A model-based approach to language integration

The interactions of several languages within a soft- ware system pose a number of problems. There is several anecdotal and empirical evidence supporting such concerns. This paper presents a solution to achieve proper language integration in the context of language workbenches and with limited effort. A simple example is presented to show how cross- language constraints can be addressed and the quality of the support attainable, which covers error-checking and refactoring. A research agenda is then presented, to support future work in the area of language integration, taking advantage of modern language workbenches features

Using schema transformation pathways for data lineage tracing

With the increasing amount and diversity of information available on the Internet, there has been a huge growth in information systems that need to integrate data from distributed, heterogeneous data sources. Tracing the lineage of the integrated data is one of the problems being addressed in data warehousing research. This paper presents a data lineage tracing approach based on schema transformation pathways. Our approach is not limited to one specific data model or query language, and would be useful in any data transformation/integration framework based on sequences of primitive schema transformations

A Quantum Many-body Wave Function Inspired Language Modeling Approach

The recently proposed quantum language model (QLM) aimed at a principled approach to modeling term dependency by applying the quantum probability theory. The latest development for a more effective QLM has adopted word embeddings as a kind of global dependency information and integrated the quantum-inspired idea in a neural network architecture. While these quantum-inspired LMs are theoretically more general and also practically effective, they have two major limitations. First, they have not taken into account the interaction among words with multiple meanings, which is common and important in understanding natural language text. Second, the integration of the quantum-inspired LM with the neural network was mainly for effective training of parameters, yet lacking a theoretical foundation accounting for such integration. To address these two issues, in this paper, we propose a Quantum Many-body Wave Function (QMWF) inspired language modeling approach. The QMWF inspired LM can adopt the tensor product to model the aforesaid interaction among words. It also enables us to reveal the inherent necessity of using Convolutional Neural Network (CNN) in QMWF language modeling. Furthermore, our approach delivers a simple algorithm to represent and match text/sentence pairs. Systematic evaluation shows the effectiveness of the proposed QMWF-LM algorithm, in comparison with the state of the art quantum-inspired LMs and a couple of CNN-based methods, on three typical Question Answering (QA) datasets.Comment: 10 pages,4 figures,CIK

Exploiting the ASM method within the Model-driven Engineering paradigm

Model-driven Engineering (MDE) is an emerging approach for software development. It uses metamodels to define language (or formalism) abstract notation, so separating the abstract syntax and semantics of the language from their different concrete notations. However, metamodelling frameworks lack of a way to specify the semantics of languages, which is usually given in natural language. We claim that the MDE paradigm can gain rigor and preciseness from the integration with formal approaches, and we propose the integration with the ASMs to define a unified methodology for metamodel-based language syntax and semantics definitions

A layered operational model for describing inter-tool communication in tool integration frameworks

Integration frameworks for building software engineering environments provide at least data, control and presentation integration facilities, together with integration devices which afford access to these facilities by the tools which populate the framework. Typically, an integration device is a specially developed language, or extension to an existing language, in which the integration programmer specifies the desired interactions between the tools comprising the software engineering environment. Surprisingly little effort has been applied to assessing the expressiveness of integration languages, even though the power of such a language limits the level of integration a tool can achieve within the environment. Our work seeks to provide an approach to both assessing and comparing the expressiveness of the integration devices of a range of commercial and research products. The paper presents a layered operational model, based on information structures; this model has been developed for describing the semantics of the inter-tool communication features of integration devices in a precise manner, and in a manner which will facilitate such assessment and comparison

A Language and Hardware Independent Approach to Quantum-Classical Computing

Heterogeneous high-performance computing (HPC) systems offer novel architectures which accelerate specific workloads through judicious use of specialized coprocessors. A promising architectural approach for future scientific computations is provided by heterogeneous HPC systems integrating quantum processing units (QPUs). To this end, we present XACC (eXtreme-scale ACCelerator) --- a programming model and software framework that enables quantum acceleration within standard or HPC software workflows. XACC follows a coprocessor machine model that is independent of the underlying quantum computing hardware, thereby enabling quantum programs to be defined and executed on a variety of QPUs types through a unified application programming interface. Moreover, XACC defines a polymorphic low-level intermediate representation, and an extensible compiler frontend that enables language independent quantum programming, thus promoting integration and interoperability across the quantum programming landscape. In this work we define the software architecture enabling our hardware and language independent approach, and demonstrate its usefulness across a range of quantum computing models through illustrative examples involving the compilation and execution of gate and annealing-based quantum programs