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Requirements Engineering 2021
Mon 20 - Fri 24 September 2021
Wed 22 Sep 2021 08:20 - 08:50 at Basilica - RE 4 AI Chair(s): Travis Breaux

In traditional approaches to building software systems (that do not include an Artificial Intelligent (AI) or Machine Learning (ML) component), Requirements Engineering (RE) activities are well-established and researched. However, building software systems with one or more AI components may depend heavily on data with limited or no insight into the system’s workings. Therefore, engineering such systems poses significant new challenges to RE. Our search showed that literature has focused on using AI to manage RE activities, with limited research on RE for AI (RE4AI). Our study’s main objective was to investigate current approaches in writing requirements for AI/ML systems, identify available tools and techniques used to model requirements, and find existing challenges and limitations. We performed a Systematic Literature Review (SLR) of current RE4AI methods and identified 27 primary studies. Using these studies, we analysed the key tools and techniques used to specify and model requirements and found several challenges and limitations of existing RE4AI practices. We further provide recommendations for future research, based on our analysis of the primary studies and mapping to industry guidelines in Google PAIR). The SLR findings highlighted that present RE applications were not adaptive to manage most AI/ML systems and emphasised the need to provide new techniques and tools to support RE4AI.

Wed 22 Sep

Displayed time zone: Eastern Time (US & Canada) change

08:20 - 09:20
RE 4 AIResearch Papers at Basilica
Chair(s): Travis Breaux Carnegie Mellon University

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What’s up with Requirements Engineering for Artificial Intelligence Systems?Research Paper
Research Papers
Khlood Ahmad Deakin University, Muneera Bano School of Information Technology, Deakin University, Mohamed Abdelrazek Deakin University, Australia, Chetan Arora Deakin University, John Grundy Monash University
Non-functional Requirements for Machine Learning: Understanding Current Use and Challenges in IndustryResearch Paper
Research Papers
Khan Mohammad Habibullah University of Gothenburg, Jennifer Horkoff Chalmers and the University of Gothenburg