by Usman Ashraf, Christoph Mayr-Dorn, Alexander Egyed
Abstract:
Implementing a change is a challenging task in complex, safety-critical, or long-living software systems. Developers need to identify which artifacts are affected to correctly and completely implement a change. Changes often require editing artifacts across the software system to the extent that several developers need to be involved. Crucially, a developer needs to know which artifacts under someone else’s control have impact on her work task and, in turn, how her changes cascade to other artifacts, again, under someone else’s control. These cross-task dependencies are especially important as they are a common cause of incomplete and incorrect change propagation and require explicit coordination. Along these lines the core research question in this paper is: how can we automatically detect cross-task dependencies and use them to assist the developer? We introduce an approach for mining such dependencies from past developer interactions with engineering artifacts as the basis for live recommending artifacts during change implementation. We show that our approach lists 67% of the correctly recommended artifacts within the top-10 results with real interaction data and tasks from the Mylyn project. The results demonstrate we are able to successfully find not only cross-task dependencies but also provide them to developers in a useful manner.
Reference:
Mining Cross-Task Artifact Dependencies from Developer Interactions (Usman Ashraf, Christoph Mayr-Dorn, Alexander Egyed), In 26th IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER), Hangzhou, China9, 2019.
Bibtex Entry:
@Conference{DBLP:conf/wcre/AshrafME19,
author = {Usman Ashraf and Christoph Mayr-Dorn and Alexander Egyed},
booktitle = {26th {IEEE} International Conference on Software Analysis, Evolution and Reengineering (SANER), Hangzhou, China9},
title = {Mining Cross-Task Artifact Dependencies from Developer Interactions},
year = {2019},
pages = {186--196},
abstract = {Implementing a change is a challenging task in complex, safety-critical, or long-living software systems. Developers need to identify which artifacts are affected to correctly and completely implement a change. Changes often require editing artifacts across the software system to the extent that several developers need to be involved. Crucially, a developer needs to know which artifacts under someone else’s control have impact on her work task and, in turn, how her changes cascade to other artifacts, again, under someone else’s control. These cross-task dependencies are especially important as they are a common cause of incomplete and incorrect change propagation and require explicit coordination. Along these lines the core research question in this paper is: how can we automatically detect cross-task dependencies and use them to assist the developer? We introduce an approach for mining such dependencies from past developer interactions with engineering artifacts as the basis for live recommending artifacts during change implementation. We show that our approach lists 67% of the correctly recommended artifacts within the top-10 results with real interaction data and tasks from the Mylyn project. The results demonstrate we are able to successfully find not only cross-task dependencies but also provide them to developers in a useful manner.},
bibsource = {dblp computer science bibliography, https://dblp.org},
biburl = {https://dblp.org/rec/bib/conf/wcre/AshrafME19},
crossref = {DBLP:conf/wcre/2019},
doi = {10.1109/SANER.2019.8667990},
file = {:Conferences/SANER 2019 - Mining Cross-Task Artifact Dependencies from Developer Interactions/Mining Cross-Task Artifact Dependencies from Developer Interactions-preprint.pdf:PDF},
keywords = {Pro2Future, FWF P29415},
timestamp = {Sat, 19 Oct 2019 20:07:07 +0200},
url = {https://doi.org/10.1109/SANER.2019.8667990},
}