Related papers: Teaching Model-based Requirements Engineering to I…
The crafting of machine learning (ML) based systems requires statistical control throughout its life cycle. Careful quantification of business requirements and identification of key factors that impact the business requirements reduces the…
Background: Software modelling is a creative yet challenging task. Modellers often find themselves lost in the process, from understanding the modelling problem to solving it with proper modelling strategies and modelling tools. Students…
This article provides an overview of the importance of requirements gathering in secure software development. It explains the crucial role of Requirements Engineers in defining and understanding the customer's needs and desires, as well as…
The term Model-Driven Engineering (MDE) is typically used to describe software development approaches in which abstract models of software systems are created and systematically transformed to concrete implementations. In this paper we give…
In this position paper we propose a process model that provides a development infrastructure in which the usability engineering and software engineering life cycles co-exist in complementary roles. We describe the motivation, hurdles,…
Digital engineering practices offer significant yet underutilized potential for improving information assurance and system lifecycle management. This paper examines how capabilities like model-based engineering, digital threads, and…
Simulations offer opportunities in the examination of manufacturing processes. They represent various aspects of the production process and the associated production systems. However, often a single simulation does not suffice to provide a…
The literature on machine teaching, machine education, and curriculum design for machines is in its infancy with sparse papers on the topic primarily focusing on data and model engineering factors to improve machine learning. In this paper,…
Often during the requirements engineering (RE) process, the value of a requirement is assessed, e.g., in requirement prioritisation, release planning, and trade-off analysis. In order to support these activities, this research evaluates…
As any scientific discipline, the software engineering (SE) research community strives to contribute to the betterment of the target population of our research: software producers and consumers. We will only achieve this betterment if we…
It is a conundrum that agile projects can succeed 'without requirements' when weak requirements engineering is a known cause for project failures. While Agile development projects often manage well without extensive requirements…
As the shortage of skilled workers continues to be a pressing issue, exacerbated by demographic change, it is becoming a critical challenge for organizations to preserve the knowledge of retiring experts and to pass it on to novices. While…
When environmental interaction is expensive, model-based reinforcement learning offers a solution by planning ahead and avoiding costly mistakes. Model-based agents typically learn a single-step transition model. In this paper, we propose a…
One goal of applied operations research is to improve decisions in practice. This requires modelers and stakeholders to have a shared understanding of the system and for the developed model to reflect the system's core dynamics. There are…
Recommender systems aim to provide item recommendations for users, and are usually faced with data sparsity problem (e.g., cold start) in real-world scenarios. Recently pre-trained models have shown their effectiveness in knowledge transfer…
Empirical software engineering has received much attention in recent years and coined the shift from a more design-science-driven engineering discipline to an insight-oriented, and theory-centric one. Yet, we still face many challenges,…
Many of the requirements engineering (RE) difficulties have been argued to be due to the evolving nature of design problems in dynamic environments, characterized by high levels of uncertainty, ambiguity and emergence. It has also been…
Requirements Elicitation (RE) is a crucial software engineering skill that involves interviewing a client and then devising a software design based on the interview results. Teaching this inherently experiential skill effectively has high…
In this practice paper, we propose a framework for integrating AI into disciplinary engineering courses and curricula. The use of AI within engineering is an emerging but growing area and the knowledge, skills, and abilities (KSAs)…
Machine learning (ML) teams often work on a project just to realize the performance of the model is not good enough. Indeed, the success of ML-enabled systems involves aligning data with business problems, translating them into ML tasks,…