Microservices complement approaches like DevOps and continuous delivery in terms of software architecture. Along with this architectural style, several important deployment technologies, such as container-based virtualization and container orchestration ...

When real-time embedded systems fail: patients die, warships shoot passenger jets, airplanes crash, cars stop on freeways or accelerate uncontrollably, and other documented problems. Preventing these problems saves lives, money, enables faster delivery, ...

This paper investigates the question of improving a performance model by exploiting all the information that is known about a system. The modeling perspective is to be opened up to encompass the entire available dataset, which could make performance ...

Cyber-physical Systems (CPS) are engineered systems that are built from, and depend upon, the seamless integration of computational algorithms and physical components. Therefore, the engineering of CPS is inherently collaborative, demanding cooperation ...

The Reflection architectural pattern is an elegant reusable solution to design software applications based on a meta-model that provides a self-representation of the types used in the domain model. This provides significant benefits in terms of ...

The concept of service level agreements (SLAs) defines the idea of a reliable contract between service providers and their users. SLAs provide information on the scope, the quality and the responsibilities of a service and its provider. Service level ...

As our society evolves, more and more aspects of our daily life depend on large-scale infrastructures such as software intensive computer infrastructures, rails and road networks, gas networks, water networks, power networks, and telecommunication ...

Effective software performance analysis needs to be conducted by crossing multiple disciplines such as algorithms, data structures, effective coding, performance data collection and its associated overheads, computer architecture, operating systems, ...

Basic topics from probability and statistics -- such as probability distributions, parameter estimation, confidence intervals and statistical hypothesis testing -- are often included in computing curricula and used as tools for experimental performance ...

We describe our experience of teaching software performance engineering and analysis in academic and industrial settings. There is a need to teach course participants core principles about basic performance modeling and data handling in both settings. ...

In agile, fast and continuous development lifecycles, software performance analysis is fundamental to confidently release continuously improved software versions. Researchers and industry practitioners have identified the importance of integrating ...

The performance of software systems is an ongoing issue in the industry, including the development of corresponding performance models. Recently several approaches for deriving such performance models from monitoring data have been proposed. A current ...

Providing users with Quality of Service (QoS) guarantees and the prevention of performance problems are challenging tasks for software systems. Architectural performance models can be applied to explore performance properties of a software system at ...

This article introduces a model-driven engineering (MDE) integrated development environment (IDE) for Data-Intensive Cloud Applications (DIA) with iterative quality enhancements. As part of the H2020 DICE project (ICT-9-2014, id 644869), a framework is ...

The paper presents an industrial application of a DevOps process for a Tax fraud detection system. In particular, we report the influence of the quality assessment during development iterations, with special focus on the fulfillment of performance ...

With the onset of Big Data and Data-Intensive Applications (DIAs) exploiting such big data, the problem of offering privacy guarantees to data owners becomes crucial, even more so with the emergence of DevOps development strategies where speed is ...

The aim of this work is to present the problem of Capacity Allocation for multiple classes of Big Data applications running in the Cloud. The objective is the minimization of the renting out costs subject to the fulfillment of QoS requirements expressed ...

Modern DevOps pipelines entail extreme automation and speed as paramount assets for continuous application improvement. Likewise, monitoring is required to assess the quality of service and user-experience such that applications can continuously evolve ...

DevOps is a software engineering strategy to reduce soft- ware changes' rollout times by adopting any set of tactics that reduce friction in software lifecycles and their organisational variables, for example: coordination, communication, product ...

Microservice architectures are steadily gaining adoption in industrial practice. At the same time, performance and resilience are important properties that need to be ensured. Even though approaches for performance and resilience have been developed (...