2014
DOI: 10.1109/tse.2013.45
|View full text |Cite
|
Sign up to set email alerts
|

Variability Mining: Consistent Semi-automatic Detection of Product-Line Features

Abstract: Abstract-Software product line engineering is an efficient means to generate a set of tailored software products from a common implementation. However, adopting a product-line approach poses a major challenge and significant risks, since typically legacy code must be migrated toward a product line. Our aim is to lower the adoption barrier by providing semiautomatic tool support-called variability mining-to support developers in locating, documenting, and extracting implementations of product-line features from… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

1
54
0

Year Published

2015
2015
2022
2022

Publication Types

Select...
5
3
1

Relationship

0
9

Authors

Journals

citations
Cited by 78 publications
(55 citation statements)
references
References 58 publications
1
54
0
Order By: Relevance
“…Hence, the tool should (b) support recording the source code associated with the feature and (c) make explicit source code one structural dependency away from this source code. This iterative-refinement approach is in line with the evaluation literature on Feature Location Techniques (FLTs), which suggests that existing, fully-automated techniques are inappropriate when seeking the full location of a feature in the code-base [9], as they have low effectiveness, in terms of their recall [1]. Consequently, (d) any automated FLTs brought in to support the engineers in their feature location with the tool should augment this interactive, iterative refinement and not replace it.…”
Section: Figure 1: a Conceptual Representation Of The Feature Locatiosupporting
confidence: 53%
“…Hence, the tool should (b) support recording the source code associated with the feature and (c) make explicit source code one structural dependency away from this source code. This iterative-refinement approach is in line with the evaluation literature on Feature Location Techniques (FLTs), which suggests that existing, fully-automated techniques are inappropriate when seeking the full location of a feature in the code-base [9], as they have low effectiveness, in terms of their recall [1]. Consequently, (d) any automated FLTs brought in to support the engineers in their feature location with the tool should augment this interactive, iterative refinement and not replace it.…”
Section: Figure 1: a Conceptual Representation Of The Feature Locatiosupporting
confidence: 53%
“…Such an environment would be in the spirit of FEAT [68] where the level of visualization would be increased from Feature contents, as in FEAT, to feature contents and inter-feature dependencies. The participants' comments hinted at the requirement for a Feature Location Technique as part of this environment and an iterative process for this is envisaged, in line with the process proposed by Kastner et al [69]. In this process users would seed the tool with elements of the source code they associate with the feature and the tool would iteratively apply Feature Location Techniques to that seed set.…”
Section: Discussionmentioning
confidence: 92%
“…Overall, our empirical study shows that, given a supervised and necessary scoping (selection of products), the synthesized PCMs exhibit numerous quantitative and comparable information: 12.5% of quantified features, 15.6% of descriptive features, and only 13.0% of empty cells. The user study shows that our automatic approach retrieve 43% of correct features and 68% of correct cell values in one step and without any user intervention.…”
Section: Introductionmentioning
confidence: 86%
“…Numerous techniques have been developed to mine variability [10,15,16] and support domain analysis [17,18,19,20,7,6,3,21,22,23], but none of them address the problem of structuring the information in a PCM.…”
Section: Introductionmentioning
confidence: 99%