RECORD
Conflict Detection for Edits on Extended Feature Models using Symbolic Graph Transformation
Software Engineering · Submitted 1 Apr 2016
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim In this paper, we propose a novel conflict detection approach based on symbolic graph transformation to facilitate concurrent edits on extended feature models.
The compiled record
The paper's own sentences, arranged. Each label is drawn from a closed vocabulary; the number beside it is the probability the classifier gave that label. Numbers in the tables are the authors', checked by code. No sentence in this record was written by a model.
Open the compiled record
The abstract, sentence by sentence
Feature models are used to specify variability of user-configurable systems as appearing, e.g., in software product lines. Software product lines are supposed to be long-living and, therefore, have to continuously evolve over time to meet ever-changing requirements. Evolution imposes changes to feature models in terms of edit operations. Ensuring consistency of concurrent edits requires appropriate conflict detection techniques. However, recent approaches fail to handle crucial subtleties of extended feature models, namely constraints mixing feature-tree patterns with first-order logic formulas over non-Boolean feature attributes with potentially infinite value domains. In this paper, we propose a novel conflict detection approach based on symbolic graph transformation to facilitate concurrent edits on extended feature models. We describe extended feature models formally with symbolic graphs and edit operations with symbolic graph transformation rules combining graph patterns with first-order logic formulas. The approach is implemented by combining eMoflon with an SMT solver, and evaluated with respect to applicability.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | Feature models are used to specify variability of user-configurable systems as appearing, e.g., in software product lines. | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s1 | Software product lines are supposed to be long-living and, therefore, have to continuously evolve over time to meet ever-changing requirements. | background 1.00 | 0.04 | 0.02 | asserted 0.99 |
| s2 | Evolution imposes changes to feature models in terms of edit operations. | background 1.00 | 0.05 | 0.02 | asserted 1.00 |
| s3 | Ensuring consistency of concurrent edits requires appropriate conflict detection techniques. | background 0.98 | 0.04 | 0.04 | asserted 0.99 |
| s4 | However, recent approaches fail to handle crucial subtleties of extended feature models, namely constraints mixing feature-tree patterns with first-order logic formulas over non-Boolean feature attributes with potentially infinite value domains. | gap 1.00 | 0.06 | 0.06 | asserted 1.00 |
| s5 | In this paper, we propose a novel conflict detection approach based on symbolic graph transformation to facilitate concurrent edits on extended feature models. | contribution 1.00 | 0.94 | 0.56 | asserted 1.00 |
| s6 | We describe extended feature models formally with symbolic graphs and edit operations with symbolic graph transformation rules combining graph patterns with first-order logic formulas. | method 0.91 | 0.93 | 0.08 | asserted 1.00 |
| s7 | The approach is implemented by combining eMoflon with an SMT solver, and evaluated with respect to applicability. | method 0.95 | 0.95 | 0.10 | asserted 1.00 |
What was examined, and what was not
- arXiv listing abstract v1
- full text
- figures and tables
- references and citing sentences
- relations to other papers
- P abstract
- S sections
- T body sentences
- C citations
- R cross-paper relations
The paper
Original abstract
Feature models are used to specify variability of user-configurable systems as appearing, e.g., in software product lines. Software product lines are supposed to be long-living and, therefore, have to continuously evolve over time to meet ever-changing requirements. Evolution imposes changes to feature models in terms of edit operations. Ensuring consistency of concurrent edits requires appropriate conflict detection techniques. However, recent approaches fail to handle crucial subtleties of extended feature models, namely constraints mixing feature-tree patterns with first-order logic formulas over non-Boolean feature attributes with potentially infinite value domains. In this paper, we propose a novel conflict detection approach based on symbolic graph transformation to facilitate concurrent edits on extended feature models. We describe extended feature models formally with symbolic graphs and edit operations with symbolic graph transformation rules combining graph patterns with first-order logic formulas. The approach is implemented by combining eMoflon with an SMT solver, and evaluated with respect to applicability.
Human review
Discussion
Know something about this paper? Leave a comment, or highlight any passage above to comment on it.