1 citations · 2 across the 15 of their papers we have counts for
13 papers · 1 filter
Empirical Analysis and Detection of Hallucinations in LLM-Generated Bug Report Summaries
Hinduja Nirujan, Shreyas Patil, Abdallah Ayoub +2
Large Language Models (LLMs) are increasingly used to generate summaries of software bug reports, including sections such as Steps-to-Reproduce (S2R), Actual Behavior (AB), and Exp…
What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook
Junyu Huo, Ziqi Mao, Zihao Wan +1
AI agents are increasingly framed as software-engineering teammates, yet most studies examine them inside human-centered workflows. Little is known about the discourse autonomous A…
Exploring Ethical Concerns of Mobile Applications from App Reviews: A Literature Survey
Aakash Sorathiya, Gouri Ginde
Privacy, security, and accessibility, like ethical concerns in mobile applications (a.k.a. apps), commonly subsumed under non-functional requirements, are generally reported by use…
Towards Energy-aware Requirements Dependency Classification: Knowledge-Graph vs. Vector-Retrieval Augmented Inference with SLMs
Shreyas Patil, Pragati Kumari, Novarun Deb +1
The continuous evolution of system specifications necessitates frequent evaluation of conflicting requirements, a process that is traditionally labour intensive. Although large lan…
SAGE: A Context-Aware Approach for Mining Privacy Requirements Relevant Reviews from Mental Health Apps
Aakash Sorathiya, Gouri Ginde
Mental health (MH) apps often require sensitive user data to customize services for mental wellness needs. However, such data collection practices in some MH apps raise significant…
CMER: A Context-Aware Approach for Mining Ethical Concern-related App Reviews
Aakash Sorathiya, Gouri Ginde
With the increasing proliferation of mobile applications in our daily lives, the concerns surrounding ethics have surged significantly. Users communicate their feedback in app revi…