Lessons Learned from Analyzing Requirements Traceability using a Graph Database
| dc.contributor.author | Goman, Maksim | |
| dc.contributor.author | Rath, Michael | |
| dc.contributor.author | Mäder, Patrick | |
| dc.date.accessioned | 2023-03-02T10:35:53Z | |
| dc.date.available | 2023-03-02T10:35:53Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | Established traceability among development artifacts allows to apply structured analysis in order to answer questions posed by stakeholders. Typically, the artifacts and their links are stored in relational databases. However, answering trace related questions involves finding paths and patterns in the artifact graph - a difficult task to perform using generic query languages. Mapping the artifact and link data onto graph databases and utilizing specialized query languages may overcome this limitation. In this paper, this mapping from a relational traceability dataset to a graph database is demonstrated. Afterwards, the advantages and disadvantages of the approach are investigated by calculating three trace metrics, heavily relying on graph patterns, using a graph query language. Overall, utilizing a graph database proved to simplify traceability analysis. | en |
| dc.identifier.pissn | 0720-8928 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/40541 | |
| dc.language.iso | en | |
| dc.publisher | Geselllschaft für Informatik e.V. | |
| dc.relation.ispartof | Softwaretechnik-Trends Band 38, Heft 1 | |
| dc.title | Lessons Learned from Analyzing Requirements Traceability using a Graph Database | en |
| dc.type | Text/Journal Article | |
| gi.citation.endPage | 30 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 27 | |
| gi.conference.sessiontitle | FG ARC: Workshop des Arbeitskreises "Traceability/Evolution", 27.10.2017, Technische Universität Ilmenau |
Dateien
Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
- Name:
- ARC_AKTE_2017_p8_goman.pdf
- Größe:
- 365.05 KB
- Format:
- Adobe Portable Document Format