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Siebert, J., Joeckel, L., Heidrich, J., Trendowicz, A., Nakamichi, K., Ohashi, K., Namba, I., Yamamoto, R. and Aoyama, M. (2021) Construction of a Quality Model for Machine Learning Systems. Software Quality Journal, 30, 307-335.
https://doi.org/10.1007/s11219-021-09557-y

has been cited by the following article:

• TITLE: ISO25000-Related Metrics for Evaluating the Quality of Complex Information Systems

  AUTHORS: Antonia Stefani, Bill Vassiliadis

  KEYWORDS: Software Quality, Information Systems, Quality Standards, Quality Metrics, ISO25000

  JOURNAL NAME: Journal of Computer and Communications, Vol.11 No.9, September 20, 2023

  ABSTRACT: Evaluating complex information systems necessitates deep contextual knowledge of technology, user needs, and quality. The quality evaluation challenges increase with the system’s complexity, especially when multiple services supported by varied technological modules, are offered. Existing standards for software quality, such as the ISO25000 series, provide a broad framework for evaluation. Broadness offers initial implementation ease albeit, it often lacks specificity to cater to individual system modules. This paper maps 48 data metrics and 175 software metrics on specific system modules while aligning them with ISO standard quality traits. Using the ISO25000 series as a foundation, especially ISO25010 and 25012, this research seeks to augment the applicability of these standards to multi-faceted systems, exemplified by five distinct software modules prevalent in modern information ecosystems.