Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

10-2025

Abstract

Reproducibility Debt (RpD) refers to accumulated technical and organisational issues in scientific software that hinder the ability to reproduce research results. While reproducibility is essential to scientific integrity, RpD remains poorly defined and under-addressed. This study introduces a formal definition of RpD and investigates its causes, effects, and mitigation strategies using a mixed-methods approach involving a systematic literature review (214 papers), interviews (23 practitioners), and a global survey (59 participants). We identify seven categories of contributing issues, 75 causes, 110 effects, and 61 mitigation strategies. Findings are synthesised into a cause-effect model and supported by taxonomies of team roles and software types. This work provides conceptual clarity and practical tools to help researchers, developers, and institutions understand and manage RpD, ultimately supporting more sustainable and reproducible scientific software.

Keywords

Reproducibility, Technical Debt, Scientific Software, Scientific Computing, Computational Reproducibility

Discipline

Software Engineering

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

SPLASH Companion '25: Companion Proceedings of the 2025 ACM SIGPLAN International Conference on Systems, Programming, Languages, and Applications: Software for Humanity, Singapore, October 12-18

First Page

50

Last Page

51

ISBN

9798400721410

Identifier

10.1145/3758316.3765482

Publisher

ACM

City or Country

New York

Additional URL

https://doi.org/10.1145/3758316.3765482

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