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Abstract
Understanding variability is essential to allow the configuration of software systems to diverse requirements. Variability-aware program analysis techniques have been proposed for analyzing the space of program variants. Such techniques are highly beneficial, e.g., to determine the potential impact of changes during maintenance. This article presents an interprocedural and configuration-aware change impact analysis (CIA) approach for determining the possibly impacted source code elements when changing the source code of a product family. The approach also supports engineers, who are adapting the code of specific product variants after an initial pre-configuration. The approach can be adapted to work with different variability mechanisms, it is more precise than existing CIA approaches, and it can be implemented using standard control flow and data flow analysis. We report evaluation results on the benefit and performance of the approach using industrial product lines.
| Originalsprache | Englisch |
|---|---|
| Seiten (von - bis) | 417-461 |
| Seitenumfang | 45 |
| Fachzeitschrift | Automated Software Engineering |
| Volume | 26 |
| Ausgabenummer | 2 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 15 Juni 2019 |
Wissenschaftszweige
- 102 Informatik
- 102022 Softwareentwicklung
- 102025 Verteilte Systeme
JKU-Schwerpunkte
- Digital Transformation
Projekte
- 2 Abgeschlossen
-
Multi-Modeling and Evolution in Software Ecosystems (M02)
Angerer, F. (Forscher*in), Feichtinger, K. (Forscher*in), Filsecker, T. (Forscher*in), Grimmer, A. (Forscher*in), Hinterreiter, D. (Forscher*in), Linsbauer, L. (Forscher*in), Rabiser, D. (Forscher*in) & Grünbacher, P. (Projektleiter*in)
01.02.2013 → 30.06.2020
Projekt: Geförderte Forschung › Andere Geldgeber
-
Christian Doppler Labor für Monitoring and Evolution of Very-Large-Scale Software Systems
Grünbacher, P. (Projektleiter*in)
01.02.2013 → 31.08.2020
Projekt: Geförderte Forschung › CDG - Christian Doppler Forschungsgesellschaft
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