11 citations · 18 across the 11 of their papers we have counts for
11 papers
Monitoring Machine Learning Systems: A Multivocal Literature Review
Hira Naveed, Scott Barnett, Chetan Arora +3
Context: Dynamic production environments make it challenging to maintain reliable machine learning (ML) systems. Runtime issues, such as changes in data patterns or operating conte…
Understanding Practitioners Perspectives on Monitoring Machine Learning Systems
Hira Naveed, John Grundy, Chetan Arora +2
Given the inherent non-deterministic nature of machine learning (ML) systems, their behavior in production environments can lead to unforeseen and potentially dangerous outcomes. F…
Ethical Concerns of Generative AI and Mitigation Strategies: A Systematic Mapping Study
Yutan Huang, Chetan Arora, Wen Cheng Houng +3
[Context] Generative AI technologies, particularly Large Language Models (LLMs), have transformed numerous domains by enhancing convenience and efficiency in information retrieval,…
Managing Human-Centric Software Defects: Insights from GitHub and Practitioners' Perspectives
Vedant Chauhan, Chetan Arora, Hourieh Khalajzadeh +1
Context: Human-centric defects (HCDs) are nuanced and subjective defects that often occur due to end-user perceptions or differences, such as their genders, ages, cultures, languag…
Unlocking Adaptive User Experience with Generative AI
Yutan Huang, Tanjila Kanij, Anuradha Madugalla +3
Developing user-centred applications that address diverse user needs requires rigorous user research. This is time, effort and cost-consuming. With the recent rise of generative AI…
Towards Standards-Compliant Assistive Technology Product Specifications via LLMs
Chetan Arora, John Grundy, Louise Puli +1
In the rapidly evolving field of assistive technology (AT), ensuring that products meet national and international standards is essential for user safety, efficacy, and accessibili…
Who Uses Personas in Requirements Engineering: The Practitioners' Perspective
Yi Wang, Chetan Arora, Xiao Liu +4
Personas are commonly used in software projects to gain a better understanding of end-users' needs. However, there is a limited understanding of their usage and effectiveness in pr…
How do software practitioners perceive human-centric defects?
Vedant Chauhan, Chetan Arora, Hourieh Khalajzadeh +1
Context: Human-centric software design and development focuses on how users want to carry out their tasks rather than making users accommodate their software. Software users can ha…
Fairness Concerns in App Reviews: A Study on AI-based Mobile Apps
Ali Rezaei Nasab, Maedeh Dashti, Mojtaba Shahin +4
Fairness is one of the socio-technical concerns that must be addressed in software systems. Considering the popularity of mobile software applications (apps) among a wide range of…
Model-driven Engineering for Machine Learning Components: A Systematic Literature Review
Hira Naveed, Chetan Arora, Hourieh Khalajzadeh +2
Context: Machine Learning (ML) has become widely adopted as a component in many modern software applications. Due to the large volumes of data available, organizations want to incr…
Advancing Requirements Engineering through Generative AI: Assessing the Role of LLMs
Chetan Arora, John Grundy, Mohamed Abdelrazek
Requirements Engineering (RE) is a critical phase in software development including the elicitation, analysis, specification, and validation of software requirements. Despite the i…