183 research outputs found

    PreciseBugCollector: Extensible, Executable and Precise Bug-fix Collection

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    Bug datasets are vital for enabling deep learning techniques to address software maintenance tasks related to bugs. However, existing bug datasets suffer from precise and scale limitations: they are either small-scale but precise with manual validation or large-scale but imprecise with simple commit message processing. In this paper, we introduce PreciseBugCollector, a precise, multi-language bug collection approach that overcomes these two limitations. PreciseBugCollector is based on two novel components: a) A bug tracker to map the codebase repositories with external bug repositories to trace bug type information, and b) A bug injector to generate project-specific bugs by injecting noise into the correct codebases and then executing them against their test suites to obtain test failure messages. We implement PreciseBugCollector against three sources: 1) A bug tracker that links to the national vulnerability data set (NVD) to collect general-wise vulnerabilities, 2) A bug tracker that links to OSS-Fuzz to collect general-wise bugs, and 3) A bug injector based on 16 injection rules to generate project-wise bugs. To date, PreciseBugCollector comprises 1057818 bugs extracted from 2968 open-source projects. Of these, 12602 bugs are sourced from bug repositories (NVD and OSS-Fuzz), while the remaining 1045216 project-specific bugs are generated by the bug injector. Considering the challenge objectives, we argue that a bug injection approach is highly valuable for the industrial setting, since project-specific bugs align with domain knowledge, share the same codebase, and adhere to the coding style employed in industrial projects.Comment: Accepted at the industry challenge track of ASE 202

    1997 Research Reports: NASA/ASEE Summer Faculty Fellowship Program

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    This document is a collection of technical reports on research conducted by the participants in the 1997 NASA/ASEE Summer Faculty Fellowship Program at the Kennedy Space Center (KSC). This was the 13th year that a NASA/ASEE program has been conducted at KSC. The 1997 program was administered by the University of Central Florida in cooperation with KSC. The program was operated under the auspices of the American Society for Engineering Education (ASEE) with sponsorship and funding from the Education Division, NASA Headquarters, Washington, D.C., and KSC. The KSC Program was one of nine such Aeronautics and Space Research Programs funded by NASA in 1997. The NASA/ASEE Program is intended to be a two-year program to allow in-depth research by the university faculty member. The editors of this document were responsible for selecting appropriately qualified faculty to address some of the many problems of current interest to NASA/KSC

    Software Engineering 2021 : Fachtagung vom 22.-26. Februar 2021 Braunschweig/virtuell

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    Jiko kaifukugata operetingu shisutemu kochiku furemu waku

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    制度:新 ; 報告番号:甲2786号 ; 学位の種類:博士(工学) ; 授与年月日:2009/2/25 ; 早大学位記番号:新500
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