Towards a Software Engineering Framework for the Design, Construction and Deployment of Machine Learning-Based Solutions in Digitalization Processes

  • Ricardo Colomo-PalaciosEmail author
Conference paper
Part of the Springer Proceedings in Complexity book series (SPCOM)


There is an increasing demand of digitalization technologies in almost all aspects in modern life. A swelling part of these technologies and solutions are based on Machine Learning technologies. As a consequence of this, there is a need to develop these solutions in a sound and solid way to increase software quality in its eight characteristics: functional suitability, reliability, performance efficiency, usability, security, compatibility, maintainability and portability. To do so, it is needed to adopt software engineering and information systems standards to support the process. This paper aims to draw the path towards a framework to support digitalization processes based on machine-learning solutions.


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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Østfold University CollegeHaldenNorway

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