Agent Skillsbrycewang-stanford/Awesome-Journal-Skills › acm-sigplan-conference-on-programming-language-design-and-implementation

acm-sigplan-conference-on-programming-language-design-and-implementation

GitHub

用于评估计算机科学论文是否适合投稿至PLDI会议,提供选题定位、内容重构、证据审查及拒稿风险诊断。

Computer-Science-Conference-Skills/skills/acm-sigplan-conference-on-programming-language-design-and-implementation/SKILL.md brycewang-stanford/Awesome-Journal-Skills

Trigger Scenarios

作者指定PLDI为目标投稿 venue 需对编程语言领域稿件进行会议适配性预评估 需将期刊或arXiv风格稿件重构为CS会议叙事 需要针对该会议的证据缺口、匿名性或反驳策略诊断

Install

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acm-sigplan-conference-on-programming-language-design-and-implementation -g -y
More Options

Non-standard path

npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Computer-Science-Conference-Skills/skills/acm-sigplan-conference-on-programming-language-design-and-implementation -g -y

Use without installing

npx skills use brycewang-stanford/Awesome-Journal-Skills@acm-sigplan-conference-on-programming-language-design-and-implementation

指定 Agent (Claude Code)

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acm-sigplan-conference-on-programming-language-design-and-implementation -a claude-code -g -y

安装 repo 全部 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --all -g -y

预览 repo 内 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --list

SKILL.md

Frontmatter
{
    "name": "acm-sigplan-conference-on-programming-language-design-and-implementation",
    "description": "Use when targeting ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for programming languages flagship."
}

ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)

Conference positioning

ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) is a top computer-science conference venue for programming languages, compilers, program analysis, runtimes, optimization, and language implementation. It rewards a PL paper with formal or implementation insight plus robust evaluation. Treat this skill as a fit / venue-selection / re-framing tool for conference submission strategy, not as a substitute for the current year's CFP, author kit, ethics policy, or submission portal.

Because CS conferences change deadlines, templates, page limits, review workflow, artifact rules, AI-use policy, and rebuttal formats every cycle, always verify the live official instructions before making a submission-ready recommendation. Start from the official source anchor recorded for this venue in ../../resources/conference-roster.md and ../../resources/official-source-map.md.

When to trigger

  • The author names PLDI / ACM SIGPLAN Conference on Programming Language Design and Implementation as the target venue.
  • A manuscript in programming languages needs a conference-fit read before being formatted or submitted.
  • The paper must be re-framed from journal style or arXiv style into a selective CS conference narrative.
  • The author needs an evidence-gap, anonymity, artifact, rebuttal, or re-routing diagnosis for this venue.

Scope & topic fit

  • Core fit: programming languages, compilers, program analysis, runtimes, optimization, and language implementation.
  • Best submissions make a precise contribution type visible: algorithm, theorem, system, dataset, benchmark, empirical finding, design artifact, tool, or socio-technical analysis.
  • The paper should explain why the result matters to PLDI's reviewers, not just why it is interesting to the authors' lab or product context.
  • Position related work against the most recent conference-cycle papers in this venue and its closest siblings; stale comparisons are a common early-review weakness.
  • If the contribution is interdisciplinary, state which part is CS research and which part is domain evidence.

Venue-specific calibration

  • Reviewer lens: Read reviewers as PL specialists. Formal semantics, type systems, compiler/runtime design, or proof structure should be central.
  • Contribution hook to foreground: the venue-specific contribution bar.
  • Scope vocabulary to use naturally in the abstract and introduction: programming languages, compilers, program analysis, runtimes, optimization, and language implementation.
  • Distinctive fingerprint for reviewer calibration: programming, languages, compilers, program, analysis, runtimes, optimization, language, implementation, venue-specific, contribution, flagship, conf, researchr.
  • Official anchor domain: conf.researchr.org. Quote annual rules only after opening that source and the current-year CFP/author kit.

Close-neighbor routing guardrail

  • Use this profile only when the manuscript's central contribution is genuinely in programming languages flagship and the author can say why PLDI reviewers are the primary audience, not merely a convenient deadline.
  • Closest roster neighbors to compare before final routing: european-conference-on-information- retrieval (ECIR), text-retrieval-conference (TREC), acm-sigplan-symposium-on-principles- of-programming-languages (POPL), acm-sigplan-conference-on-object-oriented-programming- systems-languages-and-applications (OOPSLA). Break ties by contribution type, evidence shape, reviewer community, and the current official CFP from conf.researchr.org.

PLDI-specific routing detail

  • Prefer PLDI when the paper's claim lives in a working language, compiler, runtime, optimizer, program-analysis tool, or implementation technique, and the evaluation can show practical payoff beyond toy examples.
  • Use POPL as the closest contrast: POPL centers semantic or type-theoretic principles, while PLDI expects the design insight to survive implementation, benchmarking, usability, or artifact scrutiny.
  • Route to OOPSLA when the work is a broader language/software-engineering experience report, to ASPLOS/CGO/PACT when architecture or performance dominates, and to POPL when proofs rather than implementation evidence carry the main claim.

Method & evidence bar

  • Use task-appropriate baselines, multiple datasets or languages when the claim is broad, and error analysis that explains model behavior.
  • For LLM work, control for data leakage, prompt sensitivity, evaluation contamination, and human-evaluation reliability.
  • For resources, document annotation, licensing, demographics, quality control, and intended use.
  • For PLDI, the evidence must support the venue-specific signature: a PL paper with formal or implementation insight plus robust evaluation.
  • Include limitations, negative results, compute/resource reporting, data provenance, and ethics details when they affect the claim.

Structure & house style

  • State the language phenomenon, task, or system behavior before the model name.
  • Connect examples to measured errors; reviewers dislike anecdotal examples presented as evidence.
  • Use the current official template exactly; do not guess page limits, font sizes, supplement rules, anonymity exceptions, or camera-ready requirements from old cycles.
  • The introduction should answer: problem, why now, what is new, why this venue, and what evidence proves the claim.
  • Put the strongest result in the main paper, not only in the appendix or supplement; reviewers should not have to reconstruct the contribution.

Official-cycle checklist

  • Open the live official venue page: https://conf.researchr.org/series/pldi
  • Re-check the current cycle's CFP, author kit, submission system, abstract/paper deadlines, page limits, supplementary-material rules, anonymity policy, dual-submission policy, ethics policy, AI-use policy, artifact/code/data expectations, rebuttal/author-response format, and camera-ready requirements.
  • Confirm the review workflow and portal: OpenReview / CMT / HotCRP / PCS / START or society portal, as specified for the current cycle.
  • Check whether accepted papers require in-person presentation, separate registration, artifact badges, proceedings copyright, or post-acceptance release forms.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • One sentence states why this manuscript belongs at PLDI, using the venue's scope rather than generic "top conference" language.
  • The claim is calibrated to the evidence: no broader than the datasets, proofs, systems, user studies, deployments, or threat model support.
  • Related work includes the nearest current-cycle programming languages flagship papers and explains the technical delta.
  • The paper satisfies the current official template, anonymity, ethics, artifact, and rebuttal requirements.
  • The main paper is self-contained enough for reviewers to evaluate novelty and correctness without hunting through external links.

Common desk-reject triggers

  • Evaluation that is only a prompt table or cherry-picked generation examples.
  • Missing dataset documentation, licensing, or annotation reliability.
  • Claims of general language understanding from narrow English-only benchmarks.
  • Formatting, anonymity, dual-submission, external-link, or supplement violations under the current-year policy.
  • A contribution framed for a neighboring field while giving PLDI reviewers too little technical or empirical substance.

Re-routing decision

If the paper misses PLDI's bar, compare against annual-meeting-of-the-association-for-computational-linguistics / conference-on-empirical-methods-in-natural-language-processing / north-american-chapter-of-the-association-for-computational-linguistics / european-chapter-of-the-association-for-computational-linguistics. Re-route based on contribution type, not prestige: theory to a theory venue, systems to a systems venue, application-heavy work to a domain venue, and early ideas to workshops or shorter tracks when the official CFP supports them.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI)
[Contribution type] algorithm / theory / system / dataset / benchmark / empirical / design / security / other
[Main evidence gap] <single most important missing proof, experiment, study, artifact, or policy check>
[Official items to re-check] CFP / author kit / deadline / format / anonymity / ethics / AI-use / artifact / rebuttal / camera-ready
[Top rejection risk] <venue-specific risk>
[Re-route suggestion] <better-matched conference or journal if not a fit>

Version History

  • 1839142 Current 2026-07-05 12:41

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