Roberto Di Cosmo

Petr Knoth, Laurent Romary, Patrice Lopez et al.

A key issue hindering discoverability, attribution and reusability of open research software is that its existence often remains hidden within the manuscript of research papers. For these resources to become first-class bibliographic records, they first need to be identified and subsequently registered with persistent identifiers (PIDs) to be made FAIR (Findable, Accessible, Interoperable and Reusable). To this day, much open research software fails to meet FAIR principles and software resources are mostly not explicitly linked from the manuscripts that introduced them or used them. SoFAIR is a 2-year international project (2024-2025) which proposes a solution to the above problem realised over the content available through the global network of open repositories. SoFAIR will extend the capabilities of widely used open scholarly infrastructures (CORE, Software Heritage, HAL) and tools (GROBID) operated by the consortium partners, delivering and deploying an effective solution for the management of the research software lifecycle, including: 1) ML-assisted identification of research software assets from within the manuscripts of scholarly papers, 2) validation of the identified assets by authors, 3) registration of software assets with PIDs and their archival.

Guillaume Rousseau, Roberto Di Cosmo, Stefano Zacchiroli

We study the evolution of the largest known corpus of publicly available source code, i.e., the Software Heritage archive (4B unique source code files, 1B commits capturing their development histories across 50M software projects). On such corpus we quantify the growth rate of original, never-seen-before source code files and commits. We find the growth rates to be exponential over a period of more than 40 years.We then estimate the multiplication factor, i.e., how much the same artifacts (e.g., files or commits) appear in different contexts (e.g., commits or source code distribution places). We observe a combinatorial explosion in the multiplication of identical source code files across different commits.We discuss the implication of these findings for the problem of tracking the provenance of source code artifacts (e.g., where and when a given source code file or commit has been observed in the wild) for the entire body of publicly available source code. To that end we benchmark different data models for capturing software provenance information at this scale and growth rate. We identify a viable solution that is deployable on commodity hardware and appears to be maintainable for the foreseeable future.