TEBench / README.md
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---
license: cc-by-4.0
language:
- en
task_categories:
- text-generation
tags:
- code
- software-engineering
- test-evolution
- unit-testing
- benchmark
- java
- coding-agents
size_categories:
- n<1K
pretty_name: TEBench
configs:
- config_name: default
data_files:
- split: test
path: data/test.parquet
---
# TEBench: Project-Level Test Evolution Benchmark
πŸ“„ **Paper:** https://arxiv.org/abs/2605.06125 &nbsp;|&nbsp; πŸ’» **Code:** https://github.com/iSEngLab/TEBench
**TEBench** is the first **project-level** benchmark for *test evolution*: given a
project repository and a commit that changes production code, a system must
**autonomously** (1) identify which existing tests need to be modified and where
new tests are needed, and (2) produce the corresponding test patch. Unlike prior
method-level benchmarks that pre-pair a changed method with its test
(`⟨m, m', t⟩`), TEBench requires reasoning across the whole project.
The benchmark contains **314 task instances from 10 real-world Java/Maven
projects** in the Defects4J ecosystem, each annotated with one or more of three
evolution types and accompanied by **developer-written ground-truth test
patches**.
## Evolution Types
| Type | Definition |
|------|------------|
| **Breaking** | An existing test fails to compile/run after the code change; the developer modifies it to restore correctness. |
| **Stale** | An existing test still passes after the change but no longer meaningfully validates the new behavior; the developer updates it anyway. |
| **Missing** | The developer adds a **new** test to cover behavior introduced/exposed by the change. |
A task may carry multiple types simultaneously.
## The Three-Version Structure
Each instance is built around three versions of the project:
- **Vβˆ’1** (`v_minus_1_commit`) β€” parent commit, before any change.
- **Vβˆ’0.5** β€” Vβˆ’1 **plus all non-test changes** from the commit (production code,
build config, resources), with the **original tests untouched**. Vβˆ’0.5 is *not*
a commit; it is reconstructed by applying `source_patch` to Vβˆ’1. This is the
state given to the system: *the source has moved on, the tests have not.*
- **V0** (`v0_commit`) β€” the full commit including the developer's actual test
changes. This is the **ground truth**.
In this dataset:
- `source_patch` applies to **Vβˆ’1** and reconstructs **Vβˆ’0.5** (the system input).
- `test_patch` is the **gold answer**: the developer's test changes (Vβˆ’0.5 β†’ V0).
Both patches were generated with `git diff --binary --full-index` and are verified
to apply cleanly to `v_minus_1_commit` with `git apply` (see `validate_patches.py`):
**314/314 source patches and 314/314 test patches apply.**
## Data Fields
| Field | Type | Description |
|-------|------|-------------|
| `instance_id` | string | Stable id, `<project>__<short_hash>`. |
| `project` | string | Project name. |
| `repo` | string | Upstream GitHub slug (e.g. `apache/commons-lang`). |
| `v_minus_1_commit` | string | **Vβˆ’1** commit hash (parent state, before the change). |
| `v0_commit` | string | **V0** commit hash (full ground-truth commit). |
| `v0_date` | string | V0 commit date. |
| `v0_message` | string | V0 commit message. |
| `labels` | list[string] | Evolution types: `breaking` / `stale` / `missing` (β‰₯1 per task). |
| `changed_test_methods` | list[string] | GT modified/added test methods (`Class.method`). |
| `new_test_files` | list[string] | Test files where GT adds new methods. |
| `new_test_methods` | string | JSON map `{TestClass: [methods]}` of GT-added methods. |
| `num_changed_files` | int | Files changed in the commit. |
| `src_changed_lines` | int | Production lines changed. |
| `test_changed_lines` | int | Test lines changed. |
| `source_patch` | string | **Vβˆ’1 β†’ Vβˆ’0.5** diff (non-test; given to the system). |
| `test_patch` | string | **Vβˆ’0.5 β†’ V0** diff (gold test changes). |
There is a single **`test`** split with 314 instances.
## Usage
```python
from datasets import load_dataset
ds = load_dataset("iSEngLab/TEBench", split="test")
ex = ds[0]
print(ex["instance_id"], ex["labels"])
```
Reconstruct the agent input (Vβˆ’0.5) for an instance:
```bash
git clone https://github.com/<repo>.git && cd <repo>
git checkout <v_minus_1_commit>
git apply source.patch # now at V-0.5: new source, old tests
# ... system produces test changes ...
git apply test.patch # gold V0 test changes, for reference/eval
```
## Evaluation
TEBench evaluates two dimensions (full harness and Docker image referenced below):
- **Identification** β€” Precision / Recall / F1 of the test methods the system
modifies/adds vs. the ground truth. Modified/deleted tests are matched at
**method** granularity; newly added tests at **file** granularity.
- **Update** β€” a composite of **executability** (compiles & passes),
**coverage overlap** with GT on the changed production methods (line + branch),
and **modification similarity** (token Jaccard vs. GT). Executability gates the
score: non-compiling updates score 0.
## Dataset Statistics
| Project | Tasks | Breaking | Stale | Missing |
|---------|------:|---------:|------:|--------:|
| commons-cli | 18 | 8 | 12 | 9 |
| commons-codec | 19 | 12 | 11 | 12 |
| commons-collections | 23 | 10 | 14 | 15 |
| commons-compress | 86 | 34 | 58 | 53 |
| commons-csv | 31 | 22 | 18 | 16 |
| commons-lang | 69 | 28 | 46 | 40 |
| commons-math | 8 | 8 | 3 | 2 |
| gson | 1 | 1 | 0 | 1 |
| jfreechart | 3 | 1 | 3 | 1 |
| jsoup | 56 | 48 | 42 | 50 |
| **Total** | **314** | **172** | **207** | **199** |
**Label distribution** (a task may carry several types, so shares do not sum to 100%):
| Type | Tasks | Share of 314 |
|------|------:|-------------:|
| Breaking | 172 | 54.8% |
| Stale | 207 | 65.9% |
| Missing | 199 | 63.4% |
- **Multi-label:** 219 tasks (69.7%) carry β‰₯2 types; 45 (14.3%) carry all three;
95 (30.3%) are single-type.
- **Complexity (median):** 4 changed files, 34 source lines, ~32 test lines changed.
## Construction
Built via a four-stage filtering pipeline over the Defects4J ecosystem:
67,670 commits (14 Maven projects) β†’ static filtering (post-2019, co-modification
of `src/main` and `src/test`, real method-body changes) β†’ 6,169 β†’ execution-based
validation (isolated worktrees, Maven Surefire + JaCoCo) β†’ 561 β†’ quality filtering
(no merges, 5–200 test lines changed, method-level dedup) β†’ **314 instances / 10
projects**.
## Companion Artifacts
- **Evaluation harness & code:** https://github.com/iSEngLab/TEBench β€”
identification & update scoring, baselines, dataset build scripts.
- **Reproducible environment:** a prebuilt Docker image, shipped as
`docker/tebench-env.tar` in this repository (see below).
## Docker Environment
The Docker image bundles everything needed to run and evaluate TEBench β€” all 10
project repositories, Maven 3.6.3, OpenJDK 8 / 11 / 17 (default JDK 8), and the
evaluated coding agents (Claude Code, Codex CLI, OpenCode CLI) β€” so you do not
have to configure per-project toolchains.
The image archive (`docker/tebench-env.tar`) is stored in this dataset repo as an
LFS file. HuggingFace is **not** a container registry, so you download the tar and
load it locally:
```bash
# 1. Download the image archive from this dataset repo
hf download iSEngLab/TEBench docker/tebench-env.tar --repo-type=dataset --local-dir .
# 2. Load it into your local Docker
docker load -i docker/tebench-env.tar
# 3. Start a container
docker run --rm -it tebench-env
# 4. Inside the container
cd /root/TestUpdate
java -version && mvn -version # JDK 8 + Maven 3.6.3
claude --version && codex --version && opencode --version
```
Switch JDK inside the container via `JAVA_HOME` (`JAVA11_HOME`, `JAVA17_HOME` are
also available). Agent worktrees are large derived artifacts and are **not**
bundled; regenerate them inside the container with the harness when needed.
## Licensing
- **Annotations / patch metadata in this dataset:** CC-BY-4.0.
- **Embedded source code** inside `source_patch` / `test_patch` remains under the
**original license of each upstream project** and must be used accordingly:
| Project(s) | License |
|------------|---------|
| commons-* (cli, codec, collections, compress, csv, lang, math), gson | Apache-2.0 |
| jsoup | MIT |
| jfreechart | LGPL-2.1 |
Attribution to the original authors is preserved through commit hashes and the
`repo` field. Redistribution of the Docker image (which contains full source
trees) must likewise honor these licenses.
## Citation
```bibtex
@article{tebench,
title = {TEBench: Benchmarking LLM Agents on Project-Level Test Evolution},
journal = {arXiv preprint arXiv:2605.06125},
year = {2026},
url = {https://arxiv.org/abs/2605.06125}
}
```