Related papers: An Exploratory Study of Applying a Scrum Developme…
In response to the escalating need for sustainable manufacturing, this study introduces a Simulation-Based Approach (SBA) to model a stopping policy for energy-intensive stochastic production systems, developed and tested in a real-world…
With the increasing reliance on software and automation nowadays, tight deadlines, limited resources, and prioritization of functionality over security can lead to insecure coding practices. When not handled properly, these constraints…
In recent years, the number of cyber attacks has grown rapidly. An effective way to reduce the attack surface and protect software is adoption of methodologies that apply security at each step of the software development lifecycle. While…
When developing a safety-critical system it is essential to obtain an assessment of different design alternatives. In particular, an early safety assessment of the architectural design of a system is desirable. In spite of the plethora of…
Background: Accurate effort estimation is crucial for planning in Agile iterative development. Agile estimation generally relies on consensus-based methods like planning poker, which require less time and information than other formal…
In recent years, technology has advanced considerably with the introduction of many systems including advanced robotics, big data analytics, cloud computing, machine learning and many more. The opportunities to exploit the yet to come…
Context: Agile development methodologies in the software industry have increased significantly over the past decade. Although one of the main aspects of agile software development (ASD) is less documentation, there have always been…
Modern software systems undergo frequent updates, continuously evolving with new versions and variants to offer new features, improve functionality, and expand usability. Given the rapid pace of software evolution, organizations require…
Autonomous driving has made significant progress in both academia and industry, including performance improvements in perception task and the development of end-to-end autonomous driving systems. However, the safety and robustness…
As the complexity of control systems increases, the need for systematic methods to guarantee their efficacy grows as well. However, direct testing of these systems is oftentimes costly, difficult, or impractical. As a result, the test and…
Context/Background: process and practice adoption is a key element in modern software process improvement initiatives, and many of them fail. Goal: this paper presents a preliminary version of a usability model for software development…
Prompt engineering is pivotal for harnessing the capabilities of large language models (LLMs) across diverse applications. While existing prompt optimization methods improve prompt effectiveness, they often lead to prompt drifting, where…
In the early 90s, researchers began to focus on security as an important property to address in combination with safety. Over the years, researchers have proposed approaches to harmonize activities within the safety and security…
Satisfactory software performance is essential for the adoption and the success of a product. In organizations that follow traditional software development models (e.g., waterfall), Software Performance Engineering (SPE) involves…
Autonomous cyber-physical systems (CPS) can improve safety and efficiency for safety-critical applications, but require rigorous testing before deployment. The complexity of these systems often precludes the use of formal verification and…
Modern computer systems need to execute under strict safety constraints (e.g., a power limit), but doing so often conflicts with their ability to deliver high performance (i.e. minimal latency). Prior work uses machine learning to…
This research considers the problem of identifying safety constraints and developing Run Time Assurance (RTA) for Deep Reinforcement Learning (RL) Tactical Autopilots that use neural network control systems (NNCS). This research studies a…
Self-adaptive software systems (SASS) are equipped with feedback loops to adapt autonomously to changes of the software or environment. In established fields, such as embedded software, sophisticated approaches have been developed to…
With the growing interest in deploying robots in unstructured and uncertain environments, there has been increasing interest in factoring risk into safety-critical control development. Similarly, the authors believe risk should also be…
This action research study focuses on the integration of "AI assistants" in two Agile software development meetings: the Daily Scrum and a feature refinement, a planning meeting that is part of an in-house Scaled Agile framework. We discuss…