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文件名称:Algo
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- 上传时间：2015-12-06
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For a given program, testing, locating the errors identified,
and correcting those errors is a critical, yet expensive process.
The field of Search Based Software Engineering (SBSE)
addresses these phases by formulating them as search problems.
The Coevolutionary Automated Software Correction
(CASC) system targets the correction phase by coevolving
test cases and programs at the source code level. The latest
version of the CASC system is presented, featuring multiobjective
optimization and an enhanced representation language.
Results are presented demonstrating CASC’s ability
to successfully correct five seeded bugs in two non-trivial
programs the Siemens test suite. Additionally, evidence
is provided substantiating the hypothesis that multiobjective
optimization is beneficial to SBSE-For a given program, testing, locating the errors identified,
and correcting those errors is a critical, yet expensive process.
The field of Search Based Software Engineering (SBSE)
addresses these phases by formulating them as search problems.
The Coevolutionary Automated Software Correction
(CASC) system targets the correction phase by coevolving
test cases and programs at the source code level. The latest
version of the CASC system is presented, featuring multiobjective
optimization and an enhanced representation language.
Results are presented demonstrating CASC’s ability
to successfully correct five seeded bugs in two non-trivial
programs the Siemens test suite. Additionally, evidence
is provided substantiating the hypothesis that multiobjective
optimization is beneficial to SBSE
and correcting those errors is a critical, yet expensive process.
The field of Search Based Software Engineering (SBSE)
addresses these phases by formulating them as search problems.
The Coevolutionary Automated Software Correction
(CASC) system targets the correction phase by coevolving
test cases and programs at the source code level. The latest
version of the CASC system is presented, featuring multiobjective
optimization and an enhanced representation language.
Results are presented demonstrating CASC’s ability
to successfully correct five seeded bugs in two non-trivial
programs the Siemens test suite. Additionally, evidence
is provided substantiating the hypothesis that multiobjective
optimization is beneficial to SBSE-For a given program, testing, locating the errors identified,
and correcting those errors is a critical, yet expensive process.
The field of Search Based Software Engineering (SBSE)
addresses these phases by formulating them as search problems.
The Coevolutionary Automated Software Correction
(CASC) system targets the correction phase by coevolving
test cases and programs at the source code level. The latest
version of the CASC system is presented, featuring multiobjective
optimization and an enhanced representation language.
Results are presented demonstrating CASC’s ability
to successfully correct five seeded bugs in two non-trivial
programs the Siemens test suite. Additionally, evidence
is provided substantiating the hypothesis that multiobjective
optimization is beneficial to SBSE
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下载文件列表
Algo/.classpath
Algo/.project
Algo/.settings/org.eclipse.jdt.core.prefs
Algo/bin/genetic.class
Algo/bin/individual.class
Algo/src/genetic.java
Algo/src/individual.java
Algo/.settings
Algo/bin
Algo/src
Algo
Algo/.project
Algo/.settings/org.eclipse.jdt.core.prefs
Algo/bin/genetic.class
Algo/bin/individual.class
Algo/src/genetic.java
Algo/src/individual.java
Algo/.settings
Algo/bin
Algo/src
Algo
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