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  "paper_id": "identification-and-classification-of-jmh-microbenchmark-states-using-time-series-analysis",
  "page_url": "https://naser.github.io/research-publications/papers/identification-and-classification-of-jmh-microbenchmark-states-using-time-series-analysis/",
  "title": "Identification and Classification of JMH Microbenchmark States using Time Series Analysis",
  "title_variants": [],
  "authors": [
    "Tom Wallace",
    "Beatrice M. Ombuki-Berman",
    "Naser Ezzati-Jivan"
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    "year": 2023,
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    "publication_date": "2023-04-15",
    "online_date": "2023-04-15",
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    "issue": null,
    "pages": "101-105",
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  "identifiers": {
    "doi": "10.1145/3578245.3584694"
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  "abstract": null,
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  "description": "The paper uses time-series analysis to identify and classify warmup, steady-state, and anomalous states in Java JMH microbenchmarks.",
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  "summary": {
    "core_contribution": "The paper uses time-series analysis to identify and classify warmup, steady-state, and anomalous states in Java JMH microbenchmarks.",
    "problem": "JMH measurements can contain warmup, steady-state, and anomalous phases; default/manual warmup choices do not reliably identify when stable behavior begins (pp. 1-2).",
    "method": "Matrix Profile motif/discord analysis is applied to JMH time series with Python Stumpy and compared with PELT change-point detection using Python Ruptures. RQ1 compares Matrix Profile minimum/maximum/mean for 497 steady-state and 235 non-steady-state forks using an unequal-variance two-sample t-test. RQ2 uses mean/standard-deviation anomaly heuristics and treats the first 30 iterations as warmup. RQ3 scores change points falling inside motif/discord windows (pp. 2-4).",
    "findings": "RQ1 reports statistically significant differences (p < .05): steady-state benchmarks have lower Matrix Profile minimum, maximum, and mean. Matrix Profile identifies isolated spikes but can miss anomalies dominating most of a series. In the RQ3 table, 305 steady-state cases are split into 123 none/123 potential/59 noticeable correlations; 185 non-steady cases are split into 44/93/48 (pp. 3-4).",
    "limitations": "RQ2 is explicitly qualitative; the paper warns of Matrix Profile blind spots and possible errors/inconsistencies in the Python translation of the reference steady-state detector. JVM version, hardware, and OS details for the benchmark corpus: unknown.",
    "future_work": "Compare window sizes, classification functions, and larger numbers of motifs/discords; compare with industry-standard approaches (pp. 3-4)."
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  "tags": [
    "performance-analysis",
    "performance-engineering",
    "anomaly-detection",
    "machine-learning"
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    "Java Microbenchmark Harness",
    "JMH",
    "benchmark states",
    "steady state",
    "warmup",
    "Matrix Profile",
    "motifs",
    "discords",
    "PELT",
    "change points",
    "Stumpy",
    "Ruptures",
    "time-series analysis"
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    "license": null
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  "resources": {
    "code": "https://github.com/Tom-Wallace/patternReader",
    "data": null,
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    "when_to_cite": "Cite this paper when your work uses or compares matrix Profile motifs/discords as a time-series method for identifying JMH steady-state structure and isolated anomalies.",
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