The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/29a6a7bc-8b45-472c-bf26-710f2a2d1a3c

Nistor, Razvan; Applis, Leonhard; Cockx, Jesper (2024): Data underlying the Bachelor's thesis: Adapting existing bug taxonomies to Haskell. Version 2. 4TU.ResearchData. dataset. https://doi.org/10.4121/29a6a7bc-8b45-472c-bf26-710f2a2d1a3c.v2

Dataset

x choose version: version 1 - 2024-06-19

• Other Information and Computing Sciences
• Information and Computing Sciences

Bug Classification, Haskell, Interviews, Taxonomy

2024

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Razvan Nistor , Leonhard Applis , Jesper Cockx

The goal of the paper is to identify the extent to which existing bug taxonomies can classify bugs in Haskell, and how they could be adapted to better accommodate the unique features of Haskell. The specific research questions that were studied are:

RQ1 What are the most common types of Haskell bugs?

RQ2 What are the limitations of existing bug taxonomies in capturing the unique features of Haskell bugs?

RQ3 How do Haskell developers classify bugs and how is it different from the previously discussed taxonomies?

The data collected for the creation of the paper includes:

• A bug dataset of 142 bugs from 10 Haskell FOSS (free open-source software) projects, classified according to 2 taxonomies.

• A qualitative codebook created after 4 interviews performed with Haskell developers about their perspectives on bugs.

• 2024-06-19 first online

• 2024-09-20 published, posted

4TU.ResearchData

taxonomy description/pdf; codebook/pdf; bugDB/csv; bugDB/xlsx

• http://resolver.tudelft.nl/uuid:655e598b-9d5c-4e49-abf2-12516d95a9cb

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science