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issta-artifact-evaluation

Use when packaging an ISSTA tool, benchmark, and results for the artifact-evaluation track, covering the ACM badges (Artifacts Available via Zenodo,…

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技能内容

ISSTA Artifact Evaluation

Use this to package evidence for ISSTA's artifact-evaluation track. ISSTA has a genuinely strong

artifact culture: a runnable tool and a shared benchmark are treated as normal, and the badges

carry weight. Reopen the current artifact call before packaging — the badge set and the archival

requirement are cycle-specific.

The ACM badge targets

| Badge | What it certifies | What you must ship |

|---|---|---|

| Artifacts Available | The artifact is publicly, permanently retrievable | A DOI-issuing deposit (Zenodo) — a GitHub link alone does not qualify |

| Artifacts Evaluated — Functional | The artifact runs and does what the paper says | A working entry point, dependencies, and a documented expected output |

| Artifacts Evaluated — Reusable | Others can inspect, adapt, and build on it | Clean structure, real documentation, and configurability beyond the paper's runs |

| Results Reproduced | The paper's key results regenerate from the artifact | Scripts that produce the paper's tables/figures within stated tolerance |

Available is about archival; Functional and Reusable are about engineering quality; Results

Reproduced is about matching the paper. They are earned independently — decide which you are

going for before you package.

Artifact plan

  • Decide the badge set, then package to its bar. A Reusable badge needs documentation and structure

a Functional-only artifact can skip.

  • Ship the tool with a single documented entry point and a container or environment file, so an

evaluator reaches a result without reconstructing your machine.

  • Pin subjects and benchmark versions: the exact Defects4J revision, subject-program commit SHAs,

and any fuzzing seed corpora, archived rather than referenced by name.

  • Provide a results-regeneration path: a script that takes logged runs to the paper's tables, so

"Results Reproduced" is a command, not an argument.

  • Anonymize the review-time copy — repository owners, commit authors, container labels — because

ISSTA artifact review is double-anonymous alongside the paper.

  • After acceptance, make the Zenodo deposit public and citable, and record its DOI for the

camera-ready badge display.

What ISSTA evaluators try first

  • The README's quick-start, then the single command that produces one headline number. If that

fails on a clean machine, no amount of internal quality is visible.

  • A small, fast subset that finishes in minutes, before any full multi-day fuzzing or

symbolic-execution campaign. Ship a "smoke" configuration explicitly.

  • The mapping from a paper claim to the artifact output that supports it; an artifact whose outputs

cannot be tied back to Table N reads as unverifiable.

Handling long-running and non-deterministic tools

Testing and analysis artifacts often run for hours and vary between runs. Package for that reality:

artifact/
  README.md            # quick-start, smoke config, full config, expected outputs, runtime
  Dockerfile           # pinned toolchain and dependencies
  subjects/            # pinned subject SHAs or a fetch script that pins them
  run_smoke.sh         # minutes: reproduces one representative row
  run_full.sh          # hours/days: reproduces all tables
  results/             # logged raw outputs from the authors' runs
  scripts/tables.py    # regenerates paper tables from results/

State the run count and expected variance for non-deterministic results, and have the

regeneration script accept the evaluator's fresh runs as well as the shipped logs, so a partial

reproduction still lands on the paper's numbers within tolerance.

Calibration anchors

  • Evaluators are time-boxed; assume they run the smoke config and skim the full one. Design so the

smoke path alone justifies Functional.

  • Badge names, the Zenodo requirement, and any single-blind vs. double-blind detail vary by cycle;

verify against the current artifact call rather than a past year.

Output format

[Badge target] Available / Functional / Reusable / Results Reproduced
[Entry point] <command + smoke runtime>
[Pinned subjects] <benchmark version / SHAs archived?>
[Reproduction level] turnkey / scripted / descriptive / weak
[Anonymity risks] <owners/authors/labels/paths>
[Fixes before upload] <ordered list>

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