Feature space for statistical classification of Java source code patterns

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F14%3A00218677" target="_blank" >RIV/68407700:21340/14:00218677 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1109/CarpathianCC.2014.6843627" target="_blank" >http://dx.doi.org/10.1109/CarpathianCC.2014.6843627</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/CarpathianCC.2014.6843627" target="_blank" >10.1109/CarpathianCC.2014.6843627</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Feature space for statistical classification of Java source code patterns

Popis výsledku v původním jazyce

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 ofnewly 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.

Název v anglickém jazyce

Feature space for statistical classification of Java source code patterns

Popis výsledku anglicky

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 ofnewly 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.

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

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Projekt

<a href="/cs/project/LG13031" target="_blank" >LG13031: Spolupráce ČR s CERN</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2014

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 2014 15th International Carpathian Control Conference (ICCC)

ISBN

9781479935284

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

357-361

Název nakladatele

VŠB

Místo vydání

Ostrava

Místo konání akce

Velké Karlovice

Datum konání akce

28. 5. 2014

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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