SWE-MERA / README.md
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---
language:
- "en"
pretty_name: "SWE-MERA"
tags:
- SWE
- SWE-MERA
- text-to-text
- other
- agent
license: "mit"
task_categories:
- other
---
# SWE-MERA
Continuously updated [SWE-MERA](https://mera-evaluation.github.io/demo-swe-mera/leaderboard) dataset
### SWE-MERA splits:
- **dev**: for testing (10 samples)
- **lite**: presented at the leaderboard [here](https://mera-evaluation.github.io/demo-swe-mera/leaderboard) (750 samples)
- **full**: continuously updated to collect more data (2738 samples)
### Load dataset
```python
from datasets import load_dataset
ds = load_dataset("MERA-evaluation/SWE-MERA", split='dev')
```
### Evaluation
#### Description
The main tool to validate tasks is **repotest** (available at [PyPI](https://pypi.org/project/repositorytest/) or [GitHub](https://github.com/MERA-Evaluation/repotest))
`data.jsonl` - dataset file, where after the agent run, the `patch` column was changed
#### Install dependencies
```bash
pip install repositorytest
```
#### Run evaluation
```bash
swemera --fn_input=data.jsonl --fn_output=submission.jsonl --column_patch=patch --mode=docker
```
If you don't want to use Docker and prefer Conda or local execution:
```bash
swemera --fn_input=data.jsonl --fn_output=submission.jsonl --column_patch=patch --mode=local
```
### Schema
| Column Name | Type | Description | Is New Column |
|--------------------------|----------------|--------------------------------------------------------------------------------------------|--------------|
| repo | VARCHAR | Repository name (e.g., GitHub repository) | False |
| instance_id | VARCHAR | Unique identifier for task: f"{repo.replace('/', '__') + '_' + pr_number}" | False |
| base_commit | VARCHAR | Commit hash of the base code before patch applied | False |
| patch | VARCHAR | Code patch or diff applied to the base_commit to be the correct solution | False |
| test_patch | VARCHAR | Patch for test code, if separate from main code patch | False |
| problem_statement | VARCHAR | Description or statement of the problem to solve | False |
| hint_text | VARCHAR | Hints or tips for solving the problem from GitHub issue comments | False |
| created_at | VARCHAR | Date when the instance was created | False |
| closed_at | VARCHAR | Date when the instance was closed or resolved | True |
| version | VARCHAR | Version identifier for the instance or dataset | False |
| FAIL_TO_PASS | LIST[VARCHAR] | Test cases which were failing but later passed | False |
| PASS_TO_PASS | LIST[VARCHAR] | Test cases which passed at all times | False |
| environment_setup_commit | VARCHAR | Commit hash for environment setup configuration | False |
| command_build | VARCHAR | Command used to build the repo | True |
| command_test | VARCHAR | Command used to run the tests inside repo | True |
| image_name | VARCHAR | Docker or container image name used for testing environment | True |
| command_test_small | VARCHAR | Command to run a smaller subset of tests | True |
| timeout_build | INTEGER | Timeout limit in seconds for build command | True |
| timeout_test | INTEGER | Timeout limit in seconds for test command | True |
| meta | DICT[STR,ANY] | Additional metadata about the instance* |
*meta field description:
```json
{
"score": {
"task_correctness": "INTEGER",
"test_correctness": "INTEGER",
"complexity": "INTEGER",
"test_completeness": "INTEGER"
},
"type": "VARCHAR",
"pr_number": "INTEGER",
"issue_number": "INTEGER",
"merged_at": "VARCHAR",
"tag": "VARCHAR // Information on how data was collected",
"merge_commit": "VARCHAR",
"task_id": "VARCHAR // Latency identifier of the task",
"url": {
"issue": "VARCHAR",
"pr": "VARCHAR",
"diff": "VARCHAR"
},
"command_test_small": "VARCHAR // Command to run only a small number of tests"
}
```
### Dev tasks Examples
### Instances
| Instance ID | Short Title |
|------------------------ |---------------------------------------------------------------------------------------------------------------------------------------|
| reframe-0 | Performance threshold goes to -inf when it should be zero. |
| pyflakes-1 | Walrus operator + annotation can cause F821 |
| sqlglot-2 | MySQL dialect fails to parse PRIMARY KEY USING BTREE syntax |
| matchms-3 | matchms fails when reading spectra where abundance is in scientific notation #809 |
| guarddog-4 | Add Mach-O magic bytes to bundled binary detector #523 |
| pdoc-5 | Include HTML headers in ToC |
| QCElemental-6 | QCElemental allows floating point numbers for molecular charges, however when computing the spin with the fractional electron there is no way to represent the molecular multiplicity with just an integer. |
| sqlglot-7 | TSQL: PRIMARY KEY constraint fails to parse if |
| sqlglot-8 | [BUG] Conversion from SQL Server's DATEADD(quarter...) to PostgreSQL not working properly |
| python-markdownify-9 | Inline Quotation element ignored |