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  "paper_id": "multi-scale-navigation-of-large-trace-data-a-survey",
  "page_url": "https://naser.github.io/research-publications/papers/multi-scale-navigation-of-large-trace-data-a-survey/",
  "title": "Multi-scale Navigation of Large Trace Data: A Survey",
  "title_variants": [],
  "authors": [
    "Naser Ezzati-Jivan",
    "Michel R. Dagenais"
  ],
  "author_details": [
    {
      "name": "Naser Ezzati-Jivan",
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    }
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  "publication": {
    "year": 2017,
    "venue": "Concurrency and Computation: Practice and Experience",
    "type": "survey article",
    "publication_date": "2017-03-21",
    "online_date": "2017-03-21",
    "print_date": "2017-05-25",
    "volume": "29",
    "issue": "10",
    "pages": null,
    "article_number": "e4068",
    "publisher": "Wiley",
    "issn": [
      "1532-0626",
      "1532-0634"
    ],
    "isbn": [],
    "crossref_type": "journal-article"
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  "identifiers": {
    "doi": "10.1002/cpe.4068"
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  "abstract": "The survey organizes abstraction and visualization techniques that help analysts navigate long operating-system and kernel traces from overview to event-level evidence.",
  "abstract_source": "Institutional accepted-version PDF reviewed; abstract paraphrased for this catalog.",
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  "description": "The survey organizes abstraction and visualization techniques that help analysts navigate long operating-system and kernel traces from overview to event-level evidence.",
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        "note": "Survey PDF: four abstraction families, multi-level views, semantic/physical zoom, focus-plus-context, and trace-data structures"
      },
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        "note": "Survey PDF: Trace Compass/LTTV, Vampir, Jumpshot, TuningFork, HPCToolkit, VTune, and metric examples"
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        "note": "Survey PDF: complementary-techniques conclusion and bidirectional-link future direction"
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  "summary": {
    "core_contribution": "The survey provides a taxonomy and requirements-oriented comparison of techniques for collecting, abstracting, analyzing, visualizing, and navigating large execution traces.",
    "problem": "Long-running and parallel executions produce traces too large for a single-resolution display; analysts need overview, semantic navigation, and evidence-preserving drill-down.",
    "method": "Survey trace collection, maintenance, analysis, and visualization through four abstraction families and compare hierarchical, semantic, visual, and resource-oriented navigation mechanisms and data structures.",
    "findings": "The literature offers complementary techniques rather than one universally dominant abstraction. Linking overview levels to concrete events, states, resources, and metrics is central to usable large-trace analysis.",
    "limitations": "This paper synthesizes prior work and does not validate a new method, dataset, or benchmark. Its coverage and taxonomy are bounded by the selected literature and the paper's OS/kernel-oriented scope.",
    "future_work": "Improve bidirectional links between abstraction levels, support issue-to-event drill-down, and advance trace models, data structures, and interactive visualization."
  },
  "tags": [
    "trace-visualization",
    "trace-abstraction",
    "kernel-tracing",
    "performance-analysis",
    "system-tracing"
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    "trace navigation",
    "multi-scale analysis",
    "trace visualization",
    "content abstraction",
    "metric abstraction",
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    "resource abstraction",
    "semantic zoom",
    "focus-plus-context",
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    "State History Tree"
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    "license": null
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  "resources": {
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  "citation_guidance": {
    "when_to_cite": "Cite this paper when your work uses or compares the four-part taxonomy of content/data, metric, visual, and resource abstraction in large-trace navigation.",
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