Pregled bibliografske jedinice broj: 766670
Data Collection for Software Defect Prediction – an Exploratory Case Study of Open Source Software Projects
Data Collection for Software Defect Prediction – an Exploratory Case Study of Open Source Software Projects // Proceedings of MIPRO CTI 2015 / Biljanović, Petar (ur.).
Rijeka: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2015. str. 513-519 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 766670 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Data Collection for Software Defect Prediction – an Exploratory Case Study of Open Source Software Projects
Autori
Mauša, Goran ; Galinac Grbac, Tihana ; Dalbelo Bašić, Bojana
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of MIPRO CTI 2015
/ Biljanović, Petar - Rijeka : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2015, 513-519
ISBN
978-953-233-083-0
Skup
38th International Convention MIPRO 2015
Mjesto i datum
Opatija, Hrvatska, 25.05.2015. - 29.05.2015
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
software defect prediction; mining software repositories
Sažetak
Software Defect Prediction (SDP) empirical studies are highly biased with the quality of data and widely suffer from limited generalizations. The main reasons are the lack of data and its systematic data collection procedures. Our research aims at producing the first systematically defined data collection procedure for SDP datasets that are obtained by linking separate development repositories. This paper is the first step to achieving that objective, performing an exploratory study. We review the existing literature on approaches and tools used in the collection of SDP datasets, derive a detailed collection procedure and test it in this exploratory study. We quantify the bias that may be caused by the issues we identified and we review 35 tools for software product metrics collection. The most critical issues are many-to-many relation between bug-file links, duplicated bug-file links and the issue of untraceable bugs. Our research provides more detailed, experience based data collection procedure, crucial for further development of SDP body of knowledge. Furthermore, our findings enabled us to develop the automatic data collection tool.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo
POVEZANOST RADA
Projekti:
13.09.2.2.16.
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Tehnički fakultet, Rijeka