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ACM REP 2025: ACM Conference on Reproducibility and Replicability

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ACM REP
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투고 마감일:
2025-04-07 Extended
통보일:
2025-06-23
개최일:
2025-07-29
개최지:
Vancouver, British Columbia, Canada
조회: 1418   팔로우: 0   참가: 0

회반 지수 (CP-I)

39.6 / 100
전체 5,680개 중 5,143위 · 상위 91%
학술적 인정 (35%) 데이터 없음 — 중립 기준값 50점으로 계산 —
투고 선별성 (20%) 데이터 없음 — 중립 기준값 50점으로 계산 —
개최 횟수 (20%)
19
커뮤니티 관심도 (10%)
8
공개 자료 충실도 (15%)
50

사용한 입력: 확인되는 개최 횟수: 1 · 지난 24개월 동안 이 페이지를 연 연구자: 2명

공개 자료에서 빠진 항목: 역대 게재율 (+4.5) · 역대 회차 (+3.0)
주최자는 학회를 인증 신청한 뒤 이 페이지에서 바로 추가할 수 있습니다. 점수는 매일 밤 다시 계산됩니다. 이 점수를 올리는 방법

신뢰도 45% — 점수 중 중립 기준값이 아니라 실제 관측된 데이터에 근거한 비율. 이 점수는 어떻게 계산되나 · 전체 순위 보기 · 알고리즘 버전 1.1 · 산출일 2026-09-12

논문 모집

ACM REP 2025 (ACM Conference on Reproducibility and Replicability) is an academic conference held in Vancouver, British Columbia, Canada on 2025-07-29. The paper submission deadline is 2025-04-07 (extended). Acceptance notifications are sent on 2025-06-23.

ACM REP ‘25 welcomes submissions across computing disciplines, spanning both traditional computer science and interdisciplinary scientific computing applications in biology, chemistry, physics, astronomy, genomics, geosciences, etc. The conference particularly values submissions that demonstrate reproducible experimental results. Where full reproduction is not achieved, detailed documentation of the reproducibility experience is equally valuable. The conference addresses various aspects of reproducibility and replicability, including but not limited to the following topics: Reproducibility Concepts Experiment dependency management. Experiment portability for code, performance, and related metrics. Software and artifact packaging and container-related reproducibility methods. Approximate reproducibility. Record and replay methods. Data versioning and preservation. Provenance of data-intensive experiments. Automated experiment execution and validation. Reproducibility-aware computational infrastructure. Experiment discoverability for re-use. Approaches for advancing reproducibility. Reproducibility Experiences Experience of sharing and consuming reproducible artifacts. Conference-scale artifact evaluation experiences and practices. Experiences as part of hackathons and summer programs. Classroom and teaching experiences. Usability and adaptability of reproducibility frameworks into already-established domain-specific tools. Frameworks for sociological constructs to incentivize paradigm shifts. Policies around publication of articles/software. Experiences within computational science communities. Collecting datasets from laboratory / real-world settings. Systems and Security Concerns Experience comparing published systems in a domain. Tools to support replicability of system analysis. Designing machine learning workflows to support reproducibility. Reproducing real-world security findings. Privacy concerns arising from reproducibility. Challenges of reproducing security experiments. Securing reproducibility infrastructure. Broader Reproducibility Cost-benefit analysis frameworks for reproducibility. Novel methods and techniques that impact reproducibility. Reusability, repurposability, and replicability methods. Long-term artifact archiving and verification/testing for future reproducibility.
최종 수정: Dou Sun ()

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