Related papers: Using SEQUAL for Identifying Requirements to Ecore…
Rigorous and reproducible evaluation is critical for assessing the state of the art and for guiding scientific advances in Artificial Intelligence. Evaluation is challenging in practice due to several reasons, including benchmark…
When engineering complex and distributed software and hardware systems (increasingly used in many sectors, such as manufacturing, aerospace, transportation, communication, energy, and health-care), quality has become a big issue, since…
Context: Systematic literature reviews (SLRs) have become standard practise as part of software engineering research, although their quality varies. To build on the reviews, both for future research and industry practice, they need to be of…
When the IceCube experiment started serious software development it needed a development environment in which both its developers and clients could work and that would encourage and support a good software development process. Some of the…
Machine Learning for Software Engineering (ML4SE) is an actively growing research area that focuses on methods that help programmers in their work. In order to apply the developed methods in practice, they need to achieve reasonable quality…
Requirements are key artefacts to describe the intended purpose of a software system. The quality of requirements is crucial for deciding what to do next, impacting the development process's effectiveness and efficiency. However, we know…
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 growing reliance on automated code completion tools in software development, the need for comprehensive evaluation benchmarks has become critical. Existing benchmarks focus more on code completion in function and class level by…
Ethnomethodological fieldwork has long been acknowledged as a potentially valuable way of informing the design of technology. However, there is relatively little methodological support for this activity, particularly in relation to the…
Normative requirements specify social, legal, ethical, empathetic, and cultural (SLEEC) norms that must be observed by a system. To support the identification of SLEEC requirements, numerous standards and regulations have been developed.…
We present a prototype of a tool leveraging the synergy of model driven engineering (MDE) and Large Language Models (LLM) for the purpose of software development process automation in the automotive industry. In this approach, the…
Verification activities are necessary to ensure that the requirements are specified in a correct way. However, until now requirements verification research has focused on traditional up-front requirements. Agile or just-in-time requirements…
Empirical and LLM-based research in model-driven engineering increasingly relies on datasets of software models, for instance, to train or evaluate machine learning techniques for modeling support. These datasets have a significant impact…
Assessing and improving the quality of data in data-intensive systems are fundamental challenges that have given rise to numerous applications targeting transformation and cleaning of data. However, while schema design, data cleaning, and…
The objective of this research work is to improve the degree of excellence by removing the number of exceptions from the software. The modern age is more concerned with the quality of software. Extensive research is being carried out in…
Optimizing the quality of software is a function of the degree of reviews made during the early life of a software development process. Reviews detect errors and potential errors early in the software development process. The errors…
The rapid evolution of Large Language Models' has underscored the need for evaluation frameworks that are globally applicable, flexible, and modular, and that support a wide range of tasks, model types, and linguistic settings. We introduce…
In text generation evaluation, many practical issues, such as inconsistent experimental settings and metric implementations, are often ignored but lead to unfair evaluation and untenable conclusions. We present CoTK, an open-source toolkit…
Context: Mining software repositories is a popular means to gain insights into a software project's evolution, monitor project health, support decisions and derive best practices. Tools supporting the mining process are commonly applied by…
Despite potential benefits in Software Engineering (SE), adoption of software modelling in industry is low. Technical issues such as tool support have gained significant research before, but individual guidance and training have received…