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Vorträge und Posterpräsentationen (mit Tagungsband-Eintrag):

A. Mauczka, M. Bernhart, T. Grechenig:
"Analyzing the Relationship of Process Metrics And Classified Changes - A Pilot Study";
Vortrag: The 22nd International Conference on Software Engineering & Knowledge Engineering, San Francisco Bay; 01.07.2010 - 03.07.2010; in: "Proceedings of the Twenty-Second International Conference on Software Engineering & Knowledge Engineering", Knowledge Systems Institute Graduate School, (2010), ISBN: 978-1-891706-26-4; S. 269 - 272.



Kurzfassung englisch:
Abstract-Knowing how a software project is likely to evolve is
an essential problem for any software project manager. Finding
efficient predictors for performance indicators (e.g., bugrates)
has been the focus of many studies. Previous studies found
that process metrics make likely candidates for this predictor
role, for bug data in particular. We propose a methodology
for in-depth analysis of process metrics to find out how they
relate to changes. We use a lexical approach to classify changes
into perfective, adaptive and corrective changes. The analysis
consists of examining a set of hypotheses on the nature of the
relationship of certain process metrics and the change categories,
e.g., perfective changes and their impact on the consecutive bug
appearance rate of a module. As this work is in progress, we
present a pilot study on a module of the Ant Project to showcase
and discuss our technique and point out early trends.

Erstellt aus der Publikationsdatenbank der Technischen Universitšt Wien.