Companion Data for ScratchLog+: Live Analytics of Learners' Exercise Progress

This repository contains the companion data for the tool demonstration paper ‘ScratchLog+: Live Analytics of Learners' Exercise Progress’ published at the Tools and Datasets track of the International Conference Automated Software Engineering (ASE) 2026. (doi:10.1145/3832783.3834618) The code of ScratchLog+ can be found at https://github.com/se2p/ScratchLog. Our extensions to Whisker are part of https://github.com/se2p/Whisker. Using the provided data Mount the downloaded SQL file to the database container by configuring it in the docker-compose.yaml file of the ScratchLog repository: services: # … database: # … volumes: - ase2026_scratchlog-plus_demo.sql:/docker-entrypoint-initdb.d/init.sql - scratchlog-db:/var/lib/mysql # … After starting ScratchLog, you can then log in to http://localhost:8090/ with username admin and password ASE2026tool. If you want to use the GGNN model to compute the embeddings, you can download the model checkpoint and unpack the archive into embedding-connector/data/ after checking out the ScratchLog repository and pointing the embedding connector to the GGNN config via the environment variable GGNN_MODEL_CONFIG=./data/model-config.yaml.