This archive contains supplementary material, the code, and all experimental data of the ICAPS 2023 paper titled "Efficient Evaluation of Large Abstractions for Decoupled Search: Merge-and-Shrink and Symbolic Pattern Databases". The supplementary material contains full proofs for some of the formal claims made in the original paper (gnad-et-al-zenodo2023.pdf). The results are based on two versions of the code base of a decoupled-search variant of the Fast Downward planning system. The archive decoupled-fast-downward-mas.tar.xz contains the code of the decoupled Merge-And-Shrink experiments, the archive decoupled-fast-downward-spdb.tar.xz the one of the symbolic PDB experiments. The evaluation has been performed using downward-lab, which is available in lab.tar.xz. All log files and the parsed results are available in the files listed below. Once uncompressed, they can be used in downward-lab to reproduce the results tables from the paper. This can be done using the Python script experiments/decoupled-abstractions/paper-tables-icaps23-crc-autoscale.py from the Merge-And-Shrink code archive, by extracting the following files into a data folder that sits in the same folder as the script. 2022-11-24-gamer-pdbs-all.tar.xz 2023-02-22-icaps23-crc-ms.tar.xz 2023-03-06-linear-random-compliant-merge.tar.xz