Research output per year
Research output per year
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Dive into the research topics where S. Proksch is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Type4Py: Practical Deep Similarity Learning-Based Type Inference for Python
Mir, A. M., Latoskinas, E., Proksch, S. & Gousios, G., 2022, Proceedings - 2022 ACM/IEEE 44th International Conference on Software Engineering, ICSE 2022. IEEE , p. 2241-2252 12 p. (Proceedings - International Conference on Software Engineering; vol. 2022-May).Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review
Open AccessFile2 Citations (Scopus)11 Downloads (Pure) -
Configuration smells in continuous delivery pipelines: A linter and a six-month study on GitLab
Vassallo, C., Proksch, S., Jancso, A., Gall, H. C. & Di Penta, M., 2020, ESEC/FSE 2020 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering. Devanbu, P., Cohen, M. & Zimmermann, T. (eds.). Association for Computing Machinery (ACM), p. 327-337 11 p. (ESEC/FSE 2020 - Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering).Research output: Chapter in Book/Conference proceedings/Edited volume › Conference contribution › Scientific › peer-review
8 Citations (Scopus) -
How Developers Engage with Static Analysis Tools in Different Contexts
Vassallo, C., Panichella, S., Palomba, F., Proksch, S., Zaidman, A. E. & Gall, HC., 2020, In: Empirical Software Engineering. 25, 2, p. 1419-1457 39 p.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile29 Citations (Scopus)39 Downloads (Pure)