Related papers: Revisiting the Core Ontology and Problem in Requir…
Research must be reproducible in order to make an impact on science and to contribute to the body of knowledge in our field. Yet studies have shown that 70% of research from academic labs cannot be reproduced. In software engineering, and…
Research in applying natural language processing (NLP) techniques to requirements engineering (RE) tasks spans more than 40 years, from initial efforts carried out in the 1980s to more recent attempts with machine learning (ML) and deep…
Software requirements specification is undoubtedly critical for the whole software life-cycle. Nowadays, writing software requirements specifications primarily depends on human work. Although massive studies have been proposed to fasten the…
[Context and Motivation] Online user feedback provides valuable information to support requirements engineering (RE). However, analyzing online user feedback is challenging due to its large volume and noise. Large language models (LLMs)…
The main focus of the requirements engineering (RE) literature has been on the technical aspects related to the RE projects. Furthermore, research has mainly focused on the specific methods for collecting the requirements for an information…
Context: Requirements engineering process improvement (REPI) approaches have gained much attention in research and practice. Goal: So far, there is no comprehensive view on the research in REPI in terms of solutions and current state of…
In software engineering processes for machine learning (ML)-enabled systems, integrating and verifying ML components is a major challenge. A prerequisite is the specification of ML component requirements, including models and data, an area…
Legacy software systems typically include vital data for organizations that use them and should thus to be regularly maintained. Ideally, organizations should rely on Requirements Engineers to understand and manage changes of stakeholder…
Large language model agents demonstrate expert-level reasoning, yet consistently fail on enterprise-specific tasks due to missing domain knowledge -- terminology, operational procedures, system interdependencies, and institutional decisions…
Background: Nowadays, regulatory requirements engineering (regulatory RE) faces challenges of interdisciplinary nature that cannot be tackled due to existing research gaps. Aims: We envision an approach to solve some of the challenges…
We propose a novel framework to facilitate the on-demand design of data-centric systems by exploiting domain knowledge from an existing ontology. Its key ingredient is a process that we call focusing, which allows to obtain a schema for a…
[Context] Engineering Artificial Intelligence (AI) software is a relatively new area with many challenges, unknowns, and limited proven best practices. Big companies such as Google, Microsoft, and Apple have provided a suite of recent…
Requirements Engineering (RE) is a key activity in the development of software systems and is concerned with the identification of the goals of stakeholders and their elaboration into precise statements of desired services and behavior. The…
AI integration in automotive perception systems shifts requirements from static specifications to continuously evolving entities shaped by data, models, and operating contexts. When such changes are not consistently documented, validated,…
We address the issue of Ontology-Based Data Access, with ontologies represented in the framework of existential rules, also known as Datalog+/-. A well-known approach involves rewriting the query using ontological knowledge. We focus here…
Modern AI systems lack a way to express and enforce requirements. Pre-training produces intelligence, and post-training optimizes preferences, but neither guarantees that models reliably satisfy explicit, context-dependent constraints. This…
The requirements roadmap concept is introduced as a solution to the problem of the requirements engineering of adaptive systems. The concept requires a new general definition of the requirements problem which allows for quantitative…
Background: The sensitivity of Requirements Engineering (RE) to the context makes it difficult to efficiently control problems therein, thus, hampering an effective risk management devoted to allow for early corrective or even preventive…
Pre-Requirement Specification traceability is the activity of capturing relations between requirements and their sources, in particular user needs. Requirements are formal technical specifications in the solution space; needs are natural…
Requirement engineering (RE) is the first and the most important step in software production and development. The RE is aimed to specify software requirements. One of the tasks in RE is the categorization of software requirements as…