metadata

dataset_info:
  features:
    - name: year
      dtype: string
    - name: session
      dtype: string
    - name: utility_classes
      list:
        - name: content
          dtype: string
        - name: filename
          dtype: string
    - name: solution
      list:
        - name: content
          dtype: string
        - name: filename
          dtype: string
    - name: test
      struct:
        - name: components
          struct:
            - name: imports
              dtype: string
            - name: private_init
              dtype: string
            - name: test_functions
              sequence: string
        - name: content
          dtype: string
        - name: filename
          dtype: string
  splits:
    - name: test
      num_bytes: 1422409
      num_examples: 103
  download_size: 436957
  dataset_size: 1422409
configs:
  - config_name: default
    data_files:
      - split: test
        path: data/test-*

JAB: Java Academic Benchmark

Overview

The Java Academic Benchmark (JAB) is the first exam-based benchmark specifically designed to rigorously evaluate Large Language Models (LLMs) on Java Object-Oriented Programming (OOP) capabilities.

JAB comprises 103 real Java exams administered between 2014 and 2024 at a top-tier academic institution, designed and curated by Professor Mirko Viroli, an experienced full professor and co-author of this project. This ensures that each task reflects pedagogically grounded and conceptually meaningful challenges.

Unlike benchmarks that focus on isolated code snippets, JAB features full exam-style problems with expert-authored JUnit test suites, targeting class- and interface-level reasoning. Designed to assess human learners, these problems isolate common misconceptions and test deep understanding, offering granular insights into where and how models fall short.

Dataset Structure

Each exam in the JAB dataset is structured as follows:

year: Year of the exam session
session: Specific session identifier
utility_classes: Utility classes provided to students during the exam
solution: Gold solution created by Prof. Viroli (one of many possible solutions)
test: JUnit test cases that must be passed

Benchmark Significance

JAB offers several unique advantages for evaluating LLMs on Java programming tasks:

Educational Validity: Problems are designed by education experts to test conceptual understanding
Comprehensive Assessment: Tasks require full class implementations rather than just completing isolated functions
Object-Oriented Focus: Specifically targets OOP concepts including inheritance, polymorphism, encapsulation, and interfaces
Longitudinal Coverage: Spans a decade of real academic assessments (2014-2024)
Test-Driven Evaluation: Uses rigorous JUnit test suites for objective assessment

License

This dataset is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) license.

You are free to:

Share — copy and redistribute the material in any medium or format

Under the following terms:

Attribution — You must give appropriate credit (see below), provide a link to the license, and indicate if changes were made.
NonCommercial — You may not use the material for commercial purposes.
NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.

For details, see: https://creativecommons.org/licenses/by-nc-nd/4.0/

Citation

If you use JAB in your research, please cite:

<bib of our future paper>

Contact

For questions or further information about the JAB benchmark, please contact:

Mirko Viroli