AntTracks TrendViz: Configurable Heap Memory Visualization Over Time

Research output: Chapter in Book/Report/Conference proceedingConference proceedingspeer-review

Abstract

The complexity of modern applications makes it hard to fix memory leaks and other heap-related problems without tool support. Yet, most state-of-the-art tools share problems that still need to be tackled: (1) They group heap objects only based on their types, ignoring other properties such as allocation sites or data structure compositions. (2) Analyses strongly focus on a single point in time and do not show heap evolution over time. (3) Results are displayed in tables, even though more advanced visualization techniques may ease and improve the analysis. In this paper, we present a novel visualization approach that addresses these shortcomings. Heap objects can be arbitrarily classified, enabling users to group objects based on their needs. Instead of inspecting the size of those object groups at a single point in time, our approach tracks the growth of each object group over time. This growth is then visualized using time-series charts, making it easy to identify suspicious object groups. A drill-down feature enables users to investigate these object groups in more detail. Our approach has been integrated into AntTracks, a trace-based memory monitoring tool, to demonstrate its feasibility.
Original languageEnglish
Title of host publicationProceedings of the 10th ACM/SPEC International Conference on Performance Engineering
PublisherACM
Pages29-32
Number of pages4
ISBN (Electronic)9781450362863
DOIs
Publication statusPublished - Mar 2019

Fields of science

  • 102 Computer Sciences
  • 102022 Software development
  • 102025 Distributed systems

JKU Focus areas

  • Digital Transformation

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