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Many researchers have explored ways to bring static typing to dynamic languages. However, to date, such systems are not precise enough when types depend on values, which often arises when using certain Ruby libraries. For example, the type…

In a high-tech country products are becoming rapidly more complex. To manage the development process as well as to encounter unforeseen challenges, the understanding and thus the explicit modeling of organizational workflows is more…

There is no dearth of new robots that provide both generalized and customized platforms for learning and research. Unfortunately as we attempt to adapt existing software components, we are faced with an explosion of device drivers that…

In this paper, we introduce ChainerRL, an open-source deep reinforcement learning (DRL) library built using Python and the Chainer deep learning framework. ChainerRL implements a comprehensive set of DRL algorithms and techniques drawn from…

Spoken Language Understanding infers semantic meaning directly from audio data, and thus promises to reduce error propagation and misunderstandings in end-user applications. However, publicly available SLU resources are limited. In this…

Nowadays, scripting programming languages like Python, Perl and Ruby are widely used in system programming, scientific computing, etc. Although solving a particular problem in these languages requires less time, less programming effort, and…

Large Language Models (LLMs) have shown increasing potential in automating model-driven software engineering tasks, particularly in generating models conforming to Domain Specific Languages (DSLs) from natural language. While most existing…

In this paper we present our work in progress towards a domain-specific language called Robot Perception Specification Language (RPSL). RSPL provide means to specify the expected result (task knowledge) of a Robot Perception Architecture in…

We present elsciRL, an open-source Python library to facilitate the application of language solutions on reinforcement learning problems. We demonstrate the potential of our software by extending the Language Adapter with Self-Completing…

Software maintenance is an important part of a software system's life cycle. Maintenance tasks of existing software systems suffer from architecture information that is diverging over time (architectural drift). The Digital Architecture…

As one of their many applications, large language models (LLMs) have recently shown promise in automating register transfer level (RTL) code generation. However, conventional LLM decoding strategies, originally designed for natural…

This paper presents some preliminary results concerning a new user-friendly operating system interface based on the relational data model that is currently under development at the University of Texas at Austin. The premise of our work is…

We present CrossTL, a universal programming language translator enabling bidirectional translation between multiple languages through a unified intermediate representation called CrossGL. Traditional approaches require separate translators…

Dynamic reconfiguration is the action of modifying a software system at runtime. Several works have been using architectural specification as the basis for dynamic reconfiguration. Indeed ADLs (architecture description languages) let…

The rapid integration of Multimodal Large Language Models (MLLMs) into critical applications is increasingly hindered by persistent safety vulnerabilities. However, existing red-teaming benchmarks are often fragmented, limited to…

Deep reinforcement learning (DRL) has recently emerged as a promising approach to solve combinatorial optimization problems such as job shop scheduling. However, the policies learned by DRL are typically represented by deep neural networks…

Transferring composite data structures with variable-length fields often requires designing non-trivial protocols that are not compatible between hardware designs. When each project designs its own data format and protocols the ability to…

This paper presents the development and evaluation of ChatHome, a domain-specific language model (DSLM) designed for the intricate field of home renovation. Considering the proven competencies of large language models (LLMs) like GPT-4 and…

The automatic generation of RTL code (e.g., Verilog) using natural language instructions and large language models (LLMs) has attracted significant research interest recently. However, most existing approaches heavily rely on commercial…

Visualization is central to scientific discovery, yet authoring tools remain split between information and scientific visualization, and expertise in one rarely transfers to the other. Large Language Model (LLM) based systems promise to…