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Participatory Design in Digital Language Documentation: A Web Platform Approach
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Quality Assurance of Generative Dialog Models in an Evolving Conversational Agent Used for Swedish Language Practice ...
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SPT-Code: Sequence-to-Sequence Pre-Training for Learning Source Code Representations ...
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Software interactivo como herramienta de aprendizaje para niños con discapacidad auditiva en la U.E. "Especial Maturín", estado Monagas ...
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Software interactivo como herramienta de aprendizaje para niños con discapacidad auditiva en la U.E. "Especial Maturín", estado Monagas ...
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Eine agentenbasierte Architektur für Programmierung mit gesprochener Sprache ...
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Grenzüberschreitendes Textmining von Historischen Zeitungen - Das impresso-Projekt zwischen Text- und Bildverarbeitung, Design und Geschichtswissenschaft ...
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Grenzüberschreitendes Textmining von Historischen Zeitungen - Das impresso-Projekt zwischen Text- und Bildverarbeitung, Design und Geschichtswissenschaft ...
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PACSafe: Leveraging ARM Pointer Authentication for Memory Safety in C/C++ ...
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Quickstrom: Property Based Acceptance Testing with LTL Specifications ...
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POLYCRUISE: A Cross-Language Dynamic Information Flow Analysis ...
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POLYCRUISE: A Cross-Language Dynamic Information Flow Analysis ...
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MSCCD: Grammar Pluggable Clone Detection Based on ANTLR Parser Generation ...
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Abstract:
For various reasons, programming languages continue to multiply and evolve. It has become necessary to have a multilingual clone detection tool that can easily expand supported programming languages and detect various code clones is needed. However, research on multilingual code clone detection has not received sufficient attention. In this study, we propose MSCCD (Multilingual Syntactic Code Clone Detector), a grammar pluggable code clone detection tool that uses a parser generator to generate a code block extractor for the target language. The extractor then extracts the semantic code blocks from a parse tree. MSCCD can detect Type-3 clones at various granularities. We evaluated MSCCD's language extensibility by applying MSCCD to 20 modern languages. Sixteen languages were perfectly supported, and the remaining four were provided with the same detection capabilities at the expense of execution time. We evaluated MSCCD's recall by using BigCloneEval and conducted a manual experiment to evaluate precision. ... : ICPC2022 ...
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Keyword:
FOS Computer and information sciences; Software Engineering cs.SE
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URL: https://dx.doi.org/10.48550/arxiv.2204.01028 https://arxiv.org/abs/2204.01028
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Classification of Natural Language Processing Techniques for Requirements Engineering ...
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Conceptual Modeling of Events Based on One-Category Ontology ...
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Accelerating Code Search with Deep Hashing and Code Classification ...
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