Heap Evolution Analysis Using Tree Visualizations
Zusammenfassung
Memory anomalies such as memory leaks can dramatically impact application performance and can even lead to crashes. Thus, supporting developers in understanding the heap memory behavior of their systems is
essential. Unfortunately, most memory analysis tools lack advanced visualizations that could facilitate developers in analyzing suspicious memory behavior. To analyze heap memory, it is common to group the heap’s objects, for example, by their types or by their allocation sites. Using multiple grouping criteria thus results in a tree-shaped representation of the heap content. Such a heap tree is then typically presented textually in a tree table. In this paper, we present ongoing research on using well-known tree visualization techniques to visualize such heap trees as well as their evolution over time. Such visualizations may ease the detection of proliferating heap objects, facilitating memory leak analysis. To demonstrate the feasibility and applicability of the presented approach, we implemented a web-based visualization tool and integrated it into AntTracks, our trace-based memory monitoring tool.
- Vollständige Referenz
- BibTeX
Weninger, M., Makor, L. & Mössenböck, H.,
(2020).
Heap Evolution Analysis Using Tree Visualizations.
In:
Kelter, U.
(Hrsg.),
Softwaretechnik-Trends Band 40, Heft 3.
Bonn:
Gesellschaft für Informatik e.V..
(S. 64-66).
@inproceedings{mci/Weninger2020,
author = {Weninger, Markus AND Makor, Lukas AND Mössenböck, Hanspeter},
title = {Heap Evolution Analysis Using Tree Visualizations},
booktitle = {Softwaretechnik-Trends Band 40, Heft 3},
year = {2020},
editor = {Kelter, Udo} ,
pages = { 64-66 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
author = {Weninger, Markus AND Makor, Lukas AND Mössenböck, Hanspeter},
title = {Heap Evolution Analysis Using Tree Visualizations},
booktitle = {Softwaretechnik-Trends Band 40, Heft 3},
year = {2020},
editor = {Kelter, Udo} ,
pages = { 64-66 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
| Dateien | Groesse | Format | Anzeige | |
|---|---|---|---|---|
| SSP2020_Weninger_Makor.pdf | 513.6Kb | Öffnen |
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Mehr Information
ISSN: 0720-8928
Datum: 2020
Sprache:
(en)
(en)
Typ: Text/Conference Paper

