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Heap Evolution Analysis Using Tree Visualizations

dc.contributor.authorWeninger, Markus
dc.contributor.authorMakor, Lukas
dc.contributor.authorMössenböck, Hanspeter
dc.contributor.editorKelter, Udo
dc.date.accessioned2022-11-24T10:42:06Z
dc.date.available2022-11-24T10:42:06Z
dc.date.issued2020
dc.description.abstractMemory 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.en
dc.identifier.pissn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/39794
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 40, Heft 3
dc.relation.ispartofseriesSoftwaretechnik-Trends
dc.subjectAntTracks
dc.subjectheap
dc.subjectmemory
dc.subjecttree
dc.subjectvisualization
dc.titleHeap Evolution Analysis Using Tree Visualizationsen
dc.typeText/Conference Paper
gi.citation.endPage66
gi.citation.publisherPlaceBonn
gi.citation.startPage64
gi.conference.date44147
gi.conference.locationLeipzig
gi.conference.sessiontitleSymposium on Software Performance (SSP)

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