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Funding Agency and Grant Number: Slovenian Research Agency [BI-HR/18-19-036]; Croatian Ministry of Science and Education
Funding text: The authors acknowledge the project (An empirical comparison of machine learning based approaches for code smell detection, BI-HR/18-19-036) which was supported financially by the Slovenian Research Agency and by Croatian Ministry of Science and Education.
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Adapting God Class thresholds for software defect prediction: A case study
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In software engineering there is an active research field of defect prediction using software metrics. While the research shows that the prediction of defects using software metrics performs well, prediction using metrics alone lacks clear refactoring capabilities. On the other hand, code smells have the ability to describe the code anomalies precisely, and suggest their refactoring. Therefore, code smells can be a much better starting position for software fault prediction. In this paper, we present the results of preliminary research on the ability to predict software defects with the code smell God Class. The aim of our research was to test the definition of God Class, as defined by Lanza and Marinescu in 2006, in the ability to predict defects in a case study of the open source projects JDT and PDE within the Eclipse framework. The definition of the God Class was adapted using the grid search technique, with the goal of maximizing the fault prediction ability while keeping the base of the original definition. The results show that adaption of the definition in the specific project resulted in improved fault prediction ability. © 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics, MIPRO 2019 - Proceedings. All rights reserved.
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<div class="BookChapter Publication short-list"> <div class="authors"> <span class="author-name" > Gradišnik, M. </span> <span class="author-type"> </span> ; <span class="author-name" > Beranic, T. </span> <span class="author-type"> </span> ; <span class="author-name" > Karakatic, S. </span> <span class="author-type"> </span> ; <span class="author-name" > Mauša, G. ✉ </span> <span class="author-type"> </span> </div ><div class="title"><a href="/gui2/?mode=browse¶ms=publication;30846878" mtid="30846878" target="_blank">Adapting God Class thresholds for software defect prediction: A case study</a></div> <div class="InBook">In: Marko, Koricic; Zeljko, Butkovic; Karolj, Skala; Zeljka, Car; Marina, Cicin-Sain; Snjezana, Babic; Vlado, Sruk; Dejan, Skvorc; Slobodan, Ribaric; Stjepan, Gros; Boris, Vrdoljak; Mladen, Mauher; Edvard, Tijan; Predrag, Pale; Darko, Huljenic; Tihana, Galinac Grbac; Matej, Janjic (szerk.) <span class="booktitle"><a href="/gui2/?mode=browse¶ms=publication;30738595" target="_blank">2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) : Proceedings : May 20–24, 2019 Opatija, Croatia </a></span > </div><div class="pub-info"> <span class="publishedAt">Rijeka, Horvátország : <span class="publisher">Croatian Society for Information and Communication Technology Electronics and Microelectronics (MIPRO)</span> <span class="year">(2019)</span> <span class="page"> pp. 1537-1542. Paper: 8757009 , 6 p. </span> </div> <div class="pub-end"><div class="identifier-list"> <span class="identifiers"> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="10.23919/MIPRO.2019.08757009" target="_blank" href="https://doi.org/10.23919/MIPRO.2019.08757009"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="000484544500274" target="_blank" href="https://www.webofscience.com/wos/woscc/full-record/WOS:000484544500274"> WoS </a> </span> <span class="id identifier oa_none" title="none"> <a style="color:blue" title="85070263786" target="_blank" href="http://www.scopus.com/record/display.url?origin=inward&eid=2-s2.0-85070263786"> Scopus </a> </span> </span> </div> <div class="short-pub-prop-list"> <span class="short-pub-mtid"> Közlemény:30846878 </span> <span class="status-holder"><span class="status-data status-APPROVED"> Nyilvános </span></span> <span class="pub-core"> Idéző </span> <span class="pub-type">Könyvrészlet (Konferenciaközlemény ) </span> <!-- && !record.category.scientific --> <span class="pub-category">Tudományos</span> </div> </div> </div><div class="BookChapter Publication long-list">
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<div class="title"><a href="/gui2/?mode=browse¶ms=publication;30846878" target="_blank">Adapting God Class thresholds for software defect prediction: A case study</a></div> <div class="InBook"><div class="chapter-in">In:</div> <div class="authors">
<div class="autype autype-1"> <span class="author-name" >Marko Koricic
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<span class="author-name" >Zeljko Butkovic
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<span class="author-name" >Karolj Skala
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<span class="author-name" >Zeljka Car
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;
<span class="author-name" >Predrag Pale
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<span class="author-name" >Darko Huljenic
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;
<span class="author-name" >Tihana Galinac Grbac
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;
<span class="author-name" >Matej Janjic
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(szerk.) </div>
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<div class="booktitle"><a href="/gui2/?mode=browse¶ms=publication;30738595" target="_blank">2019 42nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) : Proceedings : May 20–24, 2019 Opatija, Croatia </a></div>
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<div class="mtid"><span class="long-pub-mtid">Közlemény: 30846878</span>
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<div class="lastModified">Utolsó módosítás: 2023.03.13. 10:39 Kresák Réka (SZTE admin5 Informatikai Intézet)
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<pre class="comment" style="margin-top: 0; margin-bottom: 0;"><u>Megjegyzés</u>: Funding Agency and Grant Number: Slovenian Research Agency [BI-HR/18-19-036]; Croatian Ministry of Science and Education
Funding text: The authors acknowledge the project (An empirical comparison of machine learning based approaches for code smell detection, BI-HR/18-19-036) which was supported financially by the Slovenian Research Agency and by Croatian Ministry of Science and Educ...</pre>
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