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Where is my feature and what is it about? A case study on recovering feature facets

Artikel i vetenskaplig tidskrift
Författare Jacob Krüger
Mukelabai Mukelabai
Wanzi Gu
Hui Shen
Regina Hebig
Thorsten Berger
Publicerad i Journal of Systems and Software
Volym 152
Nummer/häfte June
Sidor 239-253
ISSN 0164-1212
Publiceringsår 2019
Publicerad vid Institutionen för data- och informationsteknik (GU)
Institutionen för data- och informationsteknik, Software Engineering (GU)
Institutionen för data- och informationsteknik, datavetenskap (GU)
Sidor 239-253
Språk en
Länkar https://doi.org/10.1016/j.jss.2019....
Ämnesord Bitcoin-wallet, Case study, Feature facets, Feature location, Marlin, Software product line
Ämneskategorier Programvaruteknik

Sammanfattning

© 2019 Elsevier Inc. Developers commonly use features to define, manage, and communicate functionalities of a system. Unfortunately, the locations of features in code and other characteristics (feature facets), relevant for evolution and maintenance, are often poorly documented. Since developers change, and knowledge fades with time, such information often needs to be recovered. Modern projects boast a richness of information sources, such as pull requests, release logs, and otherwise specified domain knowledge. However, it is largely unknown from what sources the features, their locations, and their facets can be recovered. We present an exploratory study on identifying such information in two popular, variant-rich, and long-living systems: The 3D-printer firmware Marlin and the Android application Bitcoin-wallet. Besides the available information sources, we also investigated the projects’ communities, communications, and development cultures. Our results show that a multitude of information sources (e.g., commit messages and pull requests) is helpful to recover features, locations, and facets to different extents. Pull requests were the most valuable source to recover facets, followed by commit messages and the issue tracker. As many of the studied information sources are, so far, rarely exploited in techniques for recovering features and their facets, we hope to inspire researchers and tool builders with our results.

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