A Systematic Mapping of Quality Models for AI Systems, Software and Components

Recently, there has been a significant increase in the number of Artificial Intelligence (AI) systems, software, and components. As a result, it is crucial to evaluate their quality. Quality models for AI have in fact been proposed, but there is a lack of Systematic Mapping Studies (SMS) for quality...

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Bibliographic Details
Published in:	Applied sciences Vol. 12; no. 17; p. 8700
Main Authors:	Ali, Mohamed Abdullahi, Yap, Ng Keng, Ghani, Abdul Azim Abd, Zulzalil, Hazura, Admodisastro, Novia Indriaty, Najafabadi, Amin Arab
Format:	Journal Article
Language:	English
Published:	Basel MDPI AG 01-09-2022
Subjects:	Algorithms Artificial intelligence artificial intelligence software and systems data driven software components Decision making Deep learning Efficiency Evaluation ISO standards Linear algebra Machine learning Mapping Natural language processing Neural networks quality model R&D Research & development Software software components Software engineering Software quality Usability
Online Access:	Get full text
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Summary:	Recently, there has been a significant increase in the number of Artificial Intelligence (AI) systems, software, and components. As a result, it is crucial to evaluate their quality. Quality models for AI have in fact been proposed, but there is a lack of Systematic Mapping Studies (SMS) for quality models in AI systems, software, and components. The goal of this paper is to understand, classify, and critically evaluate existing quality models for AI systems, software, and components. This study conducts an SMS to investigate quality models proposed by various authors in the past. The study only found quality models for AI systems and software. So far, the SMS has revealed no work on AI software component quality models. Finally, the limitations of the quality models and the implications for future research and development efforts are discussed.
ISSN:	2076-3417 2076-3417
DOI:	10.3390/app12178700