Datasets:
Formats:
json
Languages:
English
Size:
10K - 100K
ArXiv:
Tags:
software-engineering
evaluation-harness
github-issues
issue-classification
empirical-software-engineering
llm-evaluation
License:
File size: 3,125 Bytes
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pretty_name: EvalEng
language:
- en
license: mit
task_categories:
- text-classification
- token-classification
- summarization
task_ids:
- multi-class-classification
- multi-label-classification
tags:
- software-engineering
- evaluation-harness
- github-issues
- issue-classification
- empirical-software-engineering
- llm-evaluation
- benchmark-engineering
- mlops
- dataset-mining
- text
- tabular
- arxiv:2605.24213
size_categories:
- 10K<n<100K
annotations_creators:
- machine-generated
- expert-generated
source_datasets:
- original
homepage: https://github.com/zhimin-z/EvalEng
paperswithcode_id: null
dataset_info:
features:
- name: harness_name
dtype: string
- name: github_repo
dtype: string
- name: issue_title
dtype: string
- name: issue_body
dtype: string
- name: issue_url
dtype: string
- name: issue_created_at
dtype: int64
- name: issue_closed_at
dtype: int64
- name: is_related
dtype: float64
- name: stage
dtype: float64
- name: step
dtype: string
- name: strategy
dtype: float64
- name: root_cause_label
dtype: string
- name: issue_comments
sequence: string
- name: issue_labels
sequence: string
- name: issue_cross_referenced
sequence: string
configs:
- config_name: default
data_files:
- split: train
path: train.jsonl
viewer: true
---
# EvalEng Dataset
GitHub issues collected from 57 ML evaluation harnesses, annotated with workflow stage, root cause, and evaluation strategy labels.
## Dataset Details
- **Paper:** [Towards Evaluation Engineering](https://arxiv.org/abs/2605.24213)
- **Repository:** https://github.com/zhimin-z/EvalEng
- **License:** MIT
## Fields
| Field | Type | Description |
|-------|------|-------------|
| `harness_name` | string | Name of the ML evaluation harness |
| `github_repo` | string | GitHub repository (owner/repo) |
| `issue_title` | string | Issue title |
| `issue_body` | string | Issue body text |
| `issue_url` | string | Direct URL to the GitHub issue |
| `issue_created_at` | int64 | Creation timestamp (ms since epoch) |
| `issue_closed_at` | int64 | Closed timestamp (ms since epoch) |
| `is_related` | float64 | Whether the issue is related to evaluation (1.0 = yes) |
| `stage` | float64 | Workflow stage label (numeric) |
| `step` | string | Workflow step label |
| `strategy` | float64 | Evaluation strategy label (numeric) |
| `root_cause_label` | string | Root cause category |
| `issue_comments` | list[string] | Issue comment texts |
| `issue_labels` | list[string] | GitHub labels on the issue |
| `issue_cross_referenced` | list[string] | Cross-referenced issue/PR URLs |
## Citation
```bibtex
@article{zhao2025evaleng,
title={Towards Evaluation Engineering: An Empirical Study of ML Evaluation Harnesses in the Wild},
author={Zhimin Zhao and Zehao Wang and Abdul Ali Bangash and Bram Adams and Ahmed E. Hassan},
year={2026},
eprint={2605.24213},
archivePrefix={arXiv},
primaryClass={cs.SE},
url={https://arxiv.org/abs/2605.24213},
}
``` |