Efficient Prior Publication Identification for Open Source Code - Equipe Autonomic and Critical Embedded Systems Access content directly
Conference Papers Year : 2022

Efficient Prior Publication Identification for Open Source Code


Free/Open Source Software (FOSS) enables large-scale reuse of preexisting software components. The main drawback is increased complexity in software supply chain management. A common approach to tame such complexity is automated open source compliance, which consists in automating the verication of adherence to various open source management best practices about license obligation fulllment, vulnerability tracking, software composition analysis, and nearby concerns. We consider the problem of auditing a source code base to determine which of its parts have been published before, which is an important building block of automated open source compliance toolchains. Indeed, if source code allegedly developed in house is recognized as having been previously published elsewhere, alerts should be raised to investigate where it comes from and whether this entails that additional obligations shall be fullled before product shipment. We propose an ecient approach for prior publication identication that relies on a knowledge base of known source code artifacts linked together in a global Merkle direct acyclic graph and a dedicated discovery protocol. We introduce swh-scanner, a source code scanner that realizes the proposed approach in practice using as knowledge base Software Heritage, the largest public archive of source code artifacts. We validate experimentally the proposed approach, showing its eciency in both abstract (number of queries) and concrete terms (wall-clock time), performing benchmarks on 16 845 real-world public code bases of various sizes, from small to very large.
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hal-03735961 , version 1 (21-07-2022)



Daniele Serafini, Stefano Zacchiroli. Efficient Prior Publication Identification for Open Source Code. 18th International Conference on Open Source Systems (OSS 2022), Sep 2022, Madrid, Spain. ⟨hal-03735961⟩
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