Related papers: Application Software, Domain-Specific Languages, a…
Software requirement analysis can certainly benefit from prevention and early detection of failures, in particular by some kind of automatic analysis. Formal methods offer means to represent and analyze requirements with rigorous tools,…
The world of HPC systems is changing to a more complicated system because the performance improvement of processors has been slowed down. One of the promising approaches is Domain-Specific Language(DSL), which provides a productive…
The use of Domain-Specific Languages (DSLs) is a promising field for the development of tools tailored to specific problem spaces, effectively diminishing the complexity of hand-made software. With the goal of making models as precise,…
This paper presents a Domain Specific Language (DSL) for generically describing cyber attacks, agnostic to specific system-under-test(SUT). The creation of the presented DSL is motivated by an automotive use case. The concepts of the DSL…
Large language models (LLMs) have significantly advanced the field of natural language processing (NLP), providing a highly useful, task-agnostic foundation for a wide range of applications. However, directly applying LLMs to solve…
Language-oriented modularity (LOM) is a methodology that complements language-oriented programming (LOP) in providing on-demand language abstraction solutions during software development. It involves the implementation and immediate…
There is a gap between our ability to reuse high-level concepts in software design and our ability to reuse the code implementing them. Language Oriented Programming (LOP) is a software development paradigm that aims to close this gap,…
Empirical software engineering research often depends on datasets of code repository artifacts, where sampling strategies are employed to enable large-scale analyses. The design and evaluation of these strategies are critical, as they…
Quality requirements typically differ among software features, e.g., due to different usage contexts of the features, different impacts of related quality deficiencies onto overall user satisfaction, or long-term plans of the developing…
We present MathDSL, a Domain-Specific Language (DSL) for mathematical equation solving, which, when deployed in program synthesis models, outperforms state-of-the-art reinforcement-learning-based methods. We also introduce a quantitative…
Traditional Digital Signal Processing ( DSP ) compilers work at low level ( C-level / assembly level ) and hence lose much of the optimization opportunities present at high-level ( domain-level ). The emerging multi-level compiler…
We present DAPIP, a Programming-By-Example system that learns to program with APIs to perform data transformation tasks. We design a domain-specific language (DSL) that allows for arbitrary concatenations of API outputs and constant…
Since the early days of the Web, web application developers have aspired to develop much of their applications declaratively. However, one aspect of the application, namely its business-logic is constantly left imperative. In this work we…
In the realm of software applications in the transportation industry, Domain-Specific Languages (DSLs) have enjoyed widespread adoption due to their ease of use and various other benefits. With the ceaseless progress in computer performance…
Domain Specific Languages (DSLs) increase programmer productivity and provide high performance. Their targeted abstractions allow scientists to express problems at a high level, providing rich details that optimizing compilers can exploit…
This paper addresses the problem of specifying and parsing the syntax of domain-specific languages (DSLs) in a modular, user-friendly way. That is, we want to enable the design of composable DSLs that combine the natural syntax of external…
Domain specific languages (DSL) have been used in a variety of fields to express complex scientific problems in a concise manner and provide automated performance optimization for a range of computational architectures. As such DSLs provide…
Numerical software in computational science and engineering often relies on highly-optimized building blocks from libraries such as BLAS and LAPACK, and while such libraries provide portable performance for a wide range of computing…
We present Semantic Interpreter, a natural language-friendly AI system for productivity software such as Microsoft Office that leverages large language models (LLMs) to execute user intent across application features. While LLMs are…
We address the need for expanding the presence of the Lisp family of programming languages in bioinformatics and computational biology research. Languages of this family, like Common Lisp, Scheme, or Clojure, facilitate the creation of…