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This paper presents a new language called APSL for formally describing protocols to facilitate automated testing. Many real world communication protocols exchange messages whose structures are not trivial, e.g. they may consist of multiple…
The use of artificial intelligence (AI) to support creative writing has bloomed in recent years. However, it is less well understood how AI compares to on-demand human support. We explored how writers interact with both AI and crowd worker…
Modern hardware platforms, from the very small to the very large, increasingly provide parallel and distributed computing resources for applications to maximise performance. Many applications therefore need to make effective use of tens,…
We review the scholarly contributions that utilise Natural Language Processing (NLP) techniques to support the design process. Using a heuristic approach, we gathered 223 articles that are published in 32 journals within the period…
The advent of increasingly powerful language models has raised expectations for language-based interactions. However, controlling these models is a challenge, emphasizing the need to be able to investigate the feasibility and value of their…
Automation services for complex business processes usually require a high level of information technology literacy. There is a strong demand for a smartly assisted process automation (IPA: intelligent process automation) service that…
Over the past decade, the automated generation of test inputs has made significant advances. Modern fuzzers and test generators easily produce complex input formats that do systematically cover the input and execution space. Testing…
Progress on many Natural Language Processing (NLP) tasks, such as text classification, is driven by objective, reproducible and scalable evaluation via publicly available benchmarks. However, these are not always representative of…
Cross-lingual knowledge transfer, especially between high- and low-resource languages, remains challenging in natural language processing (NLP). This study offers insights for improving cross-lingual NLP applications through the combination…
The main contribution of this paper, is to propose a novel semantic approach based on a Natural Language Processing technique in order to ensure a semantic unification of unstructured process patterns which are expressed not only in…
Blended modeling is an emerging paradigm involving seamless interaction between multiple notations for the same underlying modeling language. We focus on a model-driven engineering (MDE) approach based on meta-models to develop textual…
Answer Set Programming (ASP) is a declarative programming language used for modeling and solving complex combinatorial problems. It has been successfully applied to a number of different realworld problems. However, learning its usage can…
While state-of-the-art Text-to-Speech systems can generate natural speech of very high quality at sentence level, they still meet great challenges in speech generation for paragraph / long-form reading. Such deficiencies are due to i)…
The recent advancement in Natural Language Processing (NLP) capability has led to the development of language models (e.g., ChatGPT) that is capable of generating human-like language. In this study, we explore how language models can be…
We investigate how non-native English speakers (NNESs) interact with diverse information aids to assess and select AI-generated paraphrases. We develop ParaScope, an AI paraphrasing assistant that integrates diverse information aids, such…
To design peer-to-peer (P2P) software systems is a challenging task, because of their highly decentralized nature, which may cause unexpected emergent global behaviors. The last fifteen years have seen many P2P applications to come out and…
Automatic speech recognition enables a wide range of current and emerging applications such as automatic transcription, multimedia content analysis, and natural human-computer interfaces. This paper provides a glimpse of the opportunities…
Recent years have seen a number of proposals for performing Natural Language Generation (NLG) based in large part on statistical techniques. Despite having many attractive features, we argue that these existing approaches nonetheless have…
Software developers often rely on natural language text that appears in software engineering artifacts to access critical information as they build and work on software systems. For example, developers access requirements documents to…
The increasing demand for programmers has led to a surge in participants in programming courses, making it increasingly challenging for instructors to assess student code manually. As a result, automated programming assessment systems…