Exploring Web Search Engines to Find Architectural Knowledge
| dc.contributor.author | Soliman, Mohamed | |
| dc.contributor.author | Wiese, Marion | |
| dc.contributor.author | Li, Yikun | |
| dc.contributor.author | Riebisch, Matthias | |
| dc.contributor.author | Avgeriou, Paris | |
| dc.contributor.editor | Grunske, Lars | |
| dc.contributor.editor | Siegmund, Janet | |
| dc.contributor.editor | Vogelsang, Andreas | |
| dc.date.accessioned | 2022-01-19T12:56:55Z | |
| dc.date.available | 2022-01-19T12:56:55Z | |
| dc.date.issued | 2022 | |
| dc.description.abstract | Software engineers need relevant and up-to-date architectural knowledge (AK), in order to make well-founded design decisions. However, finding such AK is quite challenging. One pragmatic approach is to search for AK on the web using traditional search engines (e.g. Google); this is common practice among software engineers. Still, we know very little about what AK is retrieved, from where, and how useful it is. In this paper, we conduct an empirical study with 53 software engineers, who used Google to make design decisions using the Attribute-Driven-Design method. Based on how the subjects assessed the nature and relevance of the retrieved results, we determined how effective web search engines are to find relevant architectural information. Moreover, we identified the different sources of AK on the web and their associated AK concepts. | en |
| dc.identifier.doi | 10.18420/se2022-ws-029 | |
| dc.identifier.isbn | 978-3-88579-714-2 | |
| dc.identifier.pissn | 1617-5468 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/37982 | |
| dc.language.iso | en | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Software Engineering 2022 | |
| dc.relation.ispartofseries | Lecture Notes in Informatics (LNI) - Proceedings, Volume P-320 | |
| dc.subject | software architecture | |
| dc.subject | architecture knowledge | |
| dc.subject | search approach | |
| dc.subject | ||
| dc.title | Exploring Web Search Engines to Find Architectural Knowledge | en |
| dc.type | Text/Conference Paper | |
| gi.citation.endPage | 86 | |
| gi.citation.publisherPlace | Bonn | |
| gi.citation.startPage | 85 | |
| gi.conference.date | 21.-25. Feburar 2022 | |
| gi.conference.location | Berlin/Virtuell | |
| gi.conference.sessiontitle | Wissenschaftliches Hauptprogramm |
Dateien
Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
- Name:
- A1-29.pdf
- Größe:
- 245.57 KB
- Format:
- Adobe Portable Document Format