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Statements

Subject Item
n2:RIV%2F68407700%3A21340%2F14%3A00218677%21RIV15-MSM-21340___
rdf:type
skos:Concept n15:Vysledek
dcterms:description
To develop a reliable statistical classifiers of Java source code patterns, a feature space has to be developed and thoroughly examined as there are little general recommendations, such as in the field of image processing. This paper deals with development and evaluation of such feature space. Current version of feature space consisting of four categories and forty features is presented. Moreover, since feature collection from a source code is a non-trivial task, method of data acquisition with help of newly constructed domain specific language is given. Another issue that has to be solved is determination of structure of particular patterns, as their implementation can vary with different software projects. Straightforward patterns may have little explanatory power for project's architecture, however it could be demanding to detect more abstract ones. In addition, the proposed patterns should meet standards recognized by the software engineering community. To develop a reliable statistical classifiers of Java source code patterns, a feature space has to be developed and thoroughly examined as there are little general recommendations, such as in the field of image processing. This paper deals with development and evaluation of such feature space. Current version of feature space consisting of four categories and forty features is presented. Moreover, since feature collection from a source code is a non-trivial task, method of data acquisition with help of newly constructed domain specific language is given. Another issue that has to be solved is determination of structure of particular patterns, as their implementation can vary with different software projects. Straightforward patterns may have little explanatory power for project's architecture, however it could be demanding to detect more abstract ones. In addition, the proposed patterns should meet standards recognized by the software engineering community.
dcterms:title
Feature space for statistical classification of Java source code patterns Feature space for statistical classification of Java source code patterns
skos:prefLabel
Feature space for statistical classification of Java source code patterns Feature space for statistical classification of Java source code patterns
skos:notation
RIV/68407700:21340/14:00218677!RIV15-MSM-21340___
n3:aktivita
n14:I n14:S n14:P
n3:aktivity
I, P(LG13031), S
n3:dodaniDat
n9:2015
n3:domaciTvurceVysledku
Mojzeš, Matej n12:1560727 n12:1360108 n12:5745780
n3:druhVysledku
n20:D
n3:duvernostUdaju
n13:S
n3:entitaPredkladatele
n7:predkladatel
n3:idSjednocenehoVysledku
16598
n3:idVysledku
RIV/68407700:21340/14:00218677
n3:jazykVysledku
n22:eng
n3:klicovaSlova
statistical classifier; Java; source code pattern; feature space
n3:klicoveSlovo
n5:Java n5:feature%20space n5:source%20code%20pattern n5:statistical%20classifier
n3:kontrolniKodProRIV
[490EBE6B67E7]
n3:mistoKonaniAkce
Velké Karlovice
n3:mistoVydani
Ostrava
n3:nazevZdroje
Proceedings of the 2014 15th International Carpathian Control Conference (ICCC)
n3:obor
n8:JC
n3:pocetDomacichTvurcuVysledku
4
n3:pocetTvurcuVysledku
4
n3:projekt
n11:LG13031
n3:rokUplatneniVysledku
n9:2014
n3:tvurceVysledku
Smolka, Josef Virius, Miroslav Mojzeš, Matej Rost, Michal
n3:typAkce
n21:EUR
n3:zahajeniAkce
2014-05-28+02:00
s:numberOfPages
5
n16:doi
10.1109/CarpathianCC.2014.6843627
n18:hasPublisher
Vysoká škola báňská - Technická univerzita Ostrava
n17:isbn
9781479935284
n10:organizacniJednotka
21340