arXiv subjects

Muneera Bano

Publications and source records attributed to Muneera Bano.

21 records · Page 2Linked to original sources

arXiv2023

Requirements Practices and Gaps When Engineering Human-Centered Artificial Intelligence Systems

[Context] Engineering Artificial Intelligence (AI) software is a relatively new area with many challenges, unknowns, and limited proven best practices. Big companies such as Google, Microsoft, and Apple have provided a suite of recent guidelines to assist engineering teams in building human-centered AI systems. [Objective] The practices currently adopted by practitioners for developing such systems, especially during Requirements Engineering (RE), are little studied and reported to date. [Method] This paper presents the results of a survey conducted to understand current industry practices in RE for AI (RE4AI) and to determine which key human-centered AI guidelines should be followed. Our survey is based on mapping existing industrial guidelines, best practices, and efforts in the literature. [Results] We surveyed 29 professionals and found most participants agreed that all the human-centered aspects we mapped should be addressed in RE. Further, we found that most participants were using UML or Microsoft Office to present requirements. [Conclusion] We identify that most of the tools currently used are not equipped to manage AI-based software, and the use of UML and Office may pose issues to the quality of requirements captured for AI. Also, all human-centered practices mapped from the guidelines should be included in RE.

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arXiv2022

Requirements Engineering for Artificial Intelligence Systems: A Systematic Mapping Study

[Context] In traditional software systems, Requirements Engineering (RE) activities are well-established and researched. However, building Artificial Intelligence (AI) based software with limited or no insight into the system's inner workings poses significant new challenges to RE. Existing literature has focused on using AI to manage RE activities, with limited research on RE for AI (RE4AI). [Objective] This paper investigates current approaches for specifying requirements for AI systems, identifies available frameworks, methodologies, tools, and techniques used to model requirements, and finds existing challenges and limitations. [Method] We performed a systematic mapping study to find papers on current RE4AI approaches. We identified 43 primary studies and analysed the existing methodologies, models, tools, and techniques used to specify and model requirements in real-world scenarios. [Results] We found several challenges and limitations of existing RE4AI practices. The findings highlighted that current RE applications were not adequately adaptable for building AI systems and emphasised the need to provide new techniques and tools to support RE4AI. [Conclusion] Our results showed that most of the empirical studies on RE4AI focused on autonomous, self-driving vehicles and managing data requirements, and areas such as ethics, trust, and explainability need further research.

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arXiv2021

Alignment of Stakeholder Expectations about User Involvement in Agile Software Development

Context: User involvement is generally considered to contributing to user satisfaction and project success and is central to Agile software development. In theory, the expectations about user involvement, such as the PO's, are quite demanding in this Agile way of working. But what are the expectations seen in practice, and are the expectations of user involvement aligned among the development team and users? Any misalignment could contribute to conflict and miscommunication among stakeholders that may result in ineffective user involvement. Objective: Our aim is to compare and contrast the expectations of two stakeholder groups (software development team, and software users) about user involvement in order to understand the expectations and assess their alignment. Method: We have conducted an exploratory case study of expectations about user involvement in an Agile software development. Qualitative data was collected through interviews to design a novel method for the assessing the alignment of expectations about user involvement by applying Repertory Grids (RG). Results: By aggregating the results from the interviews and RGs, varying degrees of expectation alignments were observed between the development team and user representatives. Conclusion: Alignment of expectations can be assessed in practice using the proposed RG instrument and can reveal misalignment between user roles and activities they participate in Agile software development projects. Although we used RG instrument retrospectively in this study, we posit that it could also be applied from the start of a project, or proactively as a diagnostic tool throughout a project to assess and ensure that expectations are aligned.

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