Skip to content
Content
Skill

/ase-review-process

Use when reasoning about how an ASE (IEEE/ACM Automated Software Engineering) research submission is evaluated, covering double-anonymous review, the early-rejection stage before rebuttal, the Accept / Revision / Reject outcomes, the criteria-bound revision round, and how ASE's

From plugin
awesome-journal-skills
965200 skills
Install
$ npx -y skills add brycewang-stanford/Awesome-Journal-Skills --skill ase-review-process --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/ase-review-process

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use when reasoning about how an ASE (IEEE/ACM Automated Software Engineering) research submission is evaluated, covering double-anonymous review, the early-rejection stage before rebuttal, the Accept / Revision / Reject outcomes, the criteria-bound revision round, and how ASE's

SKILL.md

ase-review-process.SKILL.md
name: ase-review-process
description: Use when reasoning about how an ASE (IEEE/ACM Automated Software Engineering) research submission is evaluated, covering double-anonymous review, the early-rejection stage before rebuttal, the Accept / Revision / Reject outcomes, the criteria-bound revision round, and how ASE's process differs from FSE's PACMSE Major Revision, ICSE's cycles, and ISSTA's rounds.

ASE Review Process

Model the pipeline before interpreting any single review. ASE's process has **two distinctive gates** that authors from a plain accept/reject conference miss: an **early-rejection stage** that ends the process *before* rebuttal for the weakest papers, and a first-class **Revision** outcome whose criteria are fixed in advance. Getting both wrong wastes the little leverage authors have.

Process model

  • Submission and review run on **HotCRP** with **double-anonymous** review: identities are hidden

from reviewers, and authors reference their own prior work in the third person.

  • Each paper receives multiple reviews scoring the **significance and soundness of the automation**,

the quality of the evaluation on real subjects, threats to validity, clarity, and the Data Availability / artifact posture.

  • **Early-rejection stage:** papers whose initial scores are **uniformly negative are rejected

before the rebuttal period**. This is a mercy and a filter — it gives those authors a fast answer and concentrates rebuttal effort where it can change an outcome. If your paper survives to rebuttal, at least one reviewer saw something.

  • **Rebuttal**, then a final outcome of **Accept**, **Revision**, or **Reject**.
  • **Revision** is criteria-bound: instead of rejecting, reviewers specify **concrete, actionable

revision criteria** and agree to **accept the paper in principle if those criteria are met**. Authors return a revised paper with a **point-by-point summary of changes**, re-checked (often by a discussion lead) against the stated criteria.

  • Accepted papers appear in the proceedings in **both IEEE Xplore and the ACM Digital Library**;

camera-ready compliance and artifact follow-through matter after the verdict.

Reading a decision against the categories

| Decision | What it means | Author move | |---|---|---| | Accept | The automation and its evaluation hold; minor polish only | Camera-ready + artifact; do not reopen scope | | Revision | Repairable gaps captured as explicit criteria: a missing baseline, an ablation, a clarified construct | Meet **every** stated criterion, or justify why one is infeasible; map each to a change in the summary-of-changes | | Reject | Structural: the automation is unsound, the evaluation is not on real subjects, the delta is thin | Reframe or reroute (ICSE/FSE/ISSTA or a journal); do not lightly resubmit unchanged | | Early reject (pre-rebuttal) | Uniformly negative initial scores | No rebuttal opportunity; diagnose honestly and rebuild before any resubmission |

The strategic reading: write the initial submission so its weakest point is **expressible as a revision criterion** (an ablation you can add, a subject set you can extend) rather than **structural** (a tool you would have to redesign). The Revision outcome rewards papers that are one bounded step from done.

How ASE differs from its siblings

  • **vs. ESEC/FSE:** FSE papers are **PACMSE journal articles** with a Major Revision round and heavy

double-anonymity into the response letter. ASE is a **conference** (dual IEEE/ACM, proceedings in IEEE Xplore *and* ACM DL) whose Revision is criteria-bound but lighter-weight, and whose center of gravity is *automation* rather than broad empirical SE. Do not assume shared calendars, templates, or that ASE's Revision equals PACMSE's Major Revision.

  • **vs. ICSE:** ICSE runs its own multi-cycle structure on the IEEE side; ASE's early-rejection +

Revision model is its own. Never carry ICSE's cadence or page box across.

  • **vs. ISSTA:** ISSTA has used multi-round reviewing for *every* paper within a cycle; ASE's

Revision is **decision-driven** (you revise because you were told to, against fixed criteria), not a scheduled second read of the whole pool.

Who reads you

Expect automated-SE specialists: people who build analyzers, test generators, synthesizers, repair tools, and code models. They check whether the automation is **sound and general**, whether the evaluation uses **real subject systems** and **fair tool baselines**, whether claims outrun evidence, and they frequently open the artifact. A tool described vaguely gets caught, not skimmed.

Where author leverage actually exists

[Before submission]  area/topic tags -> reviewer pool               (largest lever)
[Initial reviews]    factual corrections, targeted evidence, clarifying a misread tool/experiment
[Rebuttal]           survive early rejection first; then move the borderline reviewer with numbers
[Revision]           the strongest lever: meet each fixed criterion, mapped in the summary-of-changes
[After reject]       no appeal; reroute to a sibling flagship or a journal

A rebuttal moves borderline papers when it corrects a factual misreading or supplies a number a reviewer said was missing; it does not move papers when it argues taste. In a Revision, a criterion that is **neither met nor explicitly addressed** is what turns the re-check into a rejection.

Misreadings to avoid

  • **Treating Revision as a guaranteed accept** — the re-check against the criteria is real.
  • **Ignoring a stated criterion** — silent omission of even one is the classic Revision failure.
  • **Treating the rebuttal as a debate** — the PC discussion decides; your text is evidence for an

advocate, not a closing argument.

  • **Forgetting the early-rejection gate** — a uniformly weak first impression ends the process with

no rebuttal; the first three pages and the evaluation table must land immediately.

  • **Projecting last year's cadence** — deadlin
Read more
Ships withawesome-journal-skills

Stanford REAP × CoPaper.AI · 由斯坦福实证方法论团队精选与维护 访问 copaper.ai 微信:CoPaper.AI 按 11 个主流学科板块覆盖 经管与商科 社会科学 人文学科 数学与物理科学 生命科学 医学与健康 工程与技术 计算机科学与 AI 体育科学 点击任一学科名可跳转到对应说明;每类下的代表子领域在正文总览中完整列出。下方封面墙按 venue 导航,完整分类见覆盖一览。 🧭 布局指南 · 📚 Skill Pack 一览 · ⚡ 如何使用 · 🧪 自动实证

Get the whole plugin
Stats
965
Stars
121
Forks
Active
Maintenance
Stata
Language
MIT
License
13h ago
Last commit
2mo ago
Created

Repo: brycewang-stanford/Awesome-Journal-Skills

Other skills on awesome-journal-skills.