Alaleh Hamidi

dblp:307/5556 · DBLP profile ↗
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2ranked-venue papers
1as first author
2since 2021 · last 2023
—ORCID · none

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Software engineering, systems software and programming languages · 2 · 1 first-author · 2 since 2021
YearPublicationVenuePosition
2023 Machine learning application development: practitioners' insights
Md. Saidur Rahman 0002, Foutse Khomh, Alaleh Hamidi, Jinghui Cheng 0001, Giuliano Antoniol, Hironori Washizaki
Softw. Qual. J.3
2021 Towards Understanding Developers' Machine-Learning Challenges: A Multi-Language Study on Stack Overflow
abstract
Machine Learning (ML) is increasingly being used as an essential component of modern software systems. Also, the maturity of the adopted techniques and the availability of frameworks have changed the way developers approach ML-related development problems. This paper aims at investigating, by analyzing Stack Overflow (SO) posts related to ML, how the questions about ML have been changing over the years, and across six different programming languages. We analyzed 43,950 SO posts in the period 2008-2020, studying (i) how the number of ML-related posts changes over time for each programming language, (ii) how the posts are distributed across different phases of a ML pipeline, and (iii) whether posts belonging to different languages or phases are more or less challenging to address. We found that some programming languages are fading while others are becoming more popular in ML development. While model-building questions are the most discussed in general, the level of challenges posed by the other phases of the ML pipeline appears to be language-dependent. Results of this work could be used to better understand ML challenges in different programming languages, and, possibly, to improve ML tutorials related to different languages.
Alaleh Hamidi, Giuliano Antoniol, Foutse Khomh, Massimiliano Di Penta, Mohammad Hamidi
SCAM1