@conference {965,
	title = {Identifying licensing of jar archives using a code-search approach},
	booktitle = {2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)2010 7th IEEE Working Conference on Mining Software Repositories (MSR 2010)},
	year = {2010},
	pages = {151 - 160},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Cape Town, South Africa},
	abstract = {Free and open source software strongly promotes the reuse of source code. Some open source Java components/libraries are distributed as jar archives only containing the bytecode and some additional information. For whoever wanting to integrate this jar in her own project, it is important to determine the license(s) of the code from which the jar archive was produced, as this affects the way that such component can be used. This paper proposes an automatic approach to determine the license of jar archives, combining the use of a code-search engine with the automatic classification of licenses contained in textual flies enclosed in the jar. Results of an empirical study performed on 37 jars - from 17 different systems - indicate that this approach is able to successfully infer the jar licenses in over 95\% of the cases, but that in many cases the license in textual flies may differ from the one of the classes contained in the jar.},
	keywords = {apache, bytecode, classification, eclipse, google code, jar, java, licenses, source code},
	isbn = {978-1-4244-6802-7},
	doi = {10.1109/MSR.2010.5463282},
	attachments = {https://flosshub.org/sites/flosshub.org/files/151msr2010.pdf},
	author = {Di Penta, Massimiliano and Daniel M. German and Antoniol, Giuliano}
}
@conference {929,
	title = {Code siblings: Technical and legal implications of copying code between applications},
	booktitle = {2009 6th IEEE International Working Conference on Mining Software Repositories (MSR)2009 6th IEEE International Working Conference on Mining Software Repositories},
	year = {2009},
	pages = {81 - 90},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Vancouver, BC, Canada},
	abstract = {Source code cloning does not happen within a single system only. It can also occur between one system and another. We use the term code sibling to refer to a code clone that evolves in a different system than the code from which it originates. Code siblings can only occur when the source code copyright owner allows it and when the conditions imposed by such license are not incompatible with the license of the destination system. In some situations copying of source code fragments are allowed - legally - in one direction, but not in the other. In this paper, we use clone detection, license mining and classification, and change history techniques to understand how code siblings - under different licenses - flow in one direction or the other between Linux and two BSD Unixes, FreeBSD and OpenBSD. Our results show that, in most cases, this migration appears to happen according to the terms of the license of the original code being copied, favoring always copying from less restrictive licenses towards more restrictive ones. We also discovered that sometimes code is inserted to the kernels from an outside source.},
	keywords = {bsd, fossology, freebsd, linux, openbsd, source code},
	isbn = {978-1-4244-3493-0},
	doi = {10.1109/MSR.2009.5069483},
	attachments = {https://flosshub.org/sites/flosshub.org/files/81CodeSiblings.pdf},
	author = {Daniel M. German and Di Penta, Massimiliano and Gueheneuc, Yann-Gael and Antoniol, Giuliano}
}
@conference {Antoniol:2005:LPC:1083142.1083156,
	title = {Linear predictive coding and cepstrum coefficients for mining time variant information from software repositories},
	booktitle = {Proceedings of the 2005 international workshop on Mining software repositories},
	series = {MSR {\textquoteright}05},
	year = {2005},
	pages = {74-78},
	publisher = {ACM},
	organization = {ACM},
	address = {New York, NY, USA},
	abstract = {This paper presents an approach to recover time variant information from software repositories. It is widely accepted that software evolves due to factors such as defect removal, market opportunity or adding new features. Software evolution details are stored in software repositories which often contain the changes history. On the other hand there is a lack of approaches, technologies and methods to efficiently extract and represent time dependent information. Disciplines such as signal and image processing or speech recognition adopt frequency domain representations to mitigate differences of signals evolving in time. Inspired by time-frequency duality, this paper proposes the use of Linear Predictive Coding (LPC) and Cepstrum coefficients to model time varying software artifact histories. LPC or Cepstrum allow obtaining very compact representations with linear complexity. These representations can be used to highlight components and artifacts evolved in the same way or with very similar evolution patterns. To assess the proposed approach we applied LPC and Cepstral analysis to 211 Linux kernel releases (i.e., from 1.0 to 1.3.100), to identify files with very similar size histories. The approach, the preliminary results and the lesson learned are presented in this paper.},
	keywords = {change history, data mining, evolution, files, kernel, linear predictive coding, linux, lpc, size, software evolution, source code},
	isbn = {1-59593-123-6},
	doi = {http://doi.acm.org/10.1145/1082983.1083156},
	url = {http://doi.acm.org/10.1145/1082983.1083156},
	attachments = {https://flosshub.org/sites/flosshub.org/files/74LinearPredictive.pdf},
	author = {Antoniol, Giuliano and Rollo, Vincenzo Fabio and Venturi, Gabriele}
}
