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giseldo
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neodataset

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metadata
license: afl-3.0
task_categories:
  - feature-extraction
  - text-classification
language:
  - en
pretty_name: 'NeoDATASET - User Story and story points from agile projects '
size_categories:
  - 10K<n<100K

This dataset contains User Story text and Story Points

Dataset Structure

Features

Column name Type Description
idproject int64 Project id
issuekey int64 User Story key
created string Created at
title string User Story text
description string User Story description
storypoints int64 Story Point

NEODATASET

NEODATASET is a dataset containing title and description in natural language of User Stories and their Story Points extracted from GitLab.

This dataset is used in my research, User Story Tutor, and was presented in this article. A version of the article is also available at arxiv.

Another use of this dataset can be seen in this another article at arxiv from another researchers.

Some information (in brazilian portuguese) can be read at this paper.

Description

This dataset encompasses data from 34 software development projects, with 40.014 User Stories taken from GitLab repositories, totaling 163.897 Story Points. It is made available on GitHub, huggging face and mendeley data, so that the entire interested community can contribute, similarly to what happens with other datasets.

This dataset was mined during January 2023 and April 2023. The mining process targeted GitLab’s top open-source projects. The selected projects employ agile software development methodologies and had the size of their tasks recorded in Story Points. To mine information from GitLab, we created an extraction tool implemented in Python that connects to GitLab via API. Only Tasks with the State attribute equal to Closed and that have the weight attribute filled in were collected. The weight field is used in GitLab to record the effort in Story Points. More information about the projects included in the dataset is also available directly from GitLab.

The projects in the dataset have different characteristics and cover different programming languages, different business domains, and different geographic locations of the team. The main entity of the dataset is the User Story (or Issue), which contains the main information. The CSV format is easier to use and contains only the attributes: issue key, created, title, description, and story points, making it more user-friendly.

The expected contribution is that this data set can assist education and research on agile software development. Although our dataset was initially designed for Story Points and User Story estimation training and research, it also includes information relevant to other software engineering aspects. In addition to providing a possibility to reproduce findings from other studies.

CSV dataset columns 

classDiagram
   class Issue {
     - issuekey
     - created
     - title 
     - description 
     - storypoints
    }
  • issuekey: User Story ID
  • created: Date of the created of the User Story
  • title: Title of User Story
  • description: Description of User Story
  • storypoints: Count of the user story informed by the team

image

Info

You can also access this dataset in only one CSV file from HuggingFace repository. It also is available at Mendeley Data. 

import pandas as pd

df = pd.read_csv("hf://datasets/giseldo/neodataset/issues.csv")

Projects in dataset

ID Projeto Total Tarefas Total SP Média STD Mín 25% 50% 75% Max
10152778 Minds 521 1594 3,1 4,2 0 1 2 3 80
10171280 Minds Mobile 2796 7213 2,6 2,7 0 1 2 3 50
12894267 MLReef 285 1419 5,0 5,0 0 2 4 6 40
3828396 GitLab Chart 15 31 2,1 1,2 1 1 2 2 5
6206924 Tildes 42 91 2,2 1,0 1 1,25 2 3 4
12584701 StackGres 171 1106 6,5 7,4 1 2 4 8 48
7764 Gitlab.com 355 970 2,7 7,2 0 1 2 3 128
12450835 Duplicity 424 5798 13,7 22,1 4 6 6 12 260
28847821 Buyer Experience 1004 2665 2,7 2,0 0 1 2 4 14
10174980 Veloren 178 502 2,8 2,8 1 1 2 3 15
250833 Gitlab Runner 13 35 2,7 2,2 1 1 2 3 9
23285197 Subway 284 507 1,8 1,5 0 1 1 2 13
1304532 Gitlab GL Infra Reliability 1724 4520 2,6 2,5 0 1 2 3 21
14052249 Mythictable 167 509 3,0 2,9 1 2 2 3 20
28419588 Lazarus 144 17800 123,6 48,7 100 100 100 100 300
4456656 Pajamas Design System 344 684 2,0 1,6 0 1 1 3 13
3836952 Tezos 103 2771 26,9 38,6 0 2,5 5 32 100
7603319 Meltano 237 1107 4,7 5,3 0 1 4 8 40
7776928 Triage ops 216 442 2,0 1,2 1 1 2 2 10
2670515 Customers gitlab com 1574 3137 2,0 1,2 0 1 2 2 15
21149814 Opengeoweb 1942 5668 2,9 1,5 1 2 3 3 20
15502567 Kicad 3284 34692 10,6 14,2 4 6 6 10 268
1714548 Petals Vockpit 154 400 2,6 1,5 1 1 2 3 8
7128869 Nlx 327 1355 4,1 3,6 0 2 3 5 21
10171263 Minds Backend Engine 982 3742 3,8 3,7 0 2 3 5 32
14976868 Database Lab Engine 113 721 6,4 7,6 1 2 4 8 42
2009901 Gitaly 171 401 2,3 1,5 1 1 2 3 13
28644964 FPC Source 102 14200 139,2 63,2 100 100 100 200 300
7071551 Gitlab UI 310 600 1,9 2,0 0 1 2 2 32
734943 Gitlab Pages 121 265 2,2 2,6 1 1 1 3 20
10171270 Minds Frontend 1845 5695 3,1 3,2 0 1 2 4 40
5261717 Gitlab vscode extension 106 185 1,7 0,7 1 1 2 2 4
19921167 Glaxnimate 420 1802 4,3 4,0 1 2 3 5 40

Foi removido o projeto abaixo, pois é muito grande. Consulte https://github.com/giseldo/neodataset caso queira também incluir o projeto abaixo

| 278964 | GitLab | 19548 | 41270 | 2,1 | 1,8 | 0 | 1 | 2 | 3 | 160 |

How to cite

Neo, G. S., Moura, J., Almeida, H., Neo, A. and Freitas Júnior, O. (2024). User Story Tutor (UST) to Support Agile Software Developers. In Proceedings of the 16th International Conference on Computer Supported Education - Volume 2: CSEDU; ISBN 978-989-758-697-2; ISSN 2184-5026, SciTePress, pages 51-62. DOI: 10.5220/0012619200003693

@conference{csedu24,
author={Giseldo S. {Neo} and José Moura and Hyggo Almeida and Alana Neo and Olival {Freitas Júnior}},
title={User Story Tutor (UST) to Support Agile Software Developers},
booktitle={Proceedings of the 16th International Conference on Computer Supported Education - Volume 2: CSEDU},
year={2024},
pages={51-62},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012619200003693},
isbn={978-989-758-697-2},
issn={2184-5026},
}

Contact Autor

Giseldo S. Neo at [email protected]. More about-me in ResearchGate or in my personal site.