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CASM 2020 : ACM SAC track on Code Analysis and Software Mining | |||||||||||||||
Link: https://sites.google.com/view/acmcasm | |||||||||||||||
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Call For Papers | |||||||||||||||
Submission Extended to 29th September
The objective of CASM track is to provide researchers and software developers the opportunity to present their observations, experiences, and research in the area of code analysis and software mining. The aim is to provide this novel topic to ACM SAC, which is not currently sufficiently covered. The area is broad, covering code transformation, static and dynamic code analysis, bytecode analysis, user interface derivation, automated test extraction, quality assurance, clone detection, inconsistency detection, security reviews, API dependency mining, control-flow modeling and reconstruction, software repository mining with many others. The outcomes of research in this area is expected to report on the best practices, state of the art, production level experience, impact on the development, design, maintenance, sustainability, security and other software quality attributes. Topics: * Static and dynamic code analysis * Bytecode analysis and metaprogramming * Code to code and code to model transformations * Software mining, code inspection, and information extraction * Software verification and code checking * API dependency mining * Automated derivations and code transformations * Security audit and compliance * Inconsistency and clone detection * Software project repository mining (git, svn..) * Analysis of code and development process (Jira, Bugizilla..) * Control-flow modeling and reconstruction * Reverse engineering * Process and system monitoring * Distributed aspect-oriented programming * Test automation, test coverage verification & quality assurance * Documentation extraction * others.. ACM SAC proceedings and published in the ACM digital library, being indexed by Thomson ISI Web of Knowledge and Scopus. Best accepted papers to be invited to Scientific Programming Journal special issue on Code Analysis and Software Mining in Scientific and Engineering Applications (IF 1.289, CiteScore 1.3) |
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