@conference {GBS16,
	title = {Enforcing Techniques and Transformation of {C/C++} Source Code to Heterogeneous Hardware},
	booktitle = {Proceedings of the 16th IEEE International Conference on Scalable Computing and Communication (ScalCom 2016)},
	year = {2016},
	month = {jul},
	pages = {1173{\textendash}1180},
	publisher = {IEEE Computer Society},
	organization = {IEEE Computer Society},
	address = {Toulouse, France},
	abstract = {Besides well-known CPU based architectures, the so-called accelerators (GPU, DSP, FPGA) are about to gain ground in everyday programming, computing tasks. However, programming such computation units is quite different from traditional programming for CPUs, and special skills are required from the developers. In this paper we present techniques, tooling support for the developers in the first step of re-engineering for parallelism in heterogeneous parallel platforms, namely to assure that the code to be offloaded to an accelerator conforms to its specific requirements by identifying the possible violations in the source code, and also by providing automatic code transformations for their elimination.},
	keywords = {C/C++, Cevelop, code transformation, Eclipse CDT, heterogeneous hardware, REPARA, Static Analysis},
	doi = {10.1109/UIC-ATC-ScalCom-CBDCom-IoP-SmartWorld.2016.0180},
	url = {http://ieeexplore.ieee.org/document/7816976/},
	author = {Gyimesi, G{\'a}bor and D{\'e}nes B{\'a}n and Istv{\'a}n Siket and Rudolf Ferenc and Brugnoni, Silvano and Corbat, Thomas and Sommerlad, Peter and Suter, Toni}
}
@conference {GGT15,
	title = {Characterization of Source Code Defects by Data Mining Conducted on {GitHub}},
	booktitle = {Proceedings of the 15th International Conference on Computational Science and Its Applications (ICCSA 2015)},
	series = {Lecture Notes in Computer Science (LNCS)},
	volume = {9159},
	year = {2015},
	month = {jun},
	pages = {47{\textendash}62},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	address = {Banff, Alberta, Canada},
	abstract = {In software systems the coding errors are unavoidable due to the frequent source changes, the tight deadlines and the inaccurate specifications. Therefore, it is important to have tools that help us in finding these errors. One way of supporting bug prediction is to analyze the characteristics of the previous errors and identify the unknown ones based on these characteristics. This paper aims to characterize the known coding errors. Nowadays, the popularity of the source code hosting services like GitHub are increasing rapidly. They provide a variety of services, among which the most important ones are the version and bug tracking systems. Version control systems store all versions of the source code, and bug tracking systems provide a unified interface for reporting errors. Bug reports can be used to identify the wrong and the previously fixed source code parts, thus the bugs can be characterized by static source code metrics or by other quantitatively measured properties using the gathered data. We chose GitHub for the base of data collection and we selected 13 Java projects for analysis. As a result, a database was constructed, which characterizes the bugs of the examined projects, thus can be used, inter alia, to improve the automatic detection of software defects.},
	keywords = {Bug database, Data mining, GitHub},
	doi = {10.1007/978-3-319-21413-9_4},
	url = {https://link.springer.com/chapter/10.1007\%2F978-3-319-21413-9_4},
	author = {Gyimesi, P{\'e}ter and Gyimesi, G{\'a}bor and T{\'o}th, Zolt{\'a}n and Rudolf Ferenc}
}
