منابع مشابه
Semantic Essence of AsmL
The Abstract State Machine Language, AsmL, is a novel executable specification language based on the theory of Abstract State Machines. AsmL is object-oriented, provides high-level mathematical data-structures, and is built around the notion of synchronous updates and finite choice. AsmL is fully integrated into the .NET framework and Microsoft development tools. In this paper, we explain the d...
متن کاملSemantic Essence of AsmL: Extended Abstract
The Abstract State Machine Language, AsmL, is a novel executable specification language based on the theory of Abstract State Machines. AsmL is object-oriented, provides high-level mathematical data-structures, and is built around the notion of synchronous updates and finite choice. AsmL is fully integrated into the .NET framework and Microsoft development tools. In this paper, we explain the d...
متن کاملThe Essence of Functional Programming on Semantic Data
Programming with knowledge represented in description logics (DL) is errorprone. Untyped access, e.g., provided by the OWL API [1], does not leverage static typing which allows for proving the absence of runtime-errors. Mapping approaches, e.g., described by [2] cannot fully capture the conceptualization of semantic data. In [3], we present λDL, a typed λ-calculus with constructs for operating ...
متن کاملEmbedding and Verification of PSL using AsmL
In this paper, we propose a methodology to integrate the Property Specification Language (PSL) in the verification process of systems designed using Abstract States Machines (ASMs). We provide a complete embedding of PSL in the ASM language AsmL, which allows us to integrate PSL properties as part of the design. For the verification, we propose a technique based on the AsmL tool that translates...
متن کاملASML: Automatic Streaming Machine Learning
Beyond the well-studied problem of scale in Big Data systems, the high velocity at which new data is generated and moved around introduces new challenges. It becomes critical to build systems that can process high speed data efficiently in order to extract useful insights, having access to Big Data is not good unless you can turn it into value. As opposed to typical offline/batch machine learni...
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ژورنال
عنوان ژورنال: Theoretical Computer Science
سال: 2005
ISSN: 0304-3975
DOI: 10.1016/j.tcs.2005.06.017