socc-experiments
From the author
Use when designing or auditing ACM SoCC evaluations, covering real or realistic deployments over simulation, production or representative workloads and traces, tail-latency and cost as first-class metrics, fair tuned baselines, scale and multi-tenancy behavior, reproducible measurement pipelines, and matching evidence to the shape of each cloud claim.
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill socc-experiments -a claude-code
Installs to .claude/skills/socc-experiments/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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Why 88
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
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- ipsn-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing IPSN-lineage evaluations, covering real testbeds and deployments, ground-truth instrumentation, energy/latency/footprint measurement on real hardware, on-device/TinyML profiling, estimation-theoretic baselines and bounds, and matching evidence to the shape of each sensing claim across the IP and SPOTS tracks.DevOps★ 1.3K
- sosp-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a SOSP paper — mapping every claim to an experiment, choosing baselines a systems PC will accept as fair, mixing microbenchmarks with end-to-end and failure runs, reporting tails and overheads honestly, and isolating the mechanism the design credits.Design★ 1.3K
- cikm-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the empirical program of a CIKM paper — matching evidence to the claim's lanes across retrieval, mining, and knowledge-management evaluation cultures, choosing datasets and baselines that survive a blended panel, isolating the boundary mechanism, and meeting applied-track deployment-evidence bars.DevOps★ 1.3K
- nsdi-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an NSDI submission — choosing traces, testbeds, and deployment evidence, sizing scale and failure-injection experiments, picking baselines that fight back, and reporting tail behavior so networked-systems reviewers can see where the design wins, loses, and breaks.DevOps★ 1.3K
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