作者:
Gupta, GopalPontelli, EnricoApplied Logic
Programming Languages and Systems Lab. Department of Computer Science University of Texas at Dallas Richardson TX 95083 United States Laboratory for Logic
Databases and Advanced Programming Department of Computer Science New Mexico State University Las Cruces NM 88003 United States
Domain Specific Languages (DSLs) are high level languages designed for solving problems in a particular domain, and have been suggested as means for developing reliable software systems. We present a (constraint) logi...
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Domain experts think and reason at a high level of abstraction when they solve problems in their domain of expertise. We present the design and motivation behind a domain specific language, called phi LOG, to enable b...
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Domain experts think and reason at a high level of abstraction when they solve problems in their domain of expertise. We present the design and motivation behind a domain specific language, called phi LOG, to enable biologists to program solutions to phylogenetic inference problems at a very high level of abstraction. The implementation infrastructure (interpreter, compiler, debugger) for the DSL is automatically obtained through a software engineering framework based on Denotational Semantics and Logic programming.
The process of extracting meaningful rules from big and complex data is called data mining. Data mining has an increasing popularity in every field today. Data units are established in customer-oriented industries suc...
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programming autonomic systems with massive number of heterogeneous components poses a number of challenges to language designers and software engineers and requires the integration of computational tools and reasoning...
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HW/SW Co-designed systems rely on dynamic binary translation and optimizations for efficient execution of binary code. Due to memory ordering properties and other architectural constraints, most binary optimizations a...
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Text style transfer aims to paraphrase a sentence in one style into another style while preserving content. Due to lack of parallel training data, state-of-art methods are unsupervised and rely on large datasets that ...
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The chase of datalog programs is anew way to reason about datalog programs that are evaluated on databases consistent with a set of constraints. It is an equivalence-preserving program transformation that uncovers pro...
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We present a novel optimization called Last Parallel Call Optimization (LPCO) for parallel systems. The last parallel call optimization can be regarded as a parallel extension of last call optimization found in sequen...
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We present a novel optimization called Last Parallel Call Optimization (LPCO) for parallel systems. The last parallel call optimization can be regarded as a parallel extension of last call optimization found in sequential systems. While the LPCO is fairly general, we use and-parallel logic programming systems to illustrate it and to report its performance on multiprocessor systems. The last parallel call optimization leads to improved time and space performance for a majority of and-parallel programs. We also present a generalization of the Last Parallel Call Optimization called Nested Parallel Call Optimization (NPCO). A major advantage of LPCO and NPCO is that parallel systems designed for exploiting control parallelism can automatically exploit data parallelism efficiently.
The purpose of this article is to examine the role an expert system can play as an intelligent job aid. The use of expert system shells for microcomputers is discussed. We argue that instructional designers, with thei...
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