Illinois Digital Scholarship: Preserving and Accessing the Digital Past, Present, and Future

Since the University's establishment in 1867, its scholarly output has been issued primarily in print, and the University Library and Archives have been readily able to collect, preserve, and to provide access to that output. Today, technological, economic, political and social forces are buffeting all means of scholarly communication. Scholars, academic institutions and publishers are engaged in debate about the impact of digital scholarship and open access publishing on the promotion and tenure process. The upsurge in digital scholarship affects many aspects of the academic enterprise, including how we record, evaluate, preserve, organize and disseminate scholarly work. The result has left the Library with no ready means by which to archive digitally produced publications, reports, presentations, and learning objects, much of which cannot be adequately represented in print form. In this incredibly fluid environment of digital scholarship, the critical question of how we will collect, preserve, and manage access to this important part of the University scholarly record demands a rational and forward-looking plan - one that includes perspectives from diverse scholarly disciplines, incorporates significant research breakthroughs in information science and computer science, and makes effective projections for future integration within the Library and computing services as a part of the campus infrastructure.Prepared jointly by the University of Illinois Library and CITES at the University of Illinois at Urbana-Champaig

Source File Set Search for Clone-and-Own Reuse Analysis

Clone-and-own approach is a natural way of source code reuse for software developers. To assess how known bugs and security vulnerabilities of a cloned component affect an application, developers and security analysts need to identify an original version of the component and understand how the cloned component is different from the original one. Although developers may record the original version information in a version control system and/or directory names, such information is often either unavailable or incomplete. In this research, we propose a code search method that takes as input a set of source files and extracts all the components including similar files from a software ecosystem (i.e., a collection of existing versions of software packages). Our method employs an efficient file similarity computation using b-bit minwise hashing technique. We use an aggregated file similarity for ranking components. To evaluate the effectiveness of this tool, we analyzed 75 cloned components in Firefox and Android source code. The tool took about two hours to report the original components from 10 million files in Debian GNU/Linux packages. Recall of the top-five components in the extracted lists is 0.907, while recall of a baseline using SHA-1 file hash is 0.773, according to the ground truth recorded in the source code repositories.Comment: 14th International Conference on Mining Software Repositorie