# Dataset: Elastic Hashing Performance Under Varying Hyperparameters ## Overview This dataset contains measurements from a benchmark of **Elastic Hashing**. The benchmark investigates the performance impact of Elastic Hashing's hyperparameters using CPU execution time. Unlike the general hash-table performance benchmark, this dataset focuses exclusively on Elastic Hashing while keeping the table capacity and load factor fixed. ## Experimental Design Only the **Elastic Hashing** scheme is evaluated. The following parameters are fixed for all benchmark configurations: * **Capacity:** $2^{16}$ * **Load factor:** $\alpha = 0.75$ The following Elastic Hashing hyperparameters are varied: * **$\delta$:** $\frac{1}{2^i}$ for $i \in {1,2,3,4}$, corresponding to $\frac{1}{2}$, $\frac{1}{4}$, $\frac{1}{8}$, and $\frac{1}{16}$ * **$c$:** values from $1$ through $100$ For each combination of $\delta$ and $c$, insert with missing keys was evaluated: ## Measurements The benchmark records **CPU execution time** for each benchmark configuration. The individual measurements are stored directly in the JSON dataset rather than being reduced to summary statistics. ## Repetitions Each configuration was evaluated using **two independent trials**. Each trial consists of: * one initialized hash table, * 100 repetitions, * 10,000 benchmark iterations per repetition. For each repetition, a random list of keys is generated. The random seed used to generate the key list identifies the repetition and associates the key sequence with its corresponding randomized trial. The same hash-table instance is used throughout the repetitions of a trial. This preserves the configured table state while allowing the benchmark to evaluate different randomized key sequences. ## Data Organization The dataset consists of a single JSON file containing the benchmark measurements and associated metadata. The metadata identifies the Elastic Hashing configuration, including $\delta$ and $c$, as well as the benchmark operation, key type, capacity, and load factor. The JSON file contains the corresponding CPU-time measurements. ## Purpose The dataset is intended to investigate the influence of Elastic Hashing's hyperparameters on its performance while keeping the table capacity and load factor constant. In particular, it can be used to: * analyze the effect of $\delta$ on CPU execution time, * analyze the effect of $c$ on CPU execution time, * investigate interactions between $\delta$ and $c$, * compare the performance of different Elastic Hashing configurations, and * reproduce the corresponding analysis presented in the associated bachelor's thesis. ## Reproducibility The dataset contains the measurements collected during the benchmark runs and is intended to support the analysis presented in the associated bachelor's thesis. The benchmark configuration and execution metadata are included with the dataset to provide additional information about the environment in which the measurements were collected. The execution environment itself is not considered part of the experimental factors; the primary factors of interest are the Elastic Hashing hyperparameters $\delta$ and $c$. The dataset contains the individual benchmark measurements rather than only aggregated statistics, allowing alternative analyses and aggregations to be performed. ## License This dataset is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license. See the accompanying `LICENSE` file for the license terms.