技能创建器
skill-creator
创建、改进和评估自定义技能,把专业流程转化为可重复使用的 AI 能力。
icdt-experiments【数据与研究】Use when deciding what counts as evidence for an ICDT (International Conference on Database Theory) result — matching-bound complexity analysis as the primary evidence, worked examples and counterexamples that establish separations, and, only for papers with an algorithmic contribution, a proportional and honestly-scoped experimental evaluation that …
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
At ICDT the primary "evidence" is a proof, not a benchmark. This skill is about matching your form of evidence to your claim: most ICDT papers are purely theoretical and need no experiments at all, while a minority with a genuine algorithmic contribution benefit from a small, honest evaluation. Bolting a systems-style experiment section onto a theorem paper does not raise its standing — a loose bound or an unproved lemma will still sink it.
| Claim shape | Primary evidence | Experiments? |
|---|---|---|
| Complexity of evaluating a query class | Matching upper and lower bounds, with proofs | No — the bound is the result |
| Expressiveness / separation | A construction or an Ehrenfeucht-Fraisse game establishing the separation | No — a witness, not a benchmark |
| Decidability / undecidability of a problem | An algorithm + termination proof, or a reduction from an undecidable problem | No |
| A new algorithm with a claimed practical complexity | The complexity proof plus an optional experiment showing the constants are reasonable | Optional, proportional |
| A dichotomy | Proof that each side holds and the boundary is exactly as stated | No |
The default answer is "the theorem is the evidence." Reach for experiments only when your paper claims something about practice that the asymptotic bound alone does not settle.
Some ICDT papers contribute an algorithm whose worst-case bound understates or overstates its behavior on realistic inputs. If you evaluate it, do so with the rigor the theory earns:
[Purpose] state exactly what the experiment tests that the proof does not (e.g., typical-case
runtime, the size of the hidden constant, scaling on real query workloads)
[Subjects] real or standard benchmark data/queries, described precisely; no cherry-picked inputs
[Baseline] a fair comparison (a prior algorithm, a naive method) implemented honestly
[Reporting] enough runs, hardware stated, and results that support only what you claim
[Scope] the experiment supplements the theorem; it never substitutes for a missing proof
Keep it proportional: an ICDT experiment is a paragraph-to-a-page confirmation, not a systems-paper
evaluation. If the experiment is the contribution, the paper likely belongs at EDBT/SIGMOD, not
ICDT (see icdt-topic-selection).
[Claim -> evidence] <each claim -> proof (bounds/construction) or experiment>
[Tightness] bounds matched and labeled? yes/no/na
[Complexity measure] data / combined / query, proven in the claimed measure? yes/no
[Experiment] none (theory-complete) / proportional supplement / over-scoped (reroute?)
[Fix queue] <ordered: close bound gaps first, then examples, then any experiment>