What is Software Quality for AI Engineers? Towards a Thinning of the Fog (CAIN 2022 - - 1st International Conference on AI Engineering - Software Engineering for AI)

Who

Valentina Golendukhina, Valentina Lenarduzzi, Michael Felderer

Track

CAIN 2022

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When

Mon 16 May 2022 06:30 - 06:45 at CAIN main room - Quality Assurance Chair(s): Henry Muccini

Abstract

Background. It is often overseen that AI-enabled systems are also software systems and therefore rely on software quality assurance (SQA) Objective. The goal of this study is therefore to investigate the software quality assurance strategies adopted during the development, integration, and maintenance of AI/ML components and code. Method. We conducted semi-structured interviews with representatives of ten Austrian SMEs that develop AI-enabled systems. Results. A qualitative analysis of the interview data identified 12 issues in the development of AI/ML components. Furthermore, we identified when quality issues arise in AI/ML components and how they are detected. Conclusion. The results of this study should guide future work on software quality assurance processes and techniques for AI/ML components.

Valentina Golendukhina

University of Innsbruck

Valentina Lenarduzzi

University of Oulu

Finland

Michael Felderer

University of Innsbruck

Austria

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Session Program

Mon 16 May
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06:30 - 07:30	Quality AssuranceCAIN 2022 at CAIN main room Chair(s): Henry Muccini University of L'Aquila, Italy

06:30 15m Research paper		What is Software Quality for AI Engineers? Towards a Thinning of the FogResearch Paper CAIN 2022 Valentina Golendukhina University of Innsbruck, Valentina Lenarduzzi University of Oulu, Michael Felderer University of Innsbruck
06:45 15m Research paper		Exploring ML testing in practice - Lessons learned from an interactive rapid review with Axis CommunicationsResearch Paper CAIN 2022 Qunying Song Lund University, Markus Borg RISE Research Institutes of Sweden, Emelie Engstrom Lund University, Håkan Ardö Axis Communications, Lund, Sweden, Sergio Rico Lund University, Sweden Pre-print
07:00 15m Research paper		Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language PracticeResearch Paper CAIN 2022 Markus Borg RISE Research Institutes of Sweden, Johan Bengtsson Lund University, Harald Österling Lund University, Alexander Hagelborn NordAxon AB, Isabella Gagner NordAxon AB, Piotr Tomaszewski RISE Research Institutes of Sweden
07:15 15m Other		Discussion on Quality Assurance CAIN 2022

Information for Participants

Mon 16 May 2022 06:30 - 07:30 at CAIN main room - Quality Assurance Chair(s): Henry Muccini

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