会议信息

ACM REP 2025: ACM Conference on Reproducibility and Replicability

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ACM REP
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截稿日期:
2025-04-07 Extended
通知日期:
2025-06-23
会议日期:
2025-07-29
会议地点:
Vancouver, British Columbia, Canada
浏览: 1421   关注: 0   参加: 0

会伴指数 (CP-I)

39.6 / 100
全站第 5,143 名 / 共 5,680 个会议 · 前 91%
学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
19
社区关注 (10%)
8
资料公开度 (15%)
50

用到的输入: 有据可查的届次：1 · 过去 24 个月打开过本页的研究者：2 人

公开资料里还缺: 历年录用率 (+4.5) · 历届信息 (+3.0)
主办方认领本会议后，可直接在这一页补上；分数每晚重算。如何提升这个分数

置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-09-12

征稿

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.
由 Dou Sun 最后更新于

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