Related papers: Performance-oriented DevOps: A Research Agenda
Business success of companies heavily depends on the availability and performance of their client applications. Due to modern development paradigms such as DevOps and microservice architectural styles, applications are decoupled into…
The DevOps team adopted agile methodologies during the summer internship program as an initiative to move away from waterfall. The DevOps team implemented the Scrum software development strategy to create an internal data dictionary web…
Self-adaptive software can assess and modify its behavior when the assessment indicates that the program is not performing as intended or when improved functionality or performance is available. Since the mid-1960s, the subject of system…
Widespread adoption of agile project management, independent delivery with microservices, and automated deployment with DevOps has tremendously speedup the systems development. The real game-changer is continuous integration (CI),…
Programming and software engineering courses in computer science curricula typically focus on both providing theoretical knowledge of programming languages and best-practices, and developing practical development skills. In a massive course…
Context: DevOps practices combine software development and IT operations. There is a growing number of DevOps related posts in popular online developer forum Stack Overflow (SO). While previous research analyzed SO posts related to…
The integration of security within DevOps, known as DevSecOps, has gained traction in modern software development to address security vulnerabilities while maintaining agility. Artificial Intelligence (AI) and Machine Learning (ML) have…
The need for performance measurement tools appeared soon after the emergence of the first Object-Oriented Database Management Systems (OODBMSs), and proved important for both designers and users (Atkinson \& Maier, 1990). Performance…
Developing modern systems software is a complex task that combines business logic programming and Software Performance Engineering (SPE). The later is an experimental and labor-intensive activity focused on optimizing the system for a given…
In modern, large-scale software development, engineering leaders face the significant challenge of gaining a holistic and data-driven view of team performance and system health. Data is often siloed across numerous disparate tools, making…
PerfDetectiveAI, a conceptual framework for performance gap analysis and suggestion in software applications is introduced in this research. For software developers, retaining a competitive edge and providing exceptional user experiences…
This study investigates the impact of integrating DevSecOps and Generative Artificial Intelligence (GAI) on software delivery performance within technology firms. Utilizing a qualitative research methodology, the research involved…
Traditionally, promoted by the internet companies, continuous delivery is more and more appealing to industries which develop systems with safety-critical functions. Since safety-critical systems must meet regulatory requirements and…
Over the Eight decades, computing paradigms have shifted from large, centralized systems to compact, distributed architectures, leading to the rise of the Distributed Computing Continuum (DCC). In this model, multiple layers such as cloud,…
One of the prerequisites of any organization is an unvarying sustainability in the dynamic and competitive industrial environment. Development of high quality software is therefore an inevitable constraint of any software industry. Defect…
Software Process Improvement (SPI) encompasses the analysis and modification of the processes within software development, aimed at improving key areas that contribute to the organizations' goals. The task of evaluating whether the selected…
Performance profiling consists of tracing a software system during execution and then analyzing the obtained traces. However, traces themselves affect the performance of the system distorting its execution. Therefore, there is a need to…
In the software development process, model transformation is increasingly assimilated. However, systems being developed with model transformation sometimes grow in size and become complex. Meanwhile, the performance of model transformation…
In many domains, the previous decade was characterized by increasing data volumes and growing complexity of computational workloads, creating new demands for highly data-parallel computing in distributed systems. Effective operation of…
Context: Applying Microservices Architecture (MSA) in DevOps has received significant attention in recent years. However, there exists no comprehensive review of the state of research on this topic. Objective: This work aims to…