Understanding Legacy Features with Featureous

Olszak, Andrzej; Jôrgensen, Bo Nørregaard

doi:10.1109/wcre.2011.64

Cited by 2 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Feature-Location Datasets. We are aware of few data-sets on feature location: Olszak and Jorgensen [26] develop a tool for feature location, which they apply on multiple systems for which the source code and data is partly available. Ji et al [18] annotate feature locations in the source code of the freely available Clafer Web Tools.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Towards a Better Understanding of Software Features and Their Characteristics

Krüger

Shen

et al. 2018

Proceedings of the 12th International Workshop on Variability Modelling of Software-Intensive Systems

View full text Add to dashboard Cite

The notion of features is commonly used to describe, structure, and communicate the functionalities of a system. Unfortunately, features and their locations in software artifacts are rarely made explicit and often need to be recovered by developers. To this end, researchers have conceived automated feature-location techniques. However, their accuracy is generally low, and they mostly rely on few information sources, disregarding the richness of modern projects. To improve such techniques, we need to improve the empirical understanding of features and their characteristics, including the information sources that support feature location. Even though, the product-line community has extensively studied features, the focus was primarily on variable features in preprocessor-based systems, largely side-stepping mandatory features, which are hard to identify. We present an exploratory case study on identifying and locating features. We study what information sources reveal features and to what extent, compare the characteristics of mandatory and optional features, and formulate hypotheses about our observations. Among others, we find that locating features in code requires substantial domain knowledge for half of the mandatory features (e.g., to connect keywords) and that mandatory and optional features in fact differ. For instance, mandatory features are less scattered. Other researchers can use our manually created data set of features locations for future research, guided by our formulated hypotheses.

show abstract

Section: Related Workmentioning

confidence: 99%

“…To recover features and their locations, different (semi-)automated techniques have been proposed [26,32]. Unfortunately, their accuracy is generally low, they require substantial effort (e.g., calibration towards the project), and often focus on one information source only, such as keywords in source code.…”

Section: Introductionmentioning

confidence: 99%