How Do Developers Search for Architectural Information? An Industrial Survey

Dieu, Musengamana Jean de; Liang, Peng; Shahin, Mojtaba

doi:10.1109/icsa53651.2022.00014

Cited by 7 publications

(10 citation statements)

References 35 publications

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“…These results also support the findings by Soliman et al in [6] that SO should be considered as one of the important sources of architectural knowledge. Moreover, practitioners reported Q&A sites (e.g., Stack Overflow) as the most useful when searching architectural information according to our recent industrial survey [4]. Thus, practitioners could rely well on SO to identify, such as, the benefits and drawbacks of architecture solutions in certain application domains, for example, the benefits and drawbacks about the framework for iOS applications in our taxonomy (see Figure 4) for architecture implementation.…”

Section: Identified Categories Of Arps In So Could Support Architecti...mentioning

confidence: 98%

“…The process was carried out by using a SQL query through the query interface provided by StackExchange Data Explorer 3 , which is a web interface that allows the execution of SQL queries on data from Q&A sites, including SO. After the pilot search with the mentioned terms, we saw that SO users mostly use the terms "design*" (i.e., "design" and "designing") in the programming context in SO, for instance, "singleton design pattern" 4 . Moreover, we were aware that Soliman et al [6] identified distinctive terms between ARPs and pure programming posts from their studied sample of SO posts.…”

Section: Rq6mentioning

confidence: 99%

“…Similarly to several existing studies (e.g., [4]), we used open coding & constant comparison to answer RQ1 and RQ3-RQ6 in our study. Open coding & constant comparison are two widely used techniques from Grounded Theory [17] during qualitative data analysis.…”

Section: Data Extraction and Analysismentioning

confidence: 99%

“…However, ever since this site started growing and being popular, architects have begun to share their competencies, experience, and design problems by asking architecture related questions or providing architecture solutions, such as architecture tactics. In our recent industrial survey on how developers search for architectural information [4], practitioners acknowledged Q&A sites (e.g., SO) as the most useful source of architectural information (e.g., benefits and drawbacks of architecture solutions). Hence, similar to searching and (re)using existing coding related answers provided in SO to solve programming related problems, software engineers (e.g., architects and developers) also search and (re)use existing architecture solutions in SO for addressing their design concerns.…”

Section: Introductionmentioning

confidence: 99%

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Characterizing Architecture Related Posts and Their Usefulness in Stack Overflow

Dieu¹,

Peng²,

Shahin³

et al. 2023

Preprint

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Context: Stack Overflow (SO) has won the intention from software engineers (e.g., architects) to learn, practice, and utilize development knowledge, such as Architectural Knowledge (AK). But little is known about AK communicated in SO, which is a type of high-level but important knowledge in development.Objective: This study aims to investigate the AK in SO posts in terms of their categories and characteristics as well as their usefulness from the point of view of SO users. Method:We conducted an exploratory study by qualitatively analyzing a statistically representative sample of 968 Architecture Related Posts (ARPs) from SO. Results:The main findings are: (1) architecture related questions can be classified into 9 core categories, in which "architecture configuration" is the most common category, followed by the "architecture decision" category, and (2) architecture related questions that provide clear descriptions together with architectural diagrams increase their likelihood of getting more than one answer, while poorly structured architecture questions tend to only get one answer. Conclusions:Our findings suggest that future research can focus on enabling automated approaches and tools that could facilitate the search and (re)use of AK in SO. SO users can refer to our proposed guidelines to compose architecture related questions with the likelihood of getting more responses in SO.

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Section: Identified Categories Of Arps In So Could Support Architecti...mentioning

confidence: 98%

Section: Rq6mentioning

confidence: 99%

Section: Data Extraction and Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Characterizing Architecture Related Posts and Their Usefulness in Stack Overflow

Dieu¹,

Peng²,

Shahin³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Empirical studies seldom explore quality concerns when confronted with the unpredictable challenges of software development, despite their significant impact on software quality improvement [377]. Recent work by Jean de Dieu et al [86] has conducted a survey study exploring information sources related to architectural decision-making. While searching for architectural information is crucial, it only provides partial knowledge about quality concerns.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Software Quality Maze: Detecting Scattered and Tangled Crosscutting Quality Concerns in Source Code in Support of Maintenance Tasks

Krasniqi

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Software quality attributes, such as reliability, security, and usability, are often well-defined and understood at the requirement level. They lay the ground foundation necessary to achieve high-quality, robust, user-friendly, and trustworthy software systems. However, when addressing these attributes at the code level, two significant challenges emerge. First, they tend to scatter across the codebase due to improper encapsulation of object-oriented classes, hampering the visibility of quality-related components across the codebase. Second, they become tangled within a single module due to intricate interdependencies with functional aspects of the code. Addressing quality concerns in the presence of scattered and tangled code can lead to unforeseen issues. For example, software developers may inadvertently introduce new and latent bugs or incorrectly implement code components deviating from the original system-wide requirements. To tackle these pressing issues, this dissertation proposes a series of state-of-the-art solutions integrating ML-based techniques and NLP-based techniques, including static program analysis techniques, to automatically and effectively detect and repair quality concerns present at the code level, even when scattered across the codebase. Additionally, we introduce program structural analysis and change impact analysis, complemented by other unsupervised ML-based techniques, to disentangle quality-related changes from functional ones, to gain a holistic understanding of a particular maintenance task. From a practical stance, our techniques can be integrated for quality risk assessment purposes and incorporated into safety-critical continuous integration systems to monitor the evolving nature of quality concerns. Furthermore, they can enhance bidirectional traceability across evolving software artifacts, such as bug reports, commit messages, and source code, and facilitate bug triaging systems for prioritizing the resolution of highly impacted quality-related bugs.

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