EdgeBench / integer_compression_codec.json
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{
"task_id": "integer_compression_codec",
"name": "Integer Compression Codec",
"category": "Systems & Software Engineering",
"base_image": "cpp",
"platform": "linux/amd64",
"internet": false,
"cwd": "/home/workspace/integer-compression-codec",
"submit_paths": [
"include/",
"src/",
"Makefile"
],
"submit_exclude": [
"**/__pycache__/",
"outputs/",
"data/",
".judge-bin/"
],
"work": {
"image_tag": "fa3895856662",
"specs_dir": "/home/workspace/integer-compression-codec",
"agent_query": "## Role\\n\\nYou are an expert systems and performance engineer improving a uint32 integer compression codec.\\n\\n## Task\\n\\nImplement a stronger `libintcompress.so` by editing the C++ code in `src/` while preserving the ABI in `include/intcompress.h`. Your goal is to improve both compression ratio and decode throughput on the provided datasets.\\n\\n## Files\\n\\n- `problem.md`: task description and constraints\\n- `task_input.md`: input / output contract\\n- `scoring_scheme.md`: public scoring rules\\n- `soft_environment.md`: environment description\\n- `include/intcompress.h`: fixed ABI\\n- `src/codec.cpp`: baseline implementation\\n- `tools/verify.cpp`: local correctness check\\n- `tools/bench.cpp`: local benchmarking tool\\n\\n## Working Strategy\\n\\n1. Read the docs first.\\n2. Keep `include/intcompress.h` unchanged.\\n3. Improve `src/` with better block encoding, delta transforms, bit-packing, SIMD, or adaptive strategies.\\n4. Use `make`, `./tools/verify`, and `./tools/bench --all ./libintcompress.so` for local iteration.\\n5. Submit intermediate versions frequently.\\n\\n## Rules\\n\\n- Do not use network access, subprocess tricks, or external services.\\n- Do not depend on third-party compression libraries.\\n- Keep the exported `ic_*` symbols intact.\\n- Correctness matters: `decode(encode(X))` must exactly recover `X`."
},
"judge": {
"image_tag": "27063396e02a",
"eval_cmd": "cd /home/workspace/integer-compression-codec && python3 runner_judge.py",
"eval_timeout": 2400,
"parser": "structured_json",
"score_direction": "maximize",
"selection": "score_first",
"rescale": {
"kind": "linear",
"lower": 0.0,
"upper": 100.0
}
}
}