Automated Analysis of Source Code Patches using Machine Learning Algorithms

An updated version of a tool for automated analysis of source code patches and branch differences is presented. The upgrade involves the use of machine learning techniques on source code, comments, and messages. It aims to help analysts, code reviewers, or auditors perform repetitive tasks continuou...

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Detalles Bibliográficos
Autores principales: Castro Lechtaler, Antonio, Liporace, Julio César, Cipriano, Marcelo, García, Edith, Maiorano, Ariel, Malvacio, Eduardo, Tapia, Néstor
Formato: Objeto de conferencia
Lenguaje:Inglés
Publicado: 2015
Materias:
Ciencias Informáticas
Data mining
Algorithms
text mining
software quality
patch analysis
Acceso en línea:http://sedici.unlp.edu.ar/handle/10915/50585
Aporte de:
SEDICI (UNLP) de Universidad Nacional de La Plata
id I19-R120-10915-50585
record_format dspace
institution Universidad Nacional de La Plata
institution_str I-19
repository_str R-120
collection SEDICI (UNLP)
language Inglés
topic Ciencias Informáticas
Data mining
Algorithms
text mining
software quality
patch analysis
spellingShingle Ciencias Informáticas
Data mining
Algorithms
text mining
software quality
patch analysis
Castro Lechtaler, Antonio
Liporace, Julio César
Cipriano, Marcelo
García, Edith
Maiorano, Ariel
Malvacio, Eduardo
Tapia, Néstor
Automated Analysis of Source Code Patches using Machine Learning Algorithms
topic_facet Ciencias Informáticas
Data mining
Algorithms
text mining
software quality
patch analysis
description An updated version of a tool for automated analysis of source code patches and branch differences is presented. The upgrade involves the use of machine learning techniques on source code, comments, and messages. It aims to help analysts, code reviewers, or auditors perform repetitive tasks continuously. The environment designed encourages collaborative work. It systematizes certain tasks pertaining to reviewing or auditing processes. Currently, the scope of the automated test is limited. Current work aims to increase the volume of source code analyzed per time unit, letting users focus on alerts automatically generated. The tool is distributed as open source software. This work also aims to provide arguments in support of the use of this type of tool. A brief overview of security problems in open source software is presented. It is argued that these problems were or may have been discovered reviewing patches and branch differences, released before the vulnerability was disclosed.
format Objeto de conferencia
Objeto de conferencia
author Castro Lechtaler, Antonio
Liporace, Julio César
Cipriano, Marcelo
García, Edith
Maiorano, Ariel
Malvacio, Eduardo
Tapia, Néstor
author_facet Castro Lechtaler, Antonio
Liporace, Julio César
Cipriano, Marcelo
García, Edith
Maiorano, Ariel
Malvacio, Eduardo
Tapia, Néstor
author_sort Castro Lechtaler, Antonio
title Automated Analysis of Source Code Patches using Machine Learning Algorithms
title_short Automated Analysis of Source Code Patches using Machine Learning Algorithms
title_full Automated Analysis of Source Code Patches using Machine Learning Algorithms
title_fullStr Automated Analysis of Source Code Patches using Machine Learning Algorithms
title_full_unstemmed Automated Analysis of Source Code Patches using Machine Learning Algorithms
title_sort automated analysis of source code patches using machine learning algorithms
publishDate 2015
url http://sedici.unlp.edu.ar/handle/10915/50585
work_keys_str_mv AT castrolechtalerantonio automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
AT liporacejuliocesar automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
AT ciprianomarcelo automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
AT garciaedith automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
AT maioranoariel automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
AT malvacioeduardo automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
AT tapianestor automatedanalysisofsourcecodepatchesusingmachinelearningalgorithms
bdutipo_str Repositorios
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