Towards Better Requirements from the Crowd: Developer Engagement with Feature Requests in Open Source Software
July 17, 2025 Β· Declared Dead Β· π 2025 IEEE 33rd International Requirements Engineering Conference Workshops (REW)
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Pragyan KC, Rambod Ghandiparsi, Thomas Herron, John Heaps, Mitra Bokaei Hosseini
arXiv ID
2507.13553
Category
cs.SE: Software Engineering
Citations
1
Venue
2025 IEEE 33rd International Requirements Engineering Conference Workshops (REW)
Last Checked
5 months ago
Abstract
As user demands evolve, effectively incorporating feature requests is crucial for maintaining software relevance and user satisfaction. Feature requests, typically expressed in natural language, often suffer from ambiguity or incomplete information due to communication gaps or the requester's limited technical expertise. These issues can lead to misinterpretation, faulty implementation, and reduced software quality. While seeking clarification from requesters is a common strategy to mitigate these risks, little is known about how developers engage in this clarification process in practice-how they formulate clarifying questions, seek technical or contextual details, align on goals and use cases, or decide to close requests without attempting clarification. This study investigates how feature requests are prone to NL defects (i.e. ambiguous or incomplete) and the conversational dynamics of clarification in open-source software (OSS) development, aiming to understand how developers handle ambiguous or incomplete feature requests. Our findings suggest that feature requests published on the OSS platforms do possess ambiguity and incompleteness, and in some cases, both. We also find that explicit clarification for the resolution of these defects is uncommon; developers usually focus on aligning with project goals rather than resolving unclear text. When clarification occurs, it emphasizes understanding user intent/goal and feasibility, rather than technical details. By characterizing the dynamics of clarification in open-source issue trackers, this work identifies patterns that can improve user-developer collaboration and inform best practices for handling feature requests effectively.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Software Engineering
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Microservices: yesterday, today, and tomorrow
π
π
The Cartographer
A Survey of Machine Learning for Big Code and Naturalness
R.I.P.
π»
Ghosted
An Overview on Smart Contracts: Challenges, Advances and Platforms
R.I.P.
π»
Ghosted
Slither: A Static Analysis Framework For Smart Contracts
R.I.P.
π»
Ghosted
ContractFuzzer: Fuzzing Smart Contracts for Vulnerability Detection
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted