This book is a critical introduction to code and software that develops an understanding of its social and philosophical implications in the digital age. Written specifically for people interested in the subject from a non-technical background, the book provides a lively and interesting analysis of these new media forms.
This tutorial book presents an augmented selection of the material presented at the Software Engineering Education and Training Track at the International Conference on Software Engineering, ICSE 2005, held in St. Louis, MO, USA in May 2005. The 12 tutorial lectures presented cover software engineering education, state of the art and practice: creativity and rigor, challenges for industries and academia, as well as future directions.
This SpringerBrief discusses multiple forms of open-source-inspired outsourcing: opensourcing, innersourcing and crowdsourcing. It uses a framework-based comparison to explain the strengths and weaknesses of each approach. By pointing out characteristics along with benefits and pitfalls of each approach, the authors provide nuanced and research-based advice to managers and developers facing software sourcing decisions. The differences and commonalities of these three emerging approaches are carefully analyzed. Chapters explore the primary challenges of reliability, efficiency and robustness in open-source methods. Examples from industrial cases are included, along with extensive references to recent research. The brief concludes with a comparative analysis of approaches and outlines key implications to be aware of when outsourcing. Software Sourcing in the Age of Open: Leveraging the Unknown Workforce is designed for professionals and researchers interested in outsourcing challenges. The content is also suitable for postgraduate students interested in contemporary software sourcing approaches.
SD-WAN is an advanced networking approach that creates hybrid networks to integrate broadband or other network services into the corporate WAN, not only just handling general business workloads and traffic, but also being capable of maintaining the performance and security of real-time and sensitive applications. This book posits that Software Defined (SD) WAN is the answer to questions such as what changes can be made to the networking sector? What innovations can make WAN, which plays a vital integrated part of the cloud ecosystem, more cost effective, performance robust, provisioning efficient, and operation intelligent?
Programming Cultures explores the relationship between software engineering and the various disciplines that benefit from new codes and programming tools. The title focuses on a range of practices including: aviation design, urban infrastructure simulation, Hollywood special effects, nanotechnology, mathematics and architecture. In terms of building design, Programming Cultures specifically examine's the potential of new software designed to solve specific visualization and data processing problems from within the profession. The book allows architects to become more familiar with programming rather than basing their work on appropriated systems designed for non-architectural applications (Maya, 3D Studio MAX etc.) and will become a primer for an emerging culture of students; academics and young professionals that are starting to outgrow the predetermined structure of today’s most popular modeling and animation packages.
The book "Accelerating Software Quality: Machine Learning and Artificial Intelligence in the Age of DevOps" is a complete asset for software developers, testers, and managers that are on their journey to a more mature DevOps workflow, and struggle with better automation and data-driven decision making. DevOps is a mature process across the entire market, however, with existing Non-AI/ML technologies and models, it comes short in expediting release cycle, identifying productivity gaps and addressing them. This book, that was implemented by myself with the help of leaders from the DevOps and test automation space, is covering topics from basic introduction to AI and ML in software development and testing, implications of AI and ML on existing apps, processes, and tools, practical tips in applying commercial and open-source AI/ML tools within existing tool chain, chat-bots testing, visual based testing using AI, automated security scanning for vulnerabilities, automated code reviews, API testing and management using AI/ML, reducing effort and time through test impact analysis (TIA), robotic process automation (RPA), AIOps for smarter code deployments and production defects prevention, and many more.When properly leveraging such tools, DevOps teams can benefit from greater code quality and functional and non-functional test automation coverage. This increases their release cycle velocity, reduces noise and software waste, and enhances their app quality.The book is divided into 3 main sections: *Section 1 covers the fundamentals of AI and ML in software development and testing. It includes introductions, definitions, 101 for testing AI-Based applications, classifications of AI/ML and defects that are tied to AI/ML, and more.*Section 2 focuses on practical advises and recommendations for using AI/ML based solutions within software development activities. This section includes topics like visual AI test automation, AI in test management, testing conversational AI applications, RPA benefits, API testing and much more.*Section 3 covers the more advanced and future-looking angles of AI and ML with projections and unique use cases. Among the topics in this section are AI and ML in logs observability, AIOps benefits to an entire DevOps teams, how to maintain AI/ML test automation, Test impact analysis with AI, and more.The book is packed with many proven best practices, real life examples, and many other open source and commercial solution recommendations that are set to shape the future of DevOps together with ML/AI
The big stories -- The skills of the new machines : technology races ahead -- Moore's law and the second half of the chessboard -- The digitization of just about everything -- Innovation : declining or recombining? -- Artificial and human intelligence in the second machine age -- Computing bounty -- Beyond GDP -- The spread -- The biggest winners : stars and superstars -- Implications of the bounty and the spread -- Learning to race with machines : recommendations for individuals -- Policy recommendations -- Long-term recommendations -- Technology and the future (which is very different from "technology is the future").