Software Quality for AI - Where We Are Now?

Valentina Lenarduzzi; Francesco Lomio; Sergio Moreschini; Davide Taibi; Damian Andrew Tamburri

doi:10.1007/978-3-030-65854-0_4

Software Quality for AI - Where We Are Now?

Valentina Lenarduzzi, Francesco Lomio, Sergio Moreschini, Davide Taibi, Damian Andrew Tamburri

Data Governance

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

26 Citations (Scopus)

Abstract

Artificial Intelligence is getting more and more popular, being adopted in a large number of applications and technology we use on a daily basis. However, a large number of Artificial Intelligence applications are produced by developers without proper training on software quality practices or processes, and in general, lack in-depth knowledge regarding software engineering processes. The main reason is due to the fact that the machine-learning engineer profession has been born very recently, and currently there is a very limited number of training or guidelines on issues (such as code quality or testing) for machine learning and applications using machine learning code. In this work, we aim at highlighting the main software quality issues of Artificial Intelligence systems, with a central focus on machine learning code, based on the experience of our four research groups. Moreover, we aim at defining a shared research road map, that we would like to discuss and to follow in collaboration with the workshop participants. As a result, the software quality of AI-enabled systems is often poorly tested and of very low quality.

Original language	English
Title of host publication	Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021
Subtitle of host publication	Future Perspectives on Software Engineering Quality - 13th International Conference, SWQD 2021, Proceedings
Editors	Dietmar Winkler, Stefan Biffl, Daniel Mendez, Manuel Wimmer, Johannes Bergsmann
Publisher	Springer
Pages	43-53
Number of pages	11
ISBN (Electronic)	978-3-030-65854-0
ISBN (Print)	978-3-030-65853-3
DOIs	https://doi.org/10.1007/978-3-030-65854-0_4
Publication status	Published - 2021

Publication series

Name	Lecture Notes in Business Information Processing
Volume	404
ISSN (Print)	1865-1348
ISSN (Electronic)	1865-1356

Bibliographical note

DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.

Keywords

AI software
Software quality

Access to Document

10.1007/978-3-030-65854-0_4

Cite this

Lenarduzzi, V., Lomio, F., Moreschini, S., Taibi, D., & Tamburri, D. A. (2021). Software Quality for AI - Where We Are Now? In D. Winkler, S. Biffl, D. Mendez, M. Wimmer, & J. Bergsmann (Eds.), Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021: Future Perspectives on Software Engineering Quality - 13th International Conference, SWQD 2021, Proceedings (pp. 43-53). (Lecture Notes in Business Information Processing; Vol. 404). Springer. https://doi.org/10.1007/978-3-030-65854-0_4

Lenarduzzi, Valentina ; Lomio, Francesco ; Moreschini, Sergio et al. / Software Quality for AI - Where We Are Now?. Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021: Future Perspectives on Software Engineering Quality - 13th International Conference, SWQD 2021, Proceedings. editor / Dietmar Winkler ; Stefan Biffl ; Daniel Mendez ; Manuel Wimmer ; Johannes Bergsmann. Springer, 2021. pp. 43-53 (Lecture Notes in Business Information Processing).

@inproceedings{35f1c1ba985b45b5b7680265af251106,

title = "Software Quality for AI - Where We Are Now?",

abstract = "Artificial Intelligence is getting more and more popular, being adopted in a large number of applications and technology we use on a daily basis. However, a large number of Artificial Intelligence applications are produced by developers without proper training on software quality practices or processes, and in general, lack in-depth knowledge regarding software engineering processes. The main reason is due to the fact that the machine-learning engineer profession has been born very recently, and currently there is a very limited number of training or guidelines on issues (such as code quality or testing) for machine learning and applications using machine learning code. In this work, we aim at highlighting the main software quality issues of Artificial Intelligence systems, with a central focus on machine learning code, based on the experience of our four research groups. Moreover, we aim at defining a shared research road map, that we would like to discuss and to follow in collaboration with the workshop participants. As a result, the software quality of AI-enabled systems is often poorly tested and of very low quality.",

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author = "Valentina Lenarduzzi and Francesco Lomio and Sergio Moreschini and Davide Taibi and Tamburri, {Damian Andrew}",

note = "DBLP's bibliographic metadata records provided through http://dblp.org/search/publ/api are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.",

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Lenarduzzi, V, Lomio, F, Moreschini, S, Taibi, D & Tamburri, DA 2021, Software Quality for AI - Where We Are Now? in D Winkler, S Biffl, D Mendez, M Wimmer & J Bergsmann (eds), Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021: Future Perspectives on Software Engineering Quality - 13th International Conference, SWQD 2021, Proceedings. Lecture Notes in Business Information Processing, vol. 404, Springer, pp. 43-53. https://doi.org/10.1007/978-3-030-65854-0_4

Software Quality for AI - Where We Are Now? / Lenarduzzi, Valentina; Lomio, Francesco; Moreschini, Sergio et al.
Software Quality: Future Perspectives on Software Engineering Quality. SWQD 2021: Future Perspectives on Software Engineering Quality - 13th International Conference, SWQD 2021, Proceedings. ed. / Dietmar Winkler; Stefan Biffl; Daniel Mendez; Manuel Wimmer; Johannes Bergsmann. Springer, 2021. p. 43-53 (Lecture Notes in Business Information Processing; Vol. 404).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review