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논문 기본 정보

자료유형
학술저널
저자정보
Sanghoon Lee (Pohang University of Science and Technology) Daniel M. German (University of Victoria) Seung-won Hwang (Yonsei University) Sunghun Kim (홍콩과기대학)
저널정보
Korean Institute of Information Scientists and Engineers Journal of Computing Science and Engineering Journal of Computing Science and Engineering Vol.9 No.4
발행연도
2015.12
수록면
190 - 203 (14page)

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초록· 키워드

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Free and open source software (FOSS) has created a large pool of source codes that can be easily copied to create new applications. However, a copy should preserve copyright notice and license of the original file unless the license explicitly permits such a change. Through software evolution, it is challenging to keep original licenses or choose proper licenses. As a result, there are many potential license violations. Despite the fact that violations can have high impact on protecting copyright, identification of violations is highly complex. It relies on manual inspections by experts. However, such inspection cannot be scaled up with open source software released daily worldwide. To make this process scalable, we propose the following two methods: use machine-based algorithms to narrow down the potential violations; and guide non-experts to manually inspect violations. Using the first method, we found 219 projects (76.6%) with potential violations. Using the second method, we show that the accuracy of crowds is comparable to that of experts. Our techniques might help developers identify potential violations, understand the causes, and resolve these violations.

목차

Abstract
I. INTRODUCTION
II. OVERVIEW
III. MACHINE IDENTIFICATION OF POTENTIAL LICENSE VIOLATIONS
IV. EVALUATION OF MACHINE-BASED APPROACHES
V. CROWDSOURCING FOR FINAL DECISION
VI. RELATED WORK
VII. CONCLUSIONS
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UCI(KEPA) : I410-ECN-0101-2016-569-002298207