Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach
This program is tentative and subject to change.
Over the past decade, app store (AppStore)-inspired requirements elicitation has proven to be highly beneficial. Developers often explore competitors’ apps to gather inspiration for new app features. With the advance of Generative AI, recent studies have demonstrated the potential of large language model (LLM)-inspired requirements elicitation. LLMs can assist in this process by providing inspiration for new feature ideas. While both approaches are gaining popularity in practice, there is limited insight into their comparison. We report on a comparative study between AppStore-inspired and LLM-inspired approaches for refining features into sub-features. By manually analyzing 1,200 sub-features recommended from both approaches, we identified their benefits, challenges, and key differences.
This program is tentative and subject to change.
Tue 29 OctDisplayed time zone: Pacific Time (US & Canada) change
10:30 - 12:00 | |||
10:30 15mTalk | Getting Inspiration for Feature Elicitation: App Store- vs. LLM-based Approach Research Papers Jialiang Wei EuroMov DHM, Univ Montpellier & IMT Mines Ales, Anne-Lise Courbis IMT Mines Alès, Thomas Lambolais IMT Mines Alès, Binbin Xu IMT Mines Alès, Pierre Louis Bernard University of Montpellier, Gerard Dray IMT Mines Alès, Walid Maalej University of Hamburg Pre-print | ||
10:45 15mTalk | Efficient Slicing of Feature Models via Projected d-DNNF Compilation Research Papers | ||
11:00 15mTalk | Learning-based Relaxation of Completeness Requirements for Data Entry Forms Journal-first Papers Hichem Belgacem Luxembourg Institute of Science and Technology, Xiaochen Li Dalian University of Technology, Domenico Bianculli University of Luxembourg, Lionel Briand University of Ottawa, Canada; Lero centre, University of Limerick, Ireland | ||
11:15 15mTalk | Blackbox Observability of Features and Feature Interactions Research Papers Kallistos Weis Saarland University, Leopoldo Teixeira Federal University of Pernambuco, Clemens Dubslaff Eindhoven University of Technology, Sven Apel Saarland University Pre-print | ||
11:30 15mTalk | AVIATE: Exploiting Translation Variants of Artifacts to Improve IR-based Traceability Recovery in Bilingual Software Projects Research Papers Kexin Sun Nanjing University, Yiding Ren Nanjing University, Hongyu Kuang Nanjing University, Hui Gao Nanjing University, Xiaoxing Ma State Key Laboratory for Novel Software Technology, Nanjing University, Guoping Rong Nanjing University, Dong Shao Nanjing University, He Zhang Nanjing University Pre-print | ||
11:45 10mTalk | Translation Titans, Reasoning Challenges: Satisfiability-Aided Language Models for Detecting Conflicting Requirements NIER Track Mohamad Fazelnia University of Hawaii at Manoa, Mehdi Mirakhorli University of Hawaii at Manoa, Hamid Bagheri University of Nebraska-Lincoln | ||