Applying information theory to software evolution

Although information theory has found success in disciplines, the literature on its applications to software evolution is limit. We are still missing artifacts that leverage the data and tooling available to measure how the information content of a project can be a proxy for its complexity. In this...

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Main Authors: TORRES, Adriano, BALTES, Sebastian, TREUDE, Christoph, WAGNER, Markus
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2023
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Online Access:https://ink.library.smu.edu.sg/sis_research/8893
https://ink.library.smu.edu.sg/context/sis_research/article/9896/viewcontent/adriano.pdf
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spelling sg-smu-ink.sis_research-98962024-06-27T09:01:48Z Applying information theory to software evolution TORRES, Adriano BALTES, Sebastian TREUDE, Christoph WAGNER, Markus Although information theory has found success in disciplines, the literature on its applications to software evolution is limit. We are still missing artifacts that leverage the data and tooling available to measure how the information content of a project can be a proxy for its complexity. In this work, we explore two definitions of entropy, one structural and one textual, and apply it to the historical progression of the commit history of 25 open source projects. We produce evidence that they generally are highly correlated. We also observed that they display weak and unstable correlations with other complexity metrics. Our preliminary investigation of outliers shows an unexpected high frequency of events where there is considerable change in the information content of the project, suggesting that such outliers may inform a definition of surprisal. 2023-05-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/8893 info:doi/10.1109/NLBSE59153.2023.00017 https://ink.library.smu.edu.sg/context/sis_research/article/9896/viewcontent/adriano.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University entropy Information theory software engineering Software Engineering
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic entropy
Information theory
software engineering
Software Engineering
spellingShingle entropy
Information theory
software engineering
Software Engineering
TORRES, Adriano
BALTES, Sebastian
TREUDE, Christoph
WAGNER, Markus
Applying information theory to software evolution
description Although information theory has found success in disciplines, the literature on its applications to software evolution is limit. We are still missing artifacts that leverage the data and tooling available to measure how the information content of a project can be a proxy for its complexity. In this work, we explore two definitions of entropy, one structural and one textual, and apply it to the historical progression of the commit history of 25 open source projects. We produce evidence that they generally are highly correlated. We also observed that they display weak and unstable correlations with other complexity metrics. Our preliminary investigation of outliers shows an unexpected high frequency of events where there is considerable change in the information content of the project, suggesting that such outliers may inform a definition of surprisal.
format text
author TORRES, Adriano
BALTES, Sebastian
TREUDE, Christoph
WAGNER, Markus
author_facet TORRES, Adriano
BALTES, Sebastian
TREUDE, Christoph
WAGNER, Markus
author_sort TORRES, Adriano
title Applying information theory to software evolution
title_short Applying information theory to software evolution
title_full Applying information theory to software evolution
title_fullStr Applying information theory to software evolution
title_full_unstemmed Applying information theory to software evolution
title_sort applying information theory to software evolution
publisher Institutional Knowledge at Singapore Management University
publishDate 2023
url https://ink.library.smu.edu.sg/sis_research/8893
https://ink.library.smu.edu.sg/context/sis_research/article/9896/viewcontent/adriano.pdf
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