Related papers: DevOps in Practice -- A preliminary Analysis of tw…
From science to industry, teamwork plays a crucial role in knowledge production and innovation. Most studies consider teams as static groups of individuals, thereby failing to capture how the micro-dynamics of collaborative processes and…
Context: While there are many success stories of achieving high reuse and improved quality using software platforms, there is a need to investigate the issues and challenges organizations face when transitioning to a software platform…
Multi-unit organizations are a form of organizations where the geographically dispersed units provide similar products or services in different markets. Deciding on an appropriate level of centralization in such organizations presents a…
In this paper we discuss the growing need for system behaviour to be validated and verified (V&V'ed) early in model-based systems engineering. Several aspects push companies towards integration of techniques, methods, and processes that…
Distributed Pseudo-tree Optimization Procedure (DPOP) is a well-known message passing algorithm that has been used to provide optimal solutions of Distributed Constraint Optimization Problems (DCOPs) -- a framework that is designed to…
Network virtualization and softwarizing network functions are trends aiming at higher network efficiency, cost reduction and agility. They are driven by the evolution in Software Defined Networking (SDN) and Network Function Virtualization…
Context Software start-ups have shown their ability to develop and launch innovative software products and services. Small, motivated teams and uncertain project scope makes start-ups good candidates for adopting Agile practices. Objective…
In order to cope with a complex and changing environment, industries seek to find new and more efficient ways to conduct their business. According to previous research, many of these change efforts fail to achieve their intended aims.…
Background: Studies on developer productivity and well-being find that the perceptions of productivity in a software team can be a socio-technical problem. Intuitively, problems and challenges can be better handled by managing expectations…
Developers frequently move into new teams or environments across software companies. Their onboarding experience is correlated with productivity, job satisfaction, and other short-term and long-term outcomes. The majority of the onboarding…
Context: Software start-ups are emerging as suppliers of innovation and software-intensive products. However, traditional software engineering practices are not evaluated in the context, nor adopted to goals and challenges of start-ups. As…
In DevOps Course, the Installation and configuration of the various software tools are useful in the context of application development. To teach DevOps Tools precisely to achieve the learning outcome is a skilled task for a trainer. From…
Software startups are becoming increasingly popular in software industry as well as other sectors of economy. Startups that lack necessary competences often seek for external resources from outsourcing partners. Little is known how this…
It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups…
Drivers for globalization are significant where today's organizations look for cheaper and faster ways to develop software as well as ways to satisfy quality and investment requirements imposed by customers, shareholders, and governments.…
Mob Programming, or "mobbing", is a relatively new collaborative programming practice being experimented with in different organizational contexts. There are a number of claimed benefits to this way of working, but it is not clear if these…
Data quality assessment has become a prominent component in the successful execution of complex data-driven artificial intelligence (AI) software systems. In practice, real-world applications generate huge volumes of data at speeds. These…
MLOps tools enable continuous development of machine learning, following the DevOps process. Different MLOps tools have been presented on the market, however, such a number of tools often create confusion on the most appropriate tool to be…
Context: Machine Learning Operations (MLOps) has emerged as a set of practices that combines development, testing, and operations to deploy and maintain machine learning applications. Objective: In this paper, we assess the benefits and…
For many decades, formal methods are considered to be the way forward to help the software industry to make more reliable and trustworthy software. However, despite this strong belief and many individual success stories, no real change in…