This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to "experiment and learn" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.

This book identifies, defines and illustrates the fundamental concepts and engineering techniques relevant to applications of software languages in software development. It presents software languages primarily from a software engineering perspective, i.e., it addresses how to parse, analyze, transform, generate, format, and otherwise process software artifacts in different software languages, as they appear in software development. To this end, it covers a wide range of software languages - most notably programming languages, domain-specific languages, modeling languages, exchange formats, and specifically also language definition languages. Further, different languages are leveraged to illustrate software language engineering concepts and techniques. The functional programming language Haskell dominates the book, while the mainstream programming languages Python and Java are additionally used for illustration. By doing this, the book collects and organizes scattered knowledge from software language engineering, focusing on application areas such as software analysis (software reverse engineering), software transformation (software re-engineering), software composition (modularity), and domain-specific languages. It is designed as a textbook for independent study as well as for bachelor's (advanced level) or master's university courses in Computer Science. An additional website provides complementary material, for example, lecture slides and videos. This book is a valuable resource for anyone wanting to understand the fundamental concepts and important engineering principles underlying software languages, allowing them to acquire much of the operational intelligence needed for dealing with software languages in software development practice. This is an important skill set for software engineers, as languages are increasingly permeating software development.

This book provides guidelines for practicing design science in the fields of information systems and software engineering research. A design process usually iterates over two activities: first designing an artifact that improves something for stakeholders and subsequently empirically investigating the performance of that artifact in its context. This "validation in context" is a key feature of the book - since an artifact is designed for a context, it should also be validated in this context. The book is divided into five parts. Part I discusses the fundamental nature of design science and its artifacts, as well as related design research questions and goals. Part II deals with the design cycle, i.e. the creation, design and validation of artifacts based on requirements and stakeholder goals. To elaborate this further, Part III presents the role of conceptual frameworks and theories in design science. Part IV continues with the empirical cycle to investigate artifacts in context, and presents the different elements of research problem analysis, research setup and data analysis. Finally, Part V deals with the practical application of the empirical cycle by presenting in detail various research methods, including observational case studies, case-based and sample-based experiments and technical action research. These main sections are complemented by two generic checklists, one for the design cycle and one for the empirical cycle. The book is written for students as well as academic and industrial researchers in software engineering or information systems. It provides guidelines on how to effectively structure research goals, how to analyze research problems concerning design goals and knowledge questions, how to validate artifact designs and how to empirically investigate artifacts in context - and finally how to present the results of the design cycle as a whole.

The eagerly awaited Pattern-Oriented Software Architecture (POSA) Volume 4 is about a pattern language for distributed computing.

The authors will guide you through the best practices and introduce you to key areas of building distributed software systems. POSA 4 connects many stand-alone patterns, pattern collections and pattern languages from the existing body of literature found in the POSA series. Such patterns relate to and are useful for distributed computing to a single language.The panel of experts provides you with a consistent and coherent holistic view on the craft of building distributed systems.Includes a foreword by Martin FowlerA must read for practitioners who want practical advice to develop a comprehensive language integrating patterns from key literature.

This new edition of Risk Management: Concepts and Guidance supplies a look at risk in light of current information, yet remains grounded in the history of risk practice. Taking a holistic approach, it examines risk as a blend of environmental, programmatic, and situational concerns. Supplying comprehensive coverage of risk management tools, practices, and protocols, the book presents powerful techniques that can enhance organizational risk identification, assessment, and management-all within the project and program environments. Updated to reflect the Project Management Institute's A Guide to the Project Management Body of Knowledge (PMBOK (R) Guide), Fifth Edition, this edition is an ideal resource for those seeking Project Management Professional and Risk Management Professional certification. Emphasizing greater clarity on risk practice, this edition maintains a focus on the ability to apply "planned clairvoyance" to peer into the future. The book begins by analyzing the various systems that can be used to apply risk management. It provides a fundamental introduction to the basics associated with particular techniques, clarifying the essential concepts of risk and how they apply in projects. The second part of the book presents the specific techniques necessary to successfully implement the systems described in Part I. The text addresses project risk management from the project manager's perspective. It adopts PMI's perspective that risk is both a threat and an opportunity, and it acknowledges that any effective risk management practice must look at the potential positive events that may befall a project, as well as the negatives.Providing coverage of the concepts that many project management texts ignore, such as the risk response matrix and risk models, the book includes appendices filled with additional reference materials and supporting details that simplifying some of the most complex aspects of risk management.

Like other sciences and engineering disciplines, software engineering requires a cycle of model building, experimentation, and learning. Experiments are valuable tools for all software engineers who are involved in evaluating and choosing between different methods, techniques, languages and tools.

The purpose of Experimentation in Software Engineering is to introduce students, teachers, researchers, and practitioners to empirical studies in software engineering, using controlled experiments. The introduction to experimentation is provided through a process perspective, and the focus is on the steps that we have to go through to perform an experiment. The book is divided into three parts. The first part provides a background of theories and methods used in experimentation. Part II then devotes one chapter to each of the five experiment steps: scoping, planning, execution, analysis, and result presentation. Part III completes the presentation with two examples. Assignments and statistical material are provided in appendixes. Overall the book provides indispensable information regarding empirical studies in particular for experiments, but also for case studies, systematic literature reviews, and surveys. It is a revision of the authors' book, which was published in 2000. In addition, substantial new material, e.g. concerning systematic literature reviews and case study research, is introduced. The book is self-contained and it is suitable as a course book in undergraduate or graduate studies where the need for empirical studies in software engineering is stressed. Exercises and assignments are included to combine the more theoretical material with practical aspects. Researchers will also benefit from the book, learning more about how to conduct empirical studies, and likewise practitioners may use it as a "cookbook" when evaluating new methods or techniques before implementing them in their organization."

Regular expressions are an extremely powerful tool for manipulating text and data. They are now standard features in a wide range of languages and popular tools, including Perl, Python, Ruby, Java, VB.NET and C# (and any language using the .NET Framework), PHP, and MySQL. If you don't use regular expressions yet, you will discover in this book a whole new world of mastery over your data. If you already use them, you'll appreciate this book's unprecedented detail and breadth of coverage. If you think you know all you need to know about regular expressions, this book is a stunning eye-opener. As this book shows, a command of regular expressions is an invaluable skill. Regular expressions allow you to code complex and subtle text processing that you never imagined could be automated. Regular expressions can save you time and aggravation. They can be used to craft elegant solutions to a wide range of problems. Once you've mastered regular expressions, they'll become an invaluable part of your toolkit. You will wonder how you ever got by without them. Yet despite their wide availability, flexibility, and unparalleled power, regular expressions are frequently underutilized. Yet what is power in the hands of an expert can be fraught with peril for the unwary. Mastering Regular Expressions will help you navigate the minefield to becoming an expert and help you optimize your use of regular expressions. Mastering Regular Expressions, Third Edition, now includes a full chapter devoted to PHP and its powerful and expressive suite of regular expression functions, in addition to enhanced PHP coverage in the central "core" chapters. Furthermore, this edition has been updated throughout to reflect advances in other languages, including expanded in-depth coverage of Sun's java.util.regex package, which has emerged as the standard Java regex implementation.Topics include: * A comparison of features among different versions of many languages and tools * How the regular expression engine works * Optimization (major savings available here!) * Matching just what you want, but not what you don't want * Sections and chapters on individual languages Written in the lucid, entertaining tone that makes a complex, dry topic become crystal-clear to programmers, and sprinkled with solutions to complex real-world problems, Mastering Regular Expressions, Third Edition offers a wealth information that you can put to immediate use. Reviews of this new edition and the second edition: "There isn't a better (or more useful) book available on regular expressions." --Zak Greant, Managing Director, eZ Systems "A real tour-de-force of a book which not only covers the mechanics of regexes in extraordinary detail but also talks about efficiency and the use of regexes in Perl, Java, and .NET...If you use regular expressions as part of your professional work (even if you already have a good book on whatever language you're programming in) I would strongly recommend this book to you." --Dr. Chris Brown, Linux Format "The author does an outstanding job leading the reader from regex novice to master. The book is extremely easy to read and chock full of useful and relevant examples...Regular expressions are valuable tools that every developer should have in their toolbox. Mastering Regular Expressi

The use of Python as a powerful computational tool is expanding with great strides. Python is a language which is easy to use, and the libraries of tools provides it with efficient versatility. As the tools continue to expand, users can create insightful models and simulations. While the tools offer an easy method to create a pipeline, such constructions are not guaranteed to provide correct results. A lot of things can go wrong when building a simulation - deviously so. Users need to understand more than just how to build a process pipeline. Modeling and Simulation in Python introduces fundamental computational modeling techniques that are used in a variety of science and engineering disciplines. It emphasizes algorithmic thinking skills using different computational environments, and includes a number of interesting examples, including Shakespeare, movie databases, virus spread, and Chess. Key Features: Several theories and applications are provided, each with working Python scripts. All Python functions written for this book are archived on GitHub. Readers do not have to be Python experts, but a working knowledge of the language is required. Students who want to know more about the foundations of modeling and simulation will find this an educational and foundational resource.

This book describes the research of the authors over more than a decade on an end-to-end methodology for the design and development of Web Information Systems (WIS). It covers syntactics, semantics and pragmatics of WIS, introduces sophisticated concepts for conceptual modelling, provides integrated foundations for all these concepts and integrates them into the co-design method for systematic WIS development. WIS, i.e. data-intensive information systems that are realized in a way that arbitrary users can access them via web browsers, constitute a prominent class of information systems, for which acceptance by its a priori unknown users in varying contexts with respect to the presented content, the ease of functionality provided and the attraction of the layout adds novel challenges for modelling, design and development. This book is structured into four parts. Part I, Web Information Systems - General Aspects, gives a general introduction to WIS describing the challenges for their development, and provides a characterization by six decisive aspects: intention, usage, content, functionality, context and presentation. Part II, High-Level WIS Design - Strategic Analysis and Usage Modelling with Storyboarding, introduces methods for high-level design of WIS covering strategic aspects and the storyboarding method, which is discussed from syntactic, semantic and pragmatic perspectives. Part III, Conceptual WIS Design - Rigorous Modelling of Web Information Systems and their Layout with Web Interaction Types and Screenography, continues with conceptual design of WIS including layout and playout. This introduces the decisive web interaction types, the screenography method and adaptation aspects. The final Part IV, Rationale of the Co-Design Methodology and Systematic Development of Web Information Systems, describes the co-design method for WIS development and its application for the systematic engineering of systems. The book addresses the research community, and at the same time can be used for education of graduate students and as methodological support for professional WIS developers. For the WIS research community it provides methods for WIS modelling on all levels of abstraction including theoretical foundations and inference mechanisms as well as a sophisticated end-to-end methodology for systematic WIS engineering from requirements elicitation over conceptual modelling to aspects of implementation, layout and playout. For students and professional developers the book can be used as a whole for educational courses on WIS design and development, as well as for more specific courses on conceptual modelling of WIS, WIS foundations and reasoning, co-design and WIS engineering or WIS layout and playout development.

Does your Rails code suffer from bloat, brittleness, or inaccuracy? Cure these problems with the regular application of test-driven development. You'll use Rails 5.1, Minitest 5, and RSpec 3.6, as well as popular testing libraries such as factory_girl and Cucumber. Updates include Rails 5.1 system tests and Webpack integration. Do what the doctor ordered to make your applications feel all better. Side effects may include better code, fewer bugs, and happier developers. Your Ruby on Rails application is sick. Deadlines are looming, but every time you make the slightest change to the code, something else breaks. Nobody remembers what that tricky piece of code was supposed to do, and nobody can tell what it actually does. Plus, it has bugs. You need test-driven development: a process for improving the design, maintainability, and long-term viability of software. With both practical code examples and discussion of why testing works, this book starts with the most basic features delivered as part of core Ruby on Rails. Once you've integrated those features into your coding practice, work with popular third-party testing tools such as RSpec, Jasmine, Cucumber, and factory_girl. Test the component parts of a Rails application, including the back-end model logic and the front-end display logic. With Rails examples, use testing to enable your code to respond better to future change. Plus, see how to handle real-world testing situations. This new edition has been updated to Rails 5.1 and RSpec 3.6 and contains full coverage of new Rails features, including system tests and the Webpack-based JavaScript setup. What You Need: Ruby 2.4, Rails 5.1

Validation of computer systems is the process that assures the formal assessment and report of quality and performance measures for all the life-cycle stages of software and system development, its implementation, qualification and acceptance, operation, modification, requalification, maintenance and retirement (PICS CSV PI 011-3). It is a process that demonstrates the compliance of computer systems functional and non-functional requirements, data integrity, regulated company procedures and safety requirements, industry standards, and applicable regulatory authority's requirements. Compliance is a state of being in adherence to application-related standards or conventions or regulations in laws and similar prescriptions. This book, which is relevant to the pharmaceutical and medical devices regulated operations, provides practical information to assist in the computer validation to production systems, while highlighting and efficiently integrating worldwide regulation into the subject. A practical approach is presented to increase efficiency and to ensure that the validation of computer systems is correctly achieved.

Here, the authors propose a method for the formal development of parallel programs - or multiprograms as they prefer to call them. They accomplish this with a minimum of formal gear, i.e. with the predicate calculus and the well- established theory of Owicki and Gries. They show that the Owicki/Gries theory can be effectively put to work for the formal development of multiprograms, regardless of whether these algorithms are distributed or not.

The focus of this book is on bridging the gap between two extreme methods for developing software. On the one hand, there are texts and approaches that are so formal that they scare off all but the most dedicated theoretical computer scientists. On the other, there are some who believe that any measure of formality is a waste of time, resulting in software that is developed by following gut feelings and intuitions.

Kourie and Watson advocate an approach known as "correctness-by-construction," a technique to derive algorithms that relies on formal theory, but that requires such theory to be deployed in a very systematic and pragmatic way. First they provide the key theoretical background (like first-order predicate logic or refinement laws) that is needed to understand and apply the method. They then detail a series of graded examples ranging from binary search to lattice cover graph construction and finite automata minimization in order to show how it can be applied to increasingly complex algorithmic problems. The principal purpose of this book is to change the way software developers approach their task at programming-in-the-small level, with a view to improving code quality. Thus it coheres with both the IEEE's Guide to the Software Engineering Body of Knowledge (SWEBOK) recommendations, which identifies themes covered in this book as part of the software engineer's arsenal of tools and methods, and with the goals of the Software Engineering Method and Theory (SEMAT) initiative, which aims to "refound software engineering based on a solid theory.""

Software development isn't an "ivory tower" exercise.Street coders get the job done by prioritizing tasks, making quick decisions, and knowing which rules to break. Street Coder: Rules to break and how to break themis a programmer's survival guide, full of tips, tricks, and hacks that will make you a more efficient programmer. This book's rebel mindset challenges status quo thinking and exposes the important skills you need on the job. You'll learnthe crucial importance of algorithms and data structures, turn programming chores into programming pleasures, and shatter dogmatic principles keeping you from your full potential. Every new coder starts out with a lot of theory; the "streetsmarts" come with experience. To be successful, you need to know how toput theory into action, understand why "best practices" are the best, and know when to go rogue and break the unbreakable rules.

Although the use of cloud computing platforms and applications has expanded rapidly, most books on the subject focus on high-level concepts. There has long been a need for a book that provides detailed guidance on how to develop secure clouds.
Filling this void, Developing and Securing the Cloud provides a comprehensive overview of cloud computing technology. Supplying step-by-step instruction on how to develop and secure cloud computing platforms and web services, it includes an easy-to-understand, basic-level overview of cloud computing and its supporting technologies.
Presenting a framework for secure cloud computing development, the book describes supporting technologies for the cloud such as web services and security. It details the various layers of the cloud computing framework, including the virtual machine monitor and hypervisor, cloud data storage, cloud data management, and virtual network monitor. It also provides several examples of cloud products and prototypes, including private, public, and U.S. government clouds.
Reviewing recent developments in cloud computing, the book illustrates the essential concepts, issues, and challenges in developing and securing today s cloud computing platforms and applications. It also examines prototypes built on experimental cloud computing systems that the author and her team have developed at the University of Texas at Dallas.
This diverse reference is suitable for those in industry, government, and academia. Technologists will develop the understanding required to select the appropriate tools for particular cloud applications. Developers will discover alternative designs for cloud development, and managers will understand if it s best to build their own clouds or contract them out.

With the rapid growth of technology in society, communication networks have become a heavily researched topic. Implementing these advanced systems is a challenge, however, due to the abundance of optimization problems within these networks. The use of meta-heuristic algorithms and nature-inspired computing has become a prevalent technique among researchers for solving these complex problems within communication networks. Despite its popularity, this specific computing technique lacks the appropriate amount of research that is needed for professionals to grasp a definite understanding. Nature-Inspired Computing Applications in Advanced Communication Networks is a collection of innovative research on the methods and applications of natural computation techniques and algorithms within communication systems such as wireless sensor networks, vehicular adhoc networks, and internet of things. While highlighting topics including mobile sensor deployment, routing optimization, and sleep scheduling, this book is ideally designed for researchers, network professionals, computer scientists, mathematicians, developers, scholars, educators, and students seeking to enhance their understanding of nature-inspired computing and its solutions within various advanced communication networks.

The C programming language is a popular language in industries as well as academics. Since its invention and standardized as ANSI C, several other standards known as C99, C11, and C17 were published with new features in subsequent years. This book covers all the traits of ANSI C and includes new features present in other standards. The content of this book helps a beginner to learn the fundamental concept of the C language. The book contains a step-by-step explanation of every program that allows a learner to understand the syntax and builds a foundation to write similar programs. The explanation clarity, exercises, and illustrations present in this book make it a complete textbook in all aspects. Features: Other than ANSI C, the book explains the new C standards like C99, C11, and C17. Most basic and easy-to-follow programs are chosen to explain the concepts and their syntax. More emphasis is given to the topics like Functions, Pointers, and Structures. Recursion is emphasized with numerous programming examples and diagrams. A separate chapter on the command-line argument and preprocessors is included that concisely explains their usage. Several real-life figures are taken to explain the concepts of dynamic memory allocation, file handling, and the difference between structure and union. The book contains more than 260 illustrations, more than 200 programs, and exercises at the end of each chapter. This book serves as a textbook for UG/PG courses in science and engineering. The researcher, postgraduate engineers, and embedded software developers can also keep this book as reference material for their fundamental learning.

Survival analysis uses statistics to calculate time to failure. Survival Analysis with Python takes a fresh look at this complex subject by explaining how to use the Python programming language to perform this type of analysis. As the subject itself is very mathematical and full of expressions and formulations, the book provides detailed explanations and examines practical implications. The book begins with an overview of the concepts underpinning statistical survival analysis. It then delves into Parametric models with coverage of Concept of maximum likelihood estimate (MLE) of a probability distribution parameter MLE of the survival function Common probability distributions and their analysis Analysis of exponential distribution as a survival function Analysis of Weibull distribution as a survival function Derivation of Gumbel distribution as a survival function from Weibull Non-parametric models including Kaplan-Meier (KM) estimator, a derivation of expression using MLE Fitting KM estimator with an example dataset, Python code and plotting curves Greenwood's formula and its derivation Models with covariates explaining The concept of time shift and the accelerated failure time (AFT) model Weibull-AFT model and derivation of parameters by MLE Proportional Hazard (PH) model Cox-PH model and Breslow's method Significance of covariates Selection of covariates The Python lifelines library is used for coding examples. By mapping theory to practical examples featuring datasets, this book is a hands-on tutorial as well as a handy reference.

Computer systems have become an important element of the world economy, with billions of dollars spent each year on development, manufacture, operation, and maintenance. Combining coverage of computer system reliability, safety, usability, and other related topics into a single volume, Computer System Reliability: Safety and Usability eliminates the need to consult many different and diverse sources in the hunt for the information required to design better computer systems. After presenting introductory aspects of computer system reliability such as safety, usability-related facts and figures, terms and definitions, and sources for obtaining useful information on computer system reliability, safety, and usability, the book: Reviews mathematical concepts considered useful to understanding subsequent chapters Presents various introductory aspects of reliability, safety, and usability and computer system reliability basics Covers software reliability assessment and improvement methods Discusses important aspects of software quality and human error and software bugs in computer systems Highlights software safety and Internet reliability Details important aspects of software usability including the need for considering usability during the software development phase, software usability engineering process, software usability inspection methods, software usability test methods, and guidelines for conducting software usability testing Elucidates web usability facts and figures, common design errors, web page design, tools for evaluating web usability, and questions to evaluate website message communication effectiveness Examines important aspects of computer system life cycle costing Written by systems reliability expert B.S. Dhillon, the book is accessible to all levels of readership, making it useful to beginners and seasoned professiona

Master proven processes for improving development with Scrum and Azure DevOps This guide can help any development team plan, track, and manage work far more effectively, by combining today's leading agile framework (Scrum) and Microsoft's ALM/DevOps toolset (Azure DevOps). Renowned Scrum expert Richard Hundhausen thoroughly covers team formation, backlogs, Sprints, test plans, collaboration, flow, continuous improvement, Azure Boards, Azure Test Plans, and the real-world tradeoffs associated with DevOps. Throughout, you'll find practical, in-the-trenches tips from experienced Professional Scrum Developers. To make this guide even more valuable, Hundhausen has organized it to complement Scrum.org's popular Professional Scrum Developer (PSD) program, which he created with Scrum.org's Ken Schwaber, author of this book's Foreword. Professional Scrum Trainer Richard Hundhausen shows how to: Deepen your understanding of the Scrum framework and Professional Scrum as based on the 2020 Scrum Guide. Provide proven work item planning and tracking, and quickly drive value from Azure Boards Improve your Scrum "pre-game": the tasks you'll perform before your first Sprint Use Azure DevOps to create and manage backlogs, plan Sprints, and collaborate throughout them Improve at scale with Scaled Professional Scrum and the Nexus scaled Scrum framework Recognize which practices are still most efficiently performed without tools Define and optimize team flow, overcome common dysfunctions, and evolve into a high-performance Professional Scrum Team About This Book For everyone who works with or relies on Scrum, including developers, designers, architects, testers, business analysts, Product Owners, Scrum Masters, managers, and other stakeholders Focuses primarily on using Scrum for software products, but can support development of adaptive solutions for any complex problem performance Professional Scrum Team

IT projects emerge from a business need. In practice, software developers must accomplish two big things before an IT project can begin: find out what you need to do (i.e., analyse business requirements) and plan out how to do it (i.e., project management). The biggest problem in IT projects is delivering the wrong product because IT people do not understand what business people require. This practical textbook teaches computer science students how to manage and deliver IT projects by linking business and IT requirements with project management in an incremental and straightforward approach. Business Analysis, Requirements, and Project Management: A Guide for Computing Students presents an approach to analysis management that scales the business perspective. It takes a business process view of a business proposal as a model and explains how to structure a technical problem into a recognisable pattern with problem frames. It shows how to identify core transactions and model them as use cases to create a requirements table useful to designers and coders. Linked to the analysis are three management tools: the product breakdown structure (PBS), the Gantt chart, and the Kanban board. The PBS is derived in part from the problem frame. The Gantt chart emerges from the PBS and ensures the key requirements are addressed by reference to use cases. The Kanban board is especially useful in Task Driven Development, which the text covers. This textbook consists of two interleaving parts and features a single case study. Part one addresses the business and requirements perspective. The second integrates core project management approaches and explains how both requirements and management are connected. The remainder of the book is appendices, the first of which provides solutions to the exercises presented in each chapter. The second appendix puts together much of the documentation for the case study into one place. The case study presents a real-word business scenario to expose students to professional practice.

Azure Infrastructure as Code is a comprehensive guide to seamlessly managing your application infrastructure with Azure's native IaC tools. The book is aimed at supporting collaboration between operations professionals and software developers, to help speed up and improve the quality of software delivery. After you master the basics, you'll dive into niche and advanced topics such as testing, reusing templates between multiple teams, and how you can define policy as code. Discover cutting-edge Deployment Stacks, and how they can help you clean up unused resources, group resources in logical containers to help visualize potential changes, and build starting plateaus for other teams to work on. About the Technology Infrastructure as code does away with time-consuming manual tasks-no more detailed scripts for creating the correct database or virtual machine. Instead, Azure's native IaC tools create infrastructure from a declarative specification in JSON (ARM) or a domain-specific language (Bicep). They empower users to create or recreate complete infrastructures with just a line of code, as well as take advantage of automation tools like Github Actions or Azure Pipelines.