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SmartDelta project: Automated quality assurance and optimization across product versions and variants
RISE Research Institutes of Sweden, Digital Systems, Industrial Systems. (Smart Industrial Automation)ORCID iD: 0000-0002-1512-0844
RISE Research Institutes of Sweden, Digital Systems, Industrial Systems. Mälardalen University, Sweden.ORCID iD: 0000-0001-6418-9971
Mälardalen University, Sweden.
Fraunhofer, Germany.
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2023 (English)In: Microprocessors and microsystems, ISSN 0141-9331, E-ISSN 1872-9436, p. 104967-104967, article id 104967Article in journal (Refereed) Published
Abstract [en]

Software systems are often built in increments with additional features or enhancements on top of existing products. This incremental development may result in the deterioration of certain quality aspects. In other words, the software can be considered an evolving entity emanating different quality characteristics as it gets updated over time with new features or deployed in different operational environments. Approaching software development with this mindset and awareness regarding quality evolution over time can be a key factor for the long-term success of a company in today’s highly competitive market of industrial software-intensive products. Therefore, it is important to be able to accurately analyze and determine the quality implications of each change and increment to a software system. To address this challenge, the multinational SmartDelta project develops automated solutions for the quality assessment of product deltas in a continuous engineering environment. The project provides smart analytics from development artifacts and system executions, offering insights into quality degradation or improvements across different product versions, and providing recommendations for the next builds. This paper presents the challenges in incremental software development tackled in the scope of the SmartDelta project, and the solutions that are produced and planned in the project, along with the industrial impact of the project for software-intensive industrial systems.

Place, publisher, year, edition, pages
2023. p. 104967-104967, article id 104967
National Category
Software Engineering Computer and Information Sciences Computer Sciences
Identifiers
URN: urn:nbn:se:ri:diva-67581DOI: 10.1016/j.micpro.2023.104967OAI: oai:DiVA.org:ri-67581DiVA, id: diva2:1808831
Funder
Vinnova, 2021-04730
Note

This work has been supported by and done in the scope of theITEA3 SmartDelta project, which has been funded by the nationalfunding authorities of the participating countries: https://itea4.org/project/smartdelta.html. Vinnova: 2021-04730

Available from: 2023-11-01 Created: 2023-11-01 Last updated: 2023-11-03Bibliographically approved

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Saadatmand, MehrdadAbbas, Muhammad

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