icse-experiments
From the author
Use when designing or auditing the evaluation of an ICSE research-track paper, covering subject and benchmark selection, baseline fairness, statistical tests and effect sizes as SE reviewers expect them, qualitative-methods rigor, ablations for AI-based techniques, and threats-driven study design.
Install
npx skills add brycewang-stanford/Awesome-Journal-Skills --skill icse-experiments -a claude-code
Installs to .claude/skills/icse-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.
Want your agent to suggest skills while you type? See how to use skills from your IDE.
Safety checks on SKILL.md
No warnings.
Why 88
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
Similar skills
Closest to this one by what they do and when they are used.
- ase-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an ASE (IEEE/ACM Automated Software Engineering) paper, covering real subject systems, fair runnable tool baselines, task-matched effectiveness metrics, ablations that isolate a learned component, oracle and correctness validation, contamination-aware LLM handling, and provenance for mining.Science★ 1.3K
- fse-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing ESEC/FSE empirical evaluations, covering real subject systems, fair baselines, SE-standard statistics and effect sizes, qualitative and mixed-methods rigor, contamination-aware LLM ablations, provenance for mining studies, and matching evidence to the shape of each software-engineering claim.Other★ 1.3K
- icdm-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the empirical evaluation for an ICDM (IEEE International Conference on Data Mining) paper - mining-task definition, strong and fairly-tuned baselines, ablations that isolate the named mechanism, scalability curves that test scale claims, and discovery-validity checks that separate real findings from evaluation artifacts.Testing★ 1.3K
- uist-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of a UIST paper — choosing among technical benchmarks, controlled comparisons, usability walkthroughs, expert sessions, and demonstration applications, matching evaluation shape to the systems claim, and avoiding the ritual study that proves nothing the paper asserts.Science★ 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
- isca-experimentsbrycewang-stanford/Awesome-Journal-SkillsUse when designing or auditing the evaluation of an ISCA paper — pinning simulator fidelity to the claims it must carry, documenting gem5-class configurations and sampling choices, selecting workload suites that represent the claim's domain, tuning baselines in good faith, and separating architectural effect from modeling artifact.Science★ 1.3K
Ratings & reviews
—
no reviews
Tried this skill? Rate it to help others. Sign in
Discussion
Join the discussion. Sign in