Related papers: Semi-Automatic Extraction of Formal Models from Ob…

Model-driven engineering is the automatic production of software artefacts from abstract models of structure and functionality. By targeting a specific class of system, it is possible to automate aspects of the development process, using…

With the advancements in open-source models, training (or finetuning) models on custom datasets has become a crucial part of developing solutions which are tailored to specific industrial or open-source applications. Yet, there is no single…

Significant advancements have been made in the capabilities of code large language models, leading to their rapid adoption and application across a wide range of domains. However, their further advancements are often constrained by the…

Model-based verification allows to express behavioral correctness conditions like the validity of execution states, boundaries of variables or timing at a high level of abstraction and affirm that they are satisfied by a software system.…

Developing techniques for editing an outfit image through natural sentences and accordingly generating new outfits has promising applications for art, fashion and design. However, it is considered as a certainly challenging task since image…

Multi-agent systems, where multiple agents (generative AI models + tools) collaborate, are emerging as an effective pattern for solving long-running, complex tasks in numerous domains. However, specifying their parameters (such as models,…

Language Models (LLMs), such as transformer-based neural networks trained on billions of parameters, have become increasingly prevalent in software engineering (SE). These models, trained on extensive datasets that include code…

Static program slicing is a fundamental technique in software engineering. Traditional static slicing tools rely on parsing complete source code, which limits their applicability to real-world scenarios where code snippets are incomplete or…

[Context:] Model-based testing is an instrument for automated generation of test cases. It requires identifying requirements in documents, understanding them syntactically and semantically, and then translating them into a test model. One…

Creative processes such as painting often involve creating different components of an image one by one. Can we build a computational model to perform this task? Prior works often fail by making global changes to the image, inserting objects…

Formal program specifications play a crucial role in various stages of software development. However, manually crafting formal program specifications is rather difficult, making the job time-consuming and labor-intensive. It is even more…

The extraction of process models from text refers to the problem of turning the information contained in an unstructured textual process descriptions into a formal representation,i.e.,a process model. Several automated approaches have been…

The advancement of LLM agents with tool-use capabilities requires diverse and complex training corpora. Existing data generation methods, which predominantly follow a paradigm of random sampling and shallow generation, often yield simple…

Automatic code transformation in which transformations are tuned for specific applications and contexts are difficult to achieve in an accessible manner. In this paper, we present an approach to build application specific code…

Extracting information from documents usually relies on natural language processing methods working on one-dimensional sequences of text. In some cases, for example, for the extraction of key information from semi-structured documents, such…

Static program slicing is a fundamental software engineering technique for isolating code relevant to specific variables. While recent learning-based approaches using language models (LMs) show promise in automating slice prediction, they…

In model-driven engineering, models abstract the relevant features of software artefacts and model transformations act on them automating complex tasks of the development process. It is, thus, crucially important to provide pragmatic,…

In this paper, we present a static code analysis strategy to extract logical schemas from NoSQL applications. Our solution is based on a model-driven reverse engineering process composed of a chain of platform-independent model…

Extracting dense representations for terms and phrases is a task of great importance for knowledge discovery platforms targeting highly-technical fields. Dense representations are used as features for downstream components and have multiple…

Automatic generation of software code from system design models remains an actively explored research area for the past several years. A number of tools are currently available to facilitate and automate the task of generating code from…