research-article

The case for software evolution

Authors:

Claire Le Goues,

Stephanie Forrest,

Westley WeimerAuthors Info & Claims

FoSER '10: Proceedings of the FSE/SDP workshop on Future of software engineering research

Pages 205 - 210

https://doi.org/10.1145/1882362.1882406

Published: 07 November 2010 Publication History

Abstract

Many software systems exceed our human ability to comprehend and manage, and they continue to contain unacceptable errors. This is an unintended consequence of Moore's Law, which has led to increases in system size, complexity, and interconnectedness. Yet, software is still primarily created, modified, and maintained by humans. The interactions among heterogeneous programs, machines and human operators has reached a level of complexity rivaling that of some biological ecosystems. By viewing software as an evolving complex system, researchers could incorporate biologically inspired mechanisms and employ the quantitative analysis methods of evolutionary biology. This approach could improve our understanding and analysis of software; it could lead to robust methods for automatically writing, debugging and improving code; and it could improve predictions about functional and structural transitions as scale increases. In the short term, an evolutionary perspective challenges several research assumptions, enabling advances in error detection, correction, and prevention.

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Cited By

Langdon WKrauss OCoello Coello C(2020)Evolving sqrt into 1/x via software data maintenanceProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion10.1145/3377929.3398110(1928-1936)Online publication date: 8-Jul-2020
https://dl.acm.org/doi/10.1145/3377929.3398110
Rao MBacon DParkes DSeltzer M(2020)Incentivizing Deep Fixes in Software EconomiesIEEE Transactions on Software Engineering10.1109/TSE.2018.284218846:1(51-70)Online publication date: 1-Jan-2020
https://doi.org/10.1109/TSE.2018.2842188
Le Goues CForrest SWeimer W(2013)Current challenges in automatic software repairSoftware Quality Journal10.1007/s11219-013-9208-021:3(421-443)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1007/s11219-013-9208-0
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The case for software evolution

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cover image ACM Conferences

FoSER '10: Proceedings of the FSE/SDP workshop on Future of software engineering research

November 2010

460 pages

ISBN:9781450304276

DOI:10.1145/1882362

General Chair:
Gruia-Catalin Roman
Washington University in St. Louis, USA
,
Program Chair:
Kevin Sullivan
University of Virginia, USA

Copyright © 2010 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGSOFT: ACM Special Interest Group on Software Engineering

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Published: 07 November 2010

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SIGSOFT/FSE'10: 18th ACM SIGSOFT Symposium on the Foundations of Software Engineering

November 7 - 8, 2010

New Mexico, Santa Fe, USA

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Cited By

Langdon WKrauss OCoello Coello C(2020)Evolving sqrt into 1/x via software data maintenanceProceedings of the 2020 Genetic and Evolutionary Computation Conference Companion10.1145/3377929.3398110(1928-1936)Online publication date: 8-Jul-2020
https://dl.acm.org/doi/10.1145/3377929.3398110
Rao MBacon DParkes DSeltzer M(2020)Incentivizing Deep Fixes in Software EconomiesIEEE Transactions on Software Engineering10.1109/TSE.2018.284218846:1(51-70)Online publication date: 1-Jan-2020
https://doi.org/10.1109/TSE.2018.2842188
Le Goues CForrest SWeimer W(2013)Current challenges in automatic software repairSoftware Quality Journal10.1007/s11219-013-9208-021:3(421-443)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1007/s11219-013-9208-0
Yamakami T(2011)A cognitively meaningful digital ecosystem approach: Implications for mobile digital ecosystem5th IEEE International Conference on Digital Ecosystems and Technologies (IEEE DEST 2011)10.1109/DEST.2011.5936626(203-207)Online publication date: May-2011
https://doi.org/10.1109/DEST.2011.5936626

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