unmask myths commonly held [...]

Seminar: MSA 2010

by kim April 12, 2010

Software archives mining deals with the automated extraction, collection, and abstraction of data from the information generated during the software development process (e.g. source code archives, bug tracking systems, etc.). This seminar (7 CP) introduces the notion of software archives and teaches recent software archives mining techniques. More details here

Mining the Jazz Repository: Challenges and Opportunities

by kim April 22, 2009

By integrating various development and collaboration tools into one single platform, the Jazz environment offers several opportunities for software repository miners. In particular, Jazz offers full traceability from the initial requirements via work packages and work assignments to the final changes and tests; all these features can be easily accessed and leveraged for better prediction [...]

Predicting Defects in SAP Java Code: An Experience Report – ICSE 2009

by kim April 5, 2009

Which components of a large software system are the most defect-prone? In a study on a large SAP Java system, we evaluated and compared a number of defect predictors, based on code features such as complexity metrics, static error detectors, change frequency, or component imports, thus replicating a number of earlier case studies in an [...]

Predicting Defects in SAP Products: A Replicated Study

by kim April 5, 2009

Given a large body of code, how do we know where to focus our quality assurance effort? By mining the software’s defect history, we can automatically learn which code features correlated with defects in the past—and leverage these correlations for new predictions: “In the past, high inheritance depth was an indicator of a high number [...]

Predicting defects for code clusters

by kim April 5, 2009

Software products and projects can become very large and still grow over time. Building one prediction model for a whole software product might be easy but might also limit the prediction accuracy. Different parts of a software product have different duties (GUI, database, kernel,…). We found out that for each of these different code zones [...]

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