{
  "schema_version": "0.1.0",
  "record_type": "research-topic",
  "topic_id": "trace-abstraction",
  "label": "Trace Abstraction",
  "title": "Trace Abstraction Research",
  "description": "Research papers on abstracting execution traces into compact, semantic, graph, or queryable representations.",
  "introduction": "This topic covers techniques that reduce or reorganize execution-trace detail while preserving information needed for analysis. The records include state histories, semantic events, graph representations, knowledge-graph views, and query-oriented abstractions for navigating or reasoning about large traces.",
  "aliases": [
    "execution trace abstraction",
    "trace summarization",
    "semantic trace representation"
  ],
  "search_terms": [
    "trace abstraction",
    "trace summarization",
    "semantic events",
    "state history",
    "knowledge graph traces"
  ],
  "related_topics": [
    "trace-analysis",
    "trace-reduction",
    "trace-visualization",
    "knowledge-graphs",
    "llm-assisted-analysis"
  ],
  "canonical_url": "https://threadslab.org/research-publications/topics/trace-abstraction.html",
  "paper_count": 9,
  "papers": [
    {
      "paper_id": "integrated-modeling-tool-state-machine-trace",
      "title": "Integrated Modeling Tool for Indexing and Analyzing State Machine Trace",
      "year": 2021,
      "authors": [
        "Simon Delisle",
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/integrated-modeling-tool-state-machine-trace/",
      "canonical_source_url": "https://doi.org/10.1109/ISNCC52172.2021.9615814",
      "core_contribution": "The paper provides a graphical state-machine modeling tool that generates trace analyses and integrates them into Trace Compass, reducing the need to hand-code state providers or XML analyses.",
      "tags": [
        "trace-analysis",
        "trace-visualization",
        "trace-abstraction",
        "performance-analysis"
      ],
      "keywords": [
        "state-machine traces",
        "trace indexing",
        "special-purpose database",
        "Gantt chart",
        "XY view",
        "trace filtering"
      ]
    },
    {
      "paper_id": "enhanced-trace-abstraction-social-network-analysis",
      "title": "Enhanced Execution Trace Abstraction Approach Using Social Network Analysis Methods",
      "year": 2020,
      "authors": [
        "Ji Wang",
        "Naser Ezzati-Jivan"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/enhanced-trace-abstraction-social-network-analysis/",
      "canonical_source_url": "https://fb-swt.gi.de/fileadmin/FB/SWT/Softwaretechnik-Trends/Verzeichnis/Band_40_Heft_3/SSP2020_Wang.pdf",
      "core_contribution": "The paper adapts community detection and PageRank from social-network analysis to reduce and prioritize system execution traces.",
      "tags": [
        "kernel-tracing",
        "trace-abstraction",
        "social-network-analysis",
        "trace-filtering",
        "lttng"
      ],
      "keywords": [
        "LTTng",
        "Trace Compass",
        "Louvain community detection",
        "PageRank",
        "thread interaction graph",
        "trace filtering",
        "virtual-machine clustering"
      ]
    },
    {
      "paper_id": "declarative-framework-stateful-trace-analysis",
      "title": "A declarative framework for stateful analysis of execution traces",
      "year": 2017,
      "authors": [
        "Florian Wininger",
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/declarative-framework-stateful-trace-analysis/",
      "canonical_source_url": "https://doi.org/10.1007/s11219-016-9311-0",
      "core_contribution": "The framework lets analysts define stateful trace analyses declaratively, using a generic state model and XML specifications that can drive storage, filtering, and visualization across trace formats.",
      "tags": [
        "trace-analysis",
        "trace-abstraction",
        "performance-analysis",
        "system-tracing",
        "trace-visualization"
      ],
      "keywords": [
        "declarative trace analysis",
        "stateful analysis",
        "execution traces",
        "LTTng",
        "ETW",
        "State History Tree",
        "XML",
        "trace filtering",
        "Gantt chart",
        "critical-path analysis"
      ]
    },
    {
      "paper_id": "multi-scale-navigation-of-large-trace-data-a-survey",
      "title": "Multi-scale navigation of large trace data: A survey",
      "year": 2017,
      "authors": [
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/multi-scale-navigation-of-large-trace-data-a-survey/",
      "canonical_source_url": "https://doi.org/10.1002/cpe.4068",
      "core_contribution": "The survey provides a taxonomy and requirements-oriented comparison of techniques for collecting, abstracting, analyzing, visualizing, and navigating large execution traces.",
      "tags": [
        "trace-visualization",
        "trace-abstraction",
        "kernel-tracing",
        "performance-analysis",
        "system-tracing"
      ],
      "keywords": [
        "trace navigation",
        "multi-scale analysis",
        "trace visualization",
        "content abstraction",
        "metric abstraction",
        "visual abstraction",
        "resource abstraction",
        "semantic zoom",
        "focus-plus-context",
        "Trace Compass",
        "Vampir",
        "Jumpshot",
        "SLOG",
        "R-tree",
        "quadtree",
        "State History Tree"
      ]
    },
    {
      "paper_id": "a-flexible-data-driven-approach-for-execution-trace-filtering",
      "title": "A Flexible Data-Driven Approach for Execution Trace Filtering",
      "year": 2015,
      "authors": [
        "Kadjo Gwandy Kouame",
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/a-flexible-data-driven-approach-for-execution-trace-filtering/",
      "canonical_source_url": "https://doi.org/10.1109/BigDataCongress.2015.112",
      "core_contribution": "The paper provides a declarative XML/state-machine approach for flexible filtering and synthetic-event generation over large kernel traces.",
      "tags": [
        "kernel-tracing",
        "system-tracing",
        "trace-filtering",
        "trace-abstraction",
        "trace-analysis"
      ],
      "keywords": [
        "execution trace filtering",
        "LTTng 2.4.0",
        "Trace Compass",
        "finite-state machine",
        "declarative analysis",
        "synthetic events",
        "SYN flood",
        "hping3",
        "state system",
        "XML modeling",
        "kernel tracing"
      ]
    },
    {
      "paper_id": "multiscale-navigation-large-trace-data",
      "title": "Multiscale Navigation in Large Trace Data",
      "year": 2014,
      "authors": [
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/multiscale-navigation-large-trace-data/",
      "canonical_source_url": "https://doi.org/10.1109/CCECE.2014.6901019",
      "core_contribution": "The paper presents multiscale trace navigation that links raw kernel events to system-call, synthetic, and fault/alert abstractions in a zoomable timeline.",
      "tags": [
        "trace-visualization",
        "trace-abstraction",
        "trace-analysis",
        "performance-analysis"
      ],
      "keywords": [
        "large trace data",
        "multiscale navigation",
        "zoomable timeline",
        "semantic zoom",
        "physical zoom",
        "trace visualization"
      ]
    },
    {
      "paper_id": "efficient-model-query-visualize-system-states-traces",
      "title": "Efficient Model to Query and Visualize the System States Extracted from Trace Data",
      "year": 2013,
      "authors": [
        "Alexandre Montplaisir",
        "Naser Ezzati-Jivan",
        "Florian Wininger",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/efficient-model-query-visualize-system-states-traces/",
      "canonical_source_url": "https://doi.org/10.1007/978-3-642-40787-1_13",
      "core_contribution": "The paper introduces a disk-backed state-history model that incrementally converts trace events into queryable state intervals, enabling scalable timestamp/state queries and visualization without replaying the entire trace.",
      "tags": [
        "trace-abstraction",
        "trace-visualization",
        "trace-analysis",
        "performance-analysis"
      ],
      "keywords": [
        "system states",
        "trace queries",
        "trace visualization",
        "interval data",
        "tree-based storage",
        "online analysis",
        "offline analysis"
      ]
    },
    {
      "paper_id": "a-stateful-approach-to-generate-synthetic-events-from-kernel-traces",
      "title": "A Stateful Approach to Generate Synthetic Events from Kernel Traces",
      "year": 2012,
      "authors": [
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/a-stateful-approach-to-generate-synthetic-events-from-kernel-traces/",
      "canonical_source_url": "https://doi.org/10.1155/2012/140368",
      "core_contribution": "The paper introduces a stateful trace-abstraction method that converts low-level kernel events into semantic and synthetic events using modeled resource state and finite-state patterns.",
      "tags": [
        "kernel-tracing",
        "system-tracing",
        "trace-abstraction",
        "trace-analysis",
        "performance-analysis"
      ],
      "keywords": [
        "stateful trace abstraction",
        "synthetic events",
        "semantic events",
        "modeled state",
        "finite-state machine",
        "LTTng",
        "Linux kernel 2.6.38.6",
        "XML pattern library",
        "partial trace abstraction",
        "fork bomb",
        "SYN flood",
        "port scanning"
      ]
    },
    {
      "paper_id": "efficient-analysis-multi-core-system-tracing-data",
      "title": "An Efficient Analysis Approach for Multi-Core System Tracing Data",
      "year": 2012,
      "authors": [
        "Naser Ezzati-Jivan",
        "Michel R. Dagenais"
      ],
      "page_url": "https://threadslab.org/research-publications/papers/efficient-analysis-multi-core-system-tracing-data/",
      "canonical_source_url": "https://doi.org/10.2316/P.2012.790-053",
      "core_contribution": "The paper introduces a stateful trace-abstraction architecture that shares modeled system state and intermediate computation across concurrent patterns to reduce the cost of analyzing large Linux kernel traces.",
      "tags": [
        "kernel-tracing",
        "lttng",
        "trace-analysis",
        "trace-abstraction",
        "trace-filtering",
        "performance-analysis",
        "multicore-systems"
      ],
      "keywords": [
        "multi-core tracing",
        "LTTng",
        "Linux kernel 2.6.38.6",
        "stateful trace analysis",
        "trace abstraction",
        "EventMapper",
        "modeled state",
        "semantic events",
        "synthetic event generation",
        "State Machine Language",
        "pattern library",
        "partial trace abstraction",
        "SYN flood",
        "fork bomb",
        "kernel trace",
        "Java trace analyzer",
        "computation sharing",
        "storage efficiency"
      ]
    }
  ]
}