arXiv subjects

Nitish Patkar

Publications and source records attributed to Nitish Patkar.

3 recordsLinked to original sources

arXiv2026

From Perception to Action: Can UI Interventions Foster Sustainable LLM Chatbot

LLM-powered chatbots are increasingly embedded in everyday workflows, raising sustainability concerns due to their energy use. Most mitigation strategies emphasize model or infrastructure efficiency, while the user-interface (UI) layer remains underexplored despite its potential to shape interaction behavior. We investigate whether sustainability-oriented UI interventions can increase users' energy awareness and encourage more energy-responsible chatbot use without reducing usability. We first conducted a baseline survey with 77 participants to assess awareness and receptiveness to intervention concepts. Guided by prior work on persuasive technology and choice architecture, we implemented a web-based chatbot prototype with a three-mode switch (Energy-efficient, Balanced, Performance), per-response energy feedback, pre-send energy estimates, a usage metrics dashboard, and energy analogies. We then evaluated the prototype in a five-day field study with 11 participants. In the baseline survey, 94.8% of respondents reported at least some awareness of AI energy use, yet 88.3% misestimated actual consumption. Although concern about environmental impact was high, only 39.0% indicated willingness to accept a performance trade-off for lower energy use. In the field study, Energy-efficient mode accounted for 55.8% of logged prompts, while 90.9% self-reported actively choosing Eco-mode when high accuracy was not required. Participants did not reduce prompt length, suggesting mode switching as the primary behavioral mechanism. Sustainability-oriented UI interventions can improve awareness and support more energy-responsible interaction patterns in LLM chatbots. These effects are best interpreted as behavioral and model-based estimates that complement backend efficiency work, and the provided prototype and replication package support further research on energy-aware conversational AI design.

cs.SE↗

arXiv2025

What is a Feature, Really? Toward a Unified Understanding Across SE Disciplines

In software engineering, the concept of a ``feature'' is widely used but inconsistently defined across disciplines such as requirements engineering (RE) and software product lines (SPL). This lack of consistency often results in communication gaps, rework, and inefficiencies in projects. To address these challenges, this paper proposes an empirical, data-driven approach to explore how features are described, implemented, and managed across real-world projects, starting with open-source software (OSS). By analyzing feature-related branches in OSS repositories, we identify patterns in contributor behavior, feature implementation, and project management activities. Our findings provide actionable insights to improve project planning, resource allocation, and team coordination. Additionally, we outline a roadmap to unify the understanding of features across software engineering disciplines. This research aims to bridge gaps between academic inquiry and practical strategies, fostering better feature planning and development workflows in diverse project environments.

cs.SE↗

arXiv2020

Caveats in Eliciting Mobile App Requirements

Factors such as app stores or platform choices heavily affect functional and non-functional mobile app requirements. We surveyed 45 companies and interviewed ten experts to explore how factors that impact mobile app requirements are understood by requirements engineers in the mobile app industry. We observed a lack of knowledge in several areas. For instance, we observed that all practitioners were aware of data privacy concerns, however, they did not know that certain third-party libraries, usage aggregators, or advertising libraries also occasionally leak sensitive user data. Similarly, certain functional requirements may not be implementable in the absence of a third-party library that is either banned from an app store for policy violations or lacks features, for instance, missing desired features in ARKit library for iOS made practitioners turn to Android. We conclude that requirements engineers should have adequate technical experience with mobile app development as well as sufficient knowledge in areas such as privacy, security and law, in order to make informed decisions during requirements elicitation.

cs.SE↗