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Academic research projects receive hundreds of billions of dollars of government investment each year. They complement business research projects by focusing on the generation of new foundational knowledge and addressing societal…
Uncertainty in large language model (LLM)-based systems is often studied at the level of a single model output, yet deployed LLM applications are compound systems in which uncertainty is transformed and reused across model internals,…
Many real-world decision-making problems involve multiple decision-making stages and various objectives. Besides, most of the decisions need to be made before having complete knowledge about all aspects of the problem leaves some sort of…
Agile software development emphasizes flexibility and iterative processes, which may conflict with the more linear, rigid, and time-consuming traditional funding and contracting approaches. This review synthesizes real-life experiences of…
Bilevel optimization is a powerful tool for modeling hierarchical decision making processes. However, the resulting problems are challenging to solve - both in theory and practice. Fortunately, there have been significant algorithmic…
This article discusses the importance of managing knowledge as a resource due to its great potential to create economic value. We detail the types of knowledge resources, the challenges associated with their management, and potential…
Software ecosystems are collections of projects that are developed and evolve together in the same environment. Existing literature investigates software ecosystems as isolated entities whose boundaries do not overlap and assumes they are…
Software development methods are usually not applied by the book. Companies are under pressure to continuously deploy software products that meet market needs and stakeholders' requests. To implement efficient and effective development…
Testing is an essential quality activity in the software development process. Usually, a software system is tested on several levels, starting with unit testing that checks the smallest parts of the code until acceptance testing, which is…
Smaller software companies, such as start-ups do not often follow an explicit process, but rather develop in a more or less unstructured way. Especially when they grow or customer involvement increases. This development without any…
With the rise of large language models (LLMs), researchers are increasingly exploring their applications in var ious vertical domains, such as software engineering. LLMs have achieved remarkable success in areas including code generation…
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…
Scholars have tried to explain how organizations can build agile teams by only looking at one level of analysis. We argue in this short paper that lessons can be learned from organizational science results explaining variance on three…
Software Repositories contain knowledge on how software engineering teams work, communicate, and collaborate. It can be used to develop a data-informed view of a team's development process, which in turn can be employed for process…
Context: Existing knowledge in agile software development suggests that individual competency (e.g. skills) is a critical success factor for agile projects. While assuming that technical skills are important for every kind of software…
The globalization feeded by the technology explosion that begans in the end of the last century, started the world to change faster every day. The only today's certain is the tomorrow's uncertain. Risk is defined as uncertain where one or…
Context: Success with agile methods in the small scale has led to an increasing adoption also in large development undertakings and organizations. Recent years have also seen an increasing amount of primary research on the topic, as well as…
Existing scientific literature highlights the importance of metrics in Agile Software Development (ASD). Still, empirical investigation into metrics in ASD is scarce, particularly in identifying the rationale and the operational challenges…
Uncertainty is prevalent in engineering design, data-driven problems, and decision making broadly. Due to inherent risk-averseness and ambiguity about assumptions, it is common to address uncertainty by formulating and solving conservative…
The use of agile principles and practices in software development is becoming a powerful force in today's workplace. In our quest to develop better products, therefore, it is imperative that we strive to learn and understand the application…