--- language: - zh - en license: apache-2.0 task_categories: - text-generation - question-answering tags: - benchmark - code - sap - abap - s4hana - enterprise-software - llm-evaluation pretty_name: ABAP-Bench size_categories: - n<1K --- # ABAP-Bench A comprehensive benchmark for evaluating Large Language Model understanding of SAP ABAP programming, S/4HANA modernization, and enterprise software engineering. ## Overview | Property | Value | |----------|-------| | Tasks | 60 | | Dimensions | 9 | | Max raw score | 1200 (normalized to 100) | | Scoring layers | 4 (Rubric + Quality + Semantic + LLM-as-Judge) | | Language | Chinese (primary), English (partial), ABAP | | License | Apache-2.0 | ## Dimensions 1. **Code Migration** (6 tasks) — ECC → S/4HANA API replacement 2. **Defect Discovery** (6 tasks) — Finding hidden bugs in ABAP code 3. **Code Rewriting** (6 tasks) — Modernizing legacy ABAP 4. **China Compliance** (6 tasks) — Golden Tax, PIPL, payroll regulations 5. **Migration Risk** (6 tasks) — Change impact and dependency analysis 6. **Security & Auth** (6 tasks) — Authorization, injection, transport security 7. **S/4HANA Architecture** (6 tasks) — ACDOCA, CDS views, FI-CO integration 8. **Performance Engineering** (6 tasks) — SELECT optimization, HANA features 9. **Modern Ecosystem** (12 tasks) — Clean Core, testing, Fiori, workflow, IDoc ## Usage ```python import json # Load tasks tasks = [] with open("data/tasks.jsonl") as f: for line in f: tasks.append(json.loads(line)) # Each task has: task_id, title, dimension, max_score, prompt_template print(tasks[0]["prompt_template"]) ``` ## Evaluation ```bash pip install -e . python -m src.evaluate_v2 --task T01 --response "your model output" --breakdown ``` ## Citation ```bibtex @misc{abapbench2026, title={ABAP-Bench: A Benchmark for Evaluating LLM Understanding of SAP ABAP and S/4HANA Modernization}, author={ABAP-Bench Contributors}, year={2026}, version={4.0}, howpublished={\url{https://github.com/abap-bench/abap-bench}}, } ```