Exploring Web Search Engines to Find Architectural Knowledge

被引：12

作者：

Soliman, Mohamed ^{[1
]}

Wiese, Marion ^{[2
]}

Li, Yikun ^{[1
]}

Riebisch, Matthias ^{[2
]}

Avgeriou, Paris ^{[1
]}

机构：

[1] Univ Groningen, Bernoulli Inst Math Comp Sci & Artificial Intelli, Groningen, Netherlands

[2] Univ Hamburg, Dept Informat, Hamburg, Germany

来源：

2021 IEEE 18TH INTERNATIONAL CONFERENCE ON SOFTWARE ARCHITECTURE (ICSA) | 2021年

关键词：

Architecture knowledge; Architecture design decisions; Search engines; DECISIONS;

D O I：

10.1109/ICSA51549.2021.00023

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：162 / 172

页数：11

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