Requirements engineering and continuous deployment

This article summarizes the RE in the Age of Continuous Deployment panel at the 25th IEEE International Requirements Engineering Conference. It highlights two synergistic points (user stories and linguistic tooling) and one challenge (nonfunctional requirements) in fast-paced, agile-like projects, and recommends how to carry on the dialogue.Peer ReviewedPostprint (author's final draft

Automation of the Continuous Integration (CI) - Continuous Delivery/Deployment (CD) Software Development

Continuous Integration (CI) is a practice in software development where developers periodically merge code changes in a central shared repository, after which automatic versions and tests are executed. CI entails an automation component (the target of this project) and a cultural one, as developers have to learn to integrate code periodically. The main goal of CI is to reduce the time to feedback over the software integration process, allowing to locate and fix bugs more easily and quickly, thus enhancing it quality while reducing the time to validate and publish new soIn traditional software development, where teams of developers worked on the same project in isolation, often led to problems integrating the resulting code. Due to this isolation, the project was not deliverable until the integration of all its parts, which was tedious and generated errors. The Continuous Integration (CI ) emerged as a practice to solve the problems of traditional methodology, with the aim of improving the quality of the code. This thesis sets out what is it and how Continuous Integration is achieved, the principles that makes it as effective as possible and the processes that follow as a consequence, to thus introduce the context of its objective: the creation of a system that automates the start-up and set-up of an environment to be able to apply the methodology of continuous integration

DevOps, Continuous Integration and Continuous Deployment Methods for Software Deployment Automation

In the fast-paced landscape of software development, the need for efficient, reliable, and rapid deployment processes has become paramount. Manual deployment processes often lead to inefficiencies, errors, and delays, impacting the overall agility and reliability of software delivery. DevOps, as a cultural and collaborative approach, plays a central role in orchestrating the synergy between development and operations teams, fostering a shared responsibility for the entire software delivery lifecycle. Continuous Integration is a fundamental DevOps practice that involves regularly integrating code changes into a shared repository, triggering automated builds and tests. Continuous Deployment complements Continuous Integration by automating the release and deployment of validated code changes into production environments. The purpose of this research is to create a software deployment automation system to make it easier and reliable for organizations to deploy software. In conclusion, the results of this research show that by adopting DevOps, Continuous Integration, and Continuous Deployment, organizations can achieve enhanced collaboration, shortened release cycles, increased deployment frequency, consistent deployment, and improved overall software quality

DevOps : Continuous integration and continuous deployment applied

DevOps is a trending concept in the SW industry introduced and popularized during the last decade, this thesis goes deep into the concept, the culture and fields related to it which are present in almost each project and company nowadays. The research model followed in the thesis basically consists in getting in contact with the DevOps culture by designing, developing and implementing a Python tool with some Continuous Integration and Continuous Deployment features. Basically this tool consists on a back-end REST API capable of creating and automating builds on any connected slave node to the tool, similar to traditional DevOps tools logic such as Jenkins or TeamCity, but in a lightweight, portable and OS independent solution, also a frontend is developed in order to make the tool easier and simpler to use. In order to demonstrate the power and the capabilities of the tool we will containerize a build environment with Docker and automate its build process with the tool as well as deploying the binaries resulting from the build process.DevOps es un concepto de tendencia en la industria del SW introducido y popularizado durante la última década, esta tesis profundiza en el concepto, la cultura y los campos relacionados que están presentes en casi cada proyecto y empresa en la actualidad. El modelo de investigación seguido en la tesis consiste básicamente en ponerse en contacto con la cultura DevOps mediante el diseño, desarrollo e implementación de una herramienta Python con algunas características de integración continua y despliegue continuo. Básicamente, esta herramienta consiste en una API REST de back-end capaz de crear y automatizar compilaciones en cualquier nodo esclavo conectado a la herramienta, similar a la lógica de herramientas DevOps tradicionales como Jenkins o TeamCity, pero en una solución ligera, portátil e independiente del sistema operativo, también un front-end se ha desarrollado para hacer que la herramienta sea más fácil y simple de usar. Para demostrar el poder y las capacidades de la herramienta, contenerizaremos un entorno de compilación con Docker y automatizaremos su proceso de compilación con la herramienta, así como desplegaremos los binarios resultantes del proceso de compilación.DevOps es un concepte tendència a la indústria del SW, introduït i popularitzat durant la darrera decada, aquesta tesis aprofundeix en el concepte, la cultura i aspectes relacionats, que son present a la majoria de projectes i empreses avui en dia. El model d'investigació a seguir durant la tesis es basa en entrar en contecte directe amb la cultura de DevOps dissenyant, desenvolupant i implementant una eina en Python amb característiques tant de Integració Continua com de Desplegament Continuu. En resum, la eina consisteix en un backend REST API que permet la creació i automatització de construccions de projectes en qualsevol node esclau conectat a la eina, de manera semblant a eines tradicional de DevOps com son Jenkins o Teamcity pero d'una manera lleugera, portable i independent del sistema operatiu. Tambe s'ha desenvolupat un frontend per facilitar l'us de l'eina. Finalment, per a demostrar el funcionament i la capacitat de l'eina crearem un entorn de construcció amb docker del qual automatitzarem el procés de construcció amb l'eina a més de desplegar els binaris resultants del procés

Continuous Deployment Transitions at Scale

Predictable, rapid, and data-driven feature rollout; lightning-fast; and automated fix deployment are some of the benefits most large software organizations worldwide are striving for. In the process, they are transitioning toward the use of continuous deployment practices. Continuous deployment enables companies to make hundreds or thousands of software changes to live computing infrastructure every day while maintaining service to millions of customers. Such ultra-fast changes create a new reality in software development. Over the past four years, the Continuous Deployment Summit, hosted at Facebook, Netflix, Google, and Twitter has been held. Representatives from companies like Cisco, Facebook, Google, IBM, Microsoft, Netflix, and Twitter have shared the triumphs and struggles of their transition to continuous deployment practices—each year the companies press on, getting ever faster. In this chapter, the authors share the common strategies and practices used by continuous deployment pioneers and adopted by newcomers as they transition and use continuous deployment practices at scale

Design Criteria to Architect Continuous Experimentation for Self-Driving Vehicles

The software powering today's vehicles surpasses mechatronics as the dominating engineering challenge due to its fast evolving and innovative nature. In addition, the software and system architecture for upcoming vehicles with automated driving functionality is already processing ~750MB/s - corresponding to over 180 simultaneous 4K-video streams from popular video-on-demand services. Hence, self-driving cars will run so much software to resemble "small data centers on wheels" rather than just transportation vehicles. Continuous Integration, Deployment, and Experimentation have been successfully adopted for software-only products as enabling methodology for feedback-based software development. For example, a popular search engine conducts ~250 experiments each day to improve the software based on its users' behavior. This work investigates design criteria for the software architecture and the corresponding software development and deployment process for complex cyber-physical systems, with the goal of enabling Continuous Experimentation as a way to achieve continuous software evolution. Our research involved reviewing related literature on the topic to extract relevant design requirements. The study is concluded by describing the software development and deployment process and software architecture adopted by our self-driving vehicle laboratory, both based on the extracted criteria.Comment: Copyright 2017 IEEE. Paper submitted and accepted at the 2017 IEEE International Conference on Software Architecture. 8 pages, 2 figures. Published in IEEE Xplore Digital Library, URL: http://ieeexplore.ieee.org/abstract/document/7930218

Security Support in Continuous Deployment Pipeline

Continuous Deployment (CD) has emerged as a new practice in the software industry to continuously and automatically deploy software changes into production. Continuous Deployment Pipeline (CDP) supports CD practice by transferring the changes from the repository to production. Since most of the CDP components run in an environment that has several interfaces to the Internet, these components are vulnerable to various kinds of malicious attacks. This paper reports our work aimed at designing secure CDP by utilizing security tactics. We have demonstrated the effectiveness of five security tactics in designing a secure pipeline by conducting an experiment on two CDPs - one incorporates security tactics while the other does not. Both CDPs have been analyzed qualitatively and quantitatively. We used assurance cases with goal-structured notations for qualitative analysis. For quantitative analysis, we used penetration tools. Our findings indicate that the applied tactics improve the security of the major components (i.e., repository, continuous integration server, main server) of a CDP by controlling access to the components and establishing secure connections