Instrumenting Python with Kieker
| dc.contributor.author | Simonov, Serafim | |
| dc.contributor.author | Düllmann, Thomas F. | |
| dc.contributor.author | Jung, Reiner | |
| dc.contributor.author | Gundlach, Sven | |
| dc.contributor.editor | Herrmann, Andrea | |
| dc.date.accessioned | 2024-02-22T10:37:52Z | |
| dc.date.available | 2024-02-22T10:37:52Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | Python has become a widely used programming language in big data, machine learning, and scientific modeling. In all these domains, performance is a key factor to success and requires the ability to understand the runtime behavior of software. Therefore, we ported Kieker monitoring to Python and evaluated different approaches to introduce probes into code. In this paper, we evaluate these approaches, show their benefits and limitations and provide a perfor mance evaluation of the Kieker 4 Python framework. | en |
| dc.identifier.issn | 0720-8928 | |
| dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/43639 | |
| dc.language.iso | en | |
| dc.pubPlace | Bonn | |
| dc.publisher | Gesellschaft für Informatik e.V. | |
| dc.relation.ispartof | Softwaretechnik-Trends Band 43, Heft 1 | |
| dc.relation.ispartofseries | Softwaretechnik-Trends | |
| dc.subject | Python | |
| dc.subject | performance | |
| dc.subject | Kieker | |
| dc.subject | monitoring | |
| dc.title | Instrumenting Python with Kieker | en |
| dc.type | Text/Conference Paper | |
| mci.conference.date | 7.-9.11.2022 | |
| mci.conference.location | Stuttgart | |
| mci.conference.sessiontitle | 13th Symposium on Software Performance (SSP) | |
| mci.reference.pages | 26-28 |
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