A Survey for What Developers Require in AI-powered Tools that Aid in Component Selection in CBSD
April 18, 2025 ยท The Cartographer ยท ๐ International Conference on Evaluation & Assessment in Software Engineering
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"Title-pattern auto-detect: A Survey for What Developers Require in AI-powered Tools that Aid in Component Selection in CBSD"
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Authors
Mahdi Jaberzadeh Ansari, Ann Barcomb
arXiv ID
2504.13751
Category
cs.SE: Software Engineering
Cross-listed
cs.AI,
cs.CY
Citations
0
Venue
International Conference on Evaluation & Assessment in Software Engineering
Last Checked
4 days ago
Abstract
Although it has been more than four decades that the first components-based software development (CBSD) studies were conducted, there is still no standard method or tool for component selection which is widely accepted by the industry. The gulf between industry and academia contributes to the lack of an accepted tool. We conducted a mixed methods survey of nearly 100 people engaged in component-based software engineering practice or research to better understand the problems facing industry, how these needs could be addressed, and current best practices employed in component selection. We also sought to identify and prioritize quality criteria for component selection from an industry perspective. In response to the call for CBSD component selection tools to incorporate recent technical advances, we also explored the perceptions of professionals about AI-driven tools, present and envisioned.
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