article

An empirical analysis of the transition from Python 2 to Python 3

Authors:

Brian A. Malloy,

James F. PowerAuthors Info & Claims

Empirical Software Engineering, Volume 24, Issue 2

Pages 751 - 778

https://doi.org/10.1007/s10664-018-9637-2

Published: 01 April 2019 Publication History

Abstract

Python is one of the most popular and widely adopted programming languages in use today. In 2008 the Python developers introduced a new version of the language, Python 3.0, that was not backward compatible with Python 2, initiating a transitional phase for Python software developers. In this paper, we describe a study that investigates the degree to which Python software developers are making the transition from Python 2 to Python 3. We have developed a Python compliance analyser, PyComply, and have analysed a previously studied corpus of Python applications called Qualitas. We use PyComply to measure and quantify the degree to which Python 3 features are being used, as well as the rate and context of their adoption in the Qualitas corpus. Our results indicate that Python software developers are not exploiting the new features and advantages of Python 3, but rather are choosing to retain backward compatibility with Python 2. Moreover, Python developers are confining themselves to a language subset, governed by the diminishing intersection of Python 2, which is not under development, and Python 3, which is under development with new features being introduced as the language continues to evolve.

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An empirical analysis of the transition from Python 2 to Python 3
1. Software and its engineering
  1. Software notations and tools
    1. General programming languages
      1. Language types

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cover image Empirical Software Engineering

Empirical Software Engineering Volume 24, Issue 2

April 2019

519 pages

ISSN:1382-3256

Issue’s Table of Contents

Copyright © Copyright © 2019 Springer Science+Business Media, LLC, part of Springer Nature.

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Kluwer Academic Publishers

United States

Publication History

Published: 01 April 2019

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Cited By

Agarwal SChimalakonda SKrishnan SKanvar VShah S(2024)Tutorial Report on Legacy Software Modernization: A Journey From Non-AI to Generative AI ApproachesProceedings of the 17th Innovations in Software Engineering Conference10.1145/3641399.3641434(1-3)Online publication date: 22-Feb-2024
https://dl.acm.org/doi/10.1145/3641399.3641434
Admiraal Cvan den Brink WGerhold MZaytsev VZubcu C(2024)Deriving modernity signatures of codebases with static analysisJournal of Systems and Software10.1016/j.jss.2024.111973211:COnline publication date: 2-Jul-2024
https://dl.acm.org/doi/10.1016/j.jss.2024.111973
Mumtaz FJehangiri AIshaq WAhmad ZAlramli OAla’anzy MGhoniem R(2024)Quality of interaction-based predictive model for support of online learning in pandemic situationsKnowledge and Information Systems10.1007/s10115-023-01995-366:3(1777-1805)Online publication date: 1-Mar-2024
https://dl.acm.org/doi/10.1007/s10115-023-01995-3
Simmons ABarnett SRivera-Villicana JBajaj AVasa R(2020)A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projectsProceedings of the 14th ACM / IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)10.1145/3382494.3410680(1-11)Online publication date: 5-Oct-2020
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Trautsch AHerbold SGrabowski J(2020)A longitudinal study of static analysis warning evolution and the effects of PMD on software quality in Apache open source projectsEmpirical Software Engineering10.1007/s10664-020-09880-125:6(5137-5192)Online publication date: 21-Sep-2020
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Izquierdo JCabot JNierstrasz OGray JOliveira B(2019)Analysis and modeling of the governance in general programming languagesProceedings of the 12th ACM SIGPLAN International Conference on Software Language Engineering10.1145/3357766.3359533(179-183)Online publication date: 20-Oct-2019
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