Prototyping and user testing is the best way to create successful products, but many designers skip this important step and use gut instinct instead. By explaining the goals and methodologies behind prototyping-and demonstrating how to prototype for both physical and digital products-this practical guide helps beginning and intermediate designers become more comfortable with creating and testing prototypes early and often in the process. Author Kathryn McElroy explains various prototyping methods, from fast and dirty to high fidelity and refined, and reveals ways to test your prototypes with users. You'll gain valuable insights for improving your product, whether it's a smartphone app or a new electronic gadget. Learn similarities and differences between prototyping for physical and digital products Know what fidelity level is needed for different prototypes Get best practices for prototyping in a variety of mediums, and choose which prototyping software or components to use Learn electronics prototyping basics and resources for getting started Write basic pseudocode and translate it into usable code for Arduino Conduct user tests to gain insights from prototypes

Since its first volume in 1960, Advances in Computers has presented detailed coverage of innovations in computer hardware, software, theory, design, and applications. It has also provided contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles usually allow. As a result, many articles have become standard references that continue to be of significant, lasting value in this rapidly expanding field.

Escape "Zombie Scrum" and Get Real Value from Agile! "Professional Scrum and Zombie Scrum are mortal enemies in eternal combat. If you relax your guard, Zombie Scrum comes back. This guide helps you stay on your guard, providing very practical tips for identifying when you have become a Zombie and how to stop this from happening. A must-have for any Zombie Scrum hunter." --Dave West, CEO, Scrum.org "Barry, Christiaan, and Johannes have done a magnificent job of accumulating successful experiences and sharing their inspiring stories in this very practical book. They don't shy away from telling it like it is, which is why their proposals are always as useful as they are grounded in reality." --Henri Lipmanowicz, cofounder, Liberating Structures Millions of professionals use Scrum. It is the #1 approach to agile software development in the world. Even so, by some estimates, over 70% of Scrum adoptions fall flat. Developers find themselves using "Zombie Scrum" processes that look like Scrum, but are slow, lifeless, and joyless. Scrum is just not working for them. Zombie Scrum Survival Guide reveals why Scrum runs aground and shows how to supercharge your Scrum outcomes, while having a lot more fun along the way. Humorous, visual, and extremely relatable, it offers practical approaches, exercises, and tools for escaping Zombie Scrum. Even if you are surrounded by skeptics, this book will be the antidote to help you build more of what users need, ship faster, improve more continuously, interact more successfully in any team, and feel a whole lot better about what you are doing. Suddenly, one day soon, you will remember: that is why we adopted Scrum in the first place! Learn how Zombie Scrum infects you, why it spreads, and how to inoculate yourself Get closer to your stakeholders, and wake up to their understanding of value Discover why Zombie teams can't learn, and what to do about it Clear away the specific obstacles to real continuous improvement Make self-managed teams real so people can behave like humans, not Zombies Zombie Scrum Survival Guide is for Scrum Masters, Scrum practitioners, Agile coaches and leaders, and everyone who wants to transform the promises of Scrum into reality. Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

We're losing hundreds of billions of dollars a year on broken software, and great new ideas such as agile development and Scrum don't always pay off. But there's hope. The nine software development practices in Beyond Legacy Code are designed to solve the problems facing our industry. Discover why these practices work, not just how they work, and dramatically increase the quality and maintainability of any software project. These nine practices could save the software industry. Beyond Legacy Code is filled with practical, hands-on advice and a common-sense exploration of why technical practices such as refactoring and test-first development are critical to building maintainable software. Discover how to avoid the pitfalls teams encounter when adopting these practices, and how to dramatically reduce the risk associated with building software--realizing significant savings in both the short and long term. With a deeper understanding of the principles behind the practices, you'll build software that's easier and less costly to maintain and extend.By adopting these nine key technical practices, you'll learn to say what, why, and for whom before how; build in small batches; integrate continuously; collaborate; create CLEAN code; write the test first; specify behaviors with tests; implement the design last; and refactor legacy code. Software developers will find hands-on, pragmatic advice for writing higher quality, more maintainable, and bug-free code. Managers, customers, and product owners will gain deeper insight into vital processes. By moving beyond the old-fashioned procedural thinking of the Industrial Revolution, and working together to embrace standards and practices that will advance software development, we can turn the legacy code crisis into a true Information Revolution.

Effective Software Testing is a hands-on guide to creating high quality tests, from your first line of code through pre-delivery checks. It's full of techniques drawn from proven research in software engineering. You'll learn to efficiently engineer tests specifically for your software and end reliance on generic testing practices that may be right for every project. Each chapter puts a new technique into practice with source code samples, real-world tradeoffs, and answers to the common questions developers pose about testing. You'll learn how to scrutinize your requirements for potential tests, generate tests from your code structure, and engineer rigorous suites of unit, integration, and system tests. Go beyond unit tests! Great software testing makes the entire development process more efficient, from understanding your code before you write it to catching bugs in tricky corner cases.Effective Software Testing teaches you a systematic approach to software testing. You'll master easy-to-apply techniques to create strong test suites that are specifically engineered for your code. Following real-world use cases and detailed code samples, you'll soon be engineering tests that find the bugs hiding in edge cases and the parts of code you would never think of testing! Along the way, you'll develop an intuition for testing that can save years of learning by trial and error.

This book constitutes the refereed proceedings of the Third IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2012, held in Costa de Caparica, Portugal, in February 2012. The 65 revised full papers were carefully reviewed and selected from numerous submissions. They cover a wide spectrum of topics ranging from collaborative enterprise networks to microelectronics. The papers are organized in topical sections on collaborative systems, service orientation, knowledge and content management, human interaction, Petri nets, smart systems, robotic systems, perceptional systems, signal processing, energy, renewable energy, energy smart grid, power electronics, electronics, optimization in electronics, telecommunications and electronics, and electronic materials. The book also includes papers from the Workshop on Data Anaylsis and Modeling Retina in Health and Disease.

An Approach to Modelling Software Evolution Processes describes formal software processes that effectively support software evolution. The importance and popularity of software evolution increase as more and more successful software systems become legacy systems. For one thing, software evolution has become an important characteristic in the software life cycle; for another, software processes play an important role in increasing efficiency and quality of software evolution. Therefore, the software evolution process, the inter-discipline of software process and software evolution, becomes a key area in software engineering.

The book is intended for software engineers and researchers in computer science.

Prof. Tong Li earned his Ph.D. in Software Engineering at De Montfort University, U.K.; he has published five monographs and over one hundred papers.

Modern-day projects require software and systems engineers to work together in realizing architectures of large and complex software-intensive systems. To date, the two have used their own tools and methods to deal with similar issues when it comes to the requirements, design, testing, maintenance, and evolution of these architectures. Software and Systems Architecture in Action explores practices that can be helpful in the development of architectures of large-scale systems in which software is a major component. Examining the synergies that exist between the disciplines of software and systems engineering, it presents concepts, techniques, and methods for creating and documenting architectures. The book describes an approach to architecture design that is driven from systemic quality attributes determined from both the business and technical goals of the system, rather than just its functional requirements. This architecture-centric design approach utilizes analytically derived patterns and tactics for quality attributes that inform the architect's design choices and help shape the architecture of a given system. The book includes coverage of techniques used to assess the impact of architecture-centric design on the structural complexity of a system. After reading the book, you will understand how to create architectures of systems and assess their ability to meet the business goals of your organization. Ideal for anyone involved with large and complex software-intensive systems, the book details powerful methods for engaging the software and systems engineers on your team. The book is also suitable for use in undergraduate and graduate-level courses on software and systems architecture as it exposes students to the concepts and techniques used to create and manage architectures of software-intensive systems.

Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing tools and techniques across a range of computing environments. The book begins by discussing the basic concepts and tools of large-scale Big Data processing and cloud computing. It also provides an overview of different programming models and cloud-based deployment models. The book's second section examines the usage of advanced Big Data processing techniques in different domains, including semantic web, graph processing, and stream processing. The third section discusses advanced topics of Big Data processing such as consistency management, privacy, and security. Supplying a comprehensive summary from both the research and applied perspectives, the book covers recent research discoveries and applications, making it an ideal reference for a wide range of audiences, including researchers and academics working on databases, data mining, and web scale data processing. After reading this book, you will gain a fundamental understanding of how to use Big Data-processing tools and techniques effectively across application domains. Coverage includes cloud data management architectures, big data analytics visualization, data management, analytics for vast amounts of unstructured data, clustering, classification, link analysis of big data, scalable data mining, and machine learning techniques.

Written by two very experienced instructors, with more than thirty years of teaching experience between them; Presents material that is grounded in practical applications that are representative of the problems researchers encounter in real life; Teaches readers the core features of modern JavaScript; Covers programming with callbacks and promises; Describes how to build data services and data visualization;

As the complexity of today s networked computer systems grows, they become increasingly difficult to understand, predict, and control. Addressing these challenges requires new approaches to building these systems. Adaptive, Dynamic, and Resilient Systems supplies readers with various perspectives of the critical infrastructure that systems of networked computers rely on. It introduces the key issues, describes their interrelationships, and presents new research in support of these areas.
The book presents the insights of a different group of international experts in each chapter. Reporting on recent developments in adaptive systems, it begins with a survey of application fields. It explains the requirements of such fields in terms of adaptation and resilience. It also provides some abstract relationship graphs that illustrate the key attributes of distributed systems to supply you with a better understanding of these factors and their dependencies.
The text examines resilient adaptive systems from the perspectives of mobile, infrastructure, and enterprise systems and protecting critical infrastructure. It details various approaches for building adaptive, dynamic, and resilient systems including agile, grid, and autonomic computing; multi-agent-based and biologically inspired approaches; and self-organizing systems.
The book includes many stories of successful applications that illustrate a diversified range of cutting-edge approaches. It concludes by covering related topics and techniques that can help to boost adaptation and resilience in your systems."

Most organizations with a web presence build and operate APIs; the doorway for customers to interact with the company's services. Designing, building, and managing these critical programs affect everyone in the organization, from engineers and product owners to C-suite executives. But the real challenge for developers and solution architects is creating an API platform from the ground up. With this practical book, you'll learn strategies for building and testing REST APIs that use API gateways to combine offerings at the microservice level. Authors James Gough, Daniel Bryant, and Matthew Auburn demonstrate how simple additions to this infrastructure can help engineers and organizations migrate to the cloud; and open the opportunity to connect internal services using technologies like a service mesh. Learn API fundamentals and architectural patterns for building an API platform Explore evolving trends such as asynchronous and streaming APIs Help drive your API program by performing an informed architectural role Build and configure key components of an API platform Deploy gateways and service meshes based on case studies Understand core security and vulnerabilities in API architecture Secure data and services using OAuth 2.0, TLS, and web application firewalls

Whether you need a new tool or just inspiration, "Seven Web Frameworks in Seven Weeks" explores modern options, giving you a taste of each with ideas that will help you create better apps. You'll see frameworks that leverage modern programming languages, employ unique architectures, live client-side instead of server-side, or embrace type systems. You'll see everything from familiar Ruby and JavaScript to the more exotic Erlang, Haskell, and Clojure. The rapid evolution of web apps demands innovative solutions: this survey of frameworks and their unique perspectives will inspire you and get you thinking in new ways to meet the challenges you face daily. This book covers seven web frameworks that are influencing modern web applications and changing web development: Sinatra, CanJS, AngularJS, Ring, Webmachine, Yesod, Immutant. Each of these web frameworks brings unique and powerful ideas to bear on building apps. Embrace the simplicity of Sinatra, which sheds the trappings of large frameworks and gets back to basics with Ruby. Live in the client with CanJS, and create apps with JavaScript in the browser. Be declarative with AngularJS; say what you want, not how to do it, with a mixture of declarative HTML and JavaScript. Turn the web into data with Ring, and use Clojure to make data your puppet. Become a master of advanced HTTP with Webmachine, and focus the power of Erlang. Prove web theorems with Yesod; see how Haskell's advanced type system isn't just for academics. Develop in luxury with Immutant, an enlightened take on the enterprise framework."Seven Web Frameworks" will influence your work, no matter which framework you currently use. Welcome to a wider web.What You Need: You'll need Windows, MacOS X or Linux, along with your favorite web browser. Each chapter will cover what you need to download and which language versions are required.

Essential comprehensive coverage of the fundamentals of requirements engineering

Requirements engineering (RE) deals with the variety of prerequisites that must be met by a software system within an organization in order for that system to produce stellar results. With that explanation in mind, this must-have book presents a disciplined approach to the engineering of high-quality requirements. Serving as a helpful introduction to the fundamental concepts and principles of requirements engineering, this guide offers a comprehensive review of the aim, scope, and role of requirements engineering as well as best practices and flaws to avoid. Shares state-of-the-art techniques for domain analysis, requirements elicitation, risk analysis, conflict management, and moreFeatures in-depth treatment of system modeling in the specific context of engineering requirementsPresents various forms of reasoning about models for requirements quality assuranceDiscusses the transitions from requirements to software specifications to software architecture

In addition, case studies are included that complement the many examples provided in the book in order to show you how the described method and techniques are applied in practical situations.

When it comes to data analytics, it pays tothink big. PySpark blends the powerful Spark big data processing engine withthe Python programming language to provide a data analysis platform that can scaleup for nearly any task. Data Analysis with Python and PySpark is yourguide to delivering successful Python-driven data projects. Data Analysis with Python and PySpark is a carefully engineered tutorial that helps you use PySpark to deliver your data-driven applications at any scale. This clear and hands-on guide shows you how to enlarge your processing capabilities across multiple machines with data from any source, ranging from Had oop-based clusters to Excel worksheets. You'll learn how to break down big analysis tasks into manageable chunks and how to choose and use the best PySpark data abstraction for your unique needs. The Spark data processing engine is an amazing analytics factory: raw data comes in,and insight comes out. Thanks to its ability to handle massive amounts of data distributed across a cluster, Spark has been adopted as standard by organizations both big and small. PySpark, which wraps the core Spark engine with a Python-based API, puts Spark-based data pipelines in the hands of programmers and data scientists working with the Python programming language. PySpark simplifies Spark's steep learning curve, and provides a seamless bridge between Spark and an ecosystem of Python-based data science tools.

The dependence on quality software in all areas of life is what makes software engineering a key discipline for today's society. Thus, over the last few decades it has been increasingly recognized that it is particularly important to demonstrate the value of software engineering methods in real-world environments, a task which is the focus of empirical software engineering. One of the leading protagonists of this discipline worldwide is Prof. Dr. Dr. h.c. Dieter Rombach, who dedicated his entire career to empirical software engineering. For his many important contributions to the field he has received numerous awards and recognitions, including the U.S. National Science Foundation's Presidential Young Investigator Award and the Cross of the Order of Merit of the Federal Republic of Germany. He is a Fellow of both the ACM and the IEEE Computer Society. This book, published in honor of his 60th birthday, is dedicated to Dieter Rombach and his contributions to software engineering in general, as well as to empirical software engineering in particular. This book presents invited contributions from a number of the most internationally renowned software engineering researchers like Victor Basili, Barry Boehm, Manfred Broy, Carlo Ghezzi, Michael Jackson, Leon Osterweil, and, of course, by Dieter Rombach himself. Several key experts from the Fraunhofer IESE, the institute founded and led by Dieter Rombach, also contributed to the book. The contributions summarize some of the most important trends in software engineering today and outline a vision for the future of the field. The book is structured into three main parts. The first part focuses on the classical foundations of software engineering, such as notations, architecture, and processes, while the second addresses empirical software engineering in particular as the core field of Dieter Rombach's contributions. Finally, the third part discusses a broad vision for the future of software engineering.

The safety case (SC) is one of the railway industry's most important deliverables for creating confidence in their systems. This is the first book on how to write an SC, based on the standard EN 50129:2003. Experience has shown that preparing and understanding an SC is difficult and time consuming, and as such the book provides insights that enhance the training for writing an SC. The book discusses both "regular" safety cases and agile safety cases, which avoid too much documentation, improve communication between the stakeholders, allow quicker approval of the system, and which are important in the light of rapidly changing technology. In addition, it discusses the necessity of frequently updating software due to market requirements, changes in requirements and increased cyber-security threats. After a general introduction to SCs and agile thinking in chapter 1, chapter 2 describes the majority of the roles that are relevant when developing railway-signaling systems. Next, chapter 3 provides information related to the assessment of signaling systems, to certifications based on IEC 61508 and to the authorization of signaling systems. Chapter 4 then explains how an agile safety plan satisfying the requirements given in EN 50126-1:1999 can be developed, while chapter 5 provides a brief introduction to safety case patterns and notations. Lastly, chapter 6 combines all this and describes how an (agile) SC can be developed and what it should include. To ensure that infrastructure managers, suppliers, consultants and others can take full advantage of the agile mind-set, the book includes concrete examples and presents relevant agile practices. Although the scope of the book is limited to signaling systems, the basic foundations for (agile) SCs are clearly described so that they can also be applied in other cases.

In areas such as military, security, aerospace, and disaster management, the need for performance optimization and interoperability among heterogeneous systems is increasingly important. Model-driven engineering, a paradigm in which the model becomes the actual software, offers a promising approach toward systems of systems (SoS) engineering. However, model-driven engineering has largely been unachieved in complex dynamical systems and netcentric SoS, partly because modeling and simulation (M&S) frameworks are stove-piped and not designed for SoS composability. Addressing this gap, Netcentric System of Systems Engineering with DEVS Unified Process presents a methodology for realizing the model-driven engineering vision and netcentric SoS using DEVS Unified Process (DUNIP). The authors draw on their experience with Discrete Event Systems Specification (DEVS) formalism, System Entity Structure (SES) theory, and applying model-driven engineering in the context of a netcentric SoS. They describe formal model-driven engineering methods for netcentric M&S using standards-based approaches to develop and test complex dynamic models with DUNIP. The book is organized into five sections: Section I introduces undergraduate students and novices to the world of DEVS. It covers systems and SoS M&S as well as DEVS formalism, software, modeling language, and DUNIP. It also assesses DUNIP with the requirements of the Department of Defense's (DoD) Open Unified Technical Framework (OpenUTF) for netcentric Test and Evaluation (T&E). Section II delves into M&S-based systems engineering for graduate students, advanced practitioners, and industry professionals. It provides methodologies to apply M&S principles to SoS design and reviews the development of executable architectures based on a framework such as the Department of Defense Architecture Framework (DoDAF). It also describes an approach for building netcentric knowledge-based contingency-driven systems. Section III guides graduate students, advanced DEVS users, and industry professionals who are interested in building DEVS virtual machines and netcentric SoS. It discusses modeling standardization, the deployment of models and simulators in a netcentric environment, event-driven architectures, and more. Section IV explores real-world case studies that realize many of the concepts defined in the previous chapters. Section V outlines the next steps and looks at how the modeling of netcentric complex adaptive systems can be attempted using DEVS concepts. It touches on the boundaries of DEVS formalism and the future work needed to utilize advanced concepts like weak and strong emergence, self-organization, scale-free systems, run-time modularity, and event interoperability. This groundbreaking work details how DUNIP offers a well-structured, platform-independent methodology for the modeling and simulation of netcentric system of systems.

Guides professionals and students through the rapidly growing field of machine learning with hands-on examples in the popular R programming language Machine learning--a branch of Artificial Intelligence (AI) which enables computers to improve their results and learn new approaches without explicit instructions--allows organizations to reveal patterns in their data and incorporate predictive analytics into their decision-making process. Practical Machine Learning in R provides a hands-on approach to solving business problems with intelligent, self-learning computer algorithms. Bestselling author and data analytics experts Fred Nwanganga and Mike Chapple explain what machine learning is, demonstrate its organizational benefits, and provide hands-on examples created in the R programming language. A perfect guide for professional self-taught learners or students in an introductory machine learning course, this reader-friendly book illustrates the numerous real-world business uses of machine learning approaches. Clear and detailed chapters cover data wrangling, R programming with the popular RStudio tool, classification and regression techniques, performance evaluation, and more. Explores data management techniques, including data collection, exploration and dimensionality reduction Covers unsupervised learning, where readers identify and summarize patterns using approaches such as apriori, eclat and clustering Describes the principles behind the Nearest Neighbor, Decision Tree and Naive Bayes classification techniques Explains how to evaluate and choose the right model, as well as how to improve model performance using ensemble methods such as Random Forest and XGBoost Practical Machine Learning in R is a must-have guide for business analysts, data scientists, and other professionals interested in leveraging the power of AI to solve business problems, as well as students and independent learners seeking to enter the field.

This OCP Oracle Certified Professional Java SE 11 Developer Complete Study Guide was published before Oracle announced major changes to its OCP certification program and the release of the new Developer 1Z0-819 exam. No matter the changes, rest assured this Study Guide covers everything you need to prepare for and take the exam. NOTE: The OCP Java SE 11 Programmer I Exam 1Z0-815 and Programmer II Exam 1Z0-816 have been retired (as of October 1, 2020), and Oracle has released a new Developer Exam 1Z0-819 to replace the previous exams. The Upgrade Exam 1Z0-817 remains the same. This is the most comprehensive prep guide available for the OCP Oracle Certified Professional Java SE 11 Developer certification--it covers Exam 1Z0-819 and the Upgrade Exam 1Z0-817 (as well as the retired Programmer I Exam 1Z0-815 and Programmer II Exam 1Z0-816)! Java is widely-used for backend cloud applications, Software as a Service applications (SAAS), and is the principal language used to develop Android applications. This object-oriented programming language is designed to run on all platforms that support Java without the need for recompilation. Oracle Java Programmer certification is highly valued by employers throughout the technology industry. The OCP Oracle Certified Professional Java SE 11 Developer Complete Study Guide in an indispensable resource for anyone preparing for the certification exam. This fully up-to-date guide covers 100% of exam objectives for Exam 1Z0-819 and Upgrade Exam 1Z0-817 (in addition to the previous Exam 1Z0-815 and Exam 1Z0-816). In-depth chapters present clear, comprehensive coverage of the functional-programming knowledge necessary to succeed. Each chapter clarifies complex material while reinforcing your understanding of vital exam topics. Also included is access to Sybex's superior online interactive learning environment and test bank that includes self-assessment tests, chapter tests, bonus practice exam questions, electronic flashcards, and a searchable glossary of important terms. The ultimate study aid for the challenging OCP exams, this popular guide: Helps you master the changes in depth, difficultly, and new module topics of the latest OCP exams Covers all exam objectives such as Java arrays, primitive data types, string APIs, objects and classes, operators and decision constructs, and applying encapsulation Allows developers to catch up on all of the newest Java material like lambda expressions, streams, concurrency, annotations, generics, and modules Provides practical methods for building Java applications, handling exceptions, programming through interfaces, secure coding in Java SE, and more Enables you to gain the information, understanding, and practice you need to pass the OCP exams The OCP Oracle Certified Professional Java SE 11 Developer Complete Study Guide is a must-have book for certification candidates needing to pass these challenging exams, as well as junior- to senior-level developers who use Java as their primary programming language.

This book constitutes the refereed proceedings of the IFIP WG 8.6 International Working Conference on Governance and Sustainability in Information Systems, held in Hamburg, Germany, in September 2011. The 14 revised full papers and 16 research in progress and practice papers presented were carefully reviewed and selected from 47 submissions. The full research papers are organized in the following topical sections:governance, sustainability, design themes, customer and user integration, and future subjects.

OCUP 2 Certification Guide: Preparing for the OMG Certified UML 2.5 Professional 2 Foundation Exam both teaches UML (R) 2.5 and prepares candidates to become certified. UML (R) (Unified Modeling Language) is the most popular graphical language used by software analysts, designers, and developers to model, visualize, communicate, test, and document systems under development. UML (R) 2.5 has recently been released, and with it a new certification program for practitioners to enhance their current or future career opportunities. There are three exam levels: Foundation, Intermediate, and Advanced. The exam covered in this book, Foundation, is a prerequisite for the higher levels. Author Michael Jesse Chonoles is a lead participant in the current OCUP 2 program-not only in writing and reviewing all the questions, but also in designing the goals of the program. This book distills his experience in modeling, mentoring, and training. Because UML (R) is a sophisticated language, with 13 diagram types, capable of modeling any type of modern software system, it takes users some time to become proficient. This effective resource will explain the material in the Foundation exam and includes many practice questions for the candidate, including sample problems similar to those found in the exam, and detailed explanations of why correct answers are correct and why wrong answers are wrong.

Distributed across servers, difficult to test, and resistant to modification-modern software is complex. Grokking Simplicity is a friendly, practical guide that will change the way you approach software design and development. It introduces a unique approach to functional programming that explains why certain features of software are prone to complexity, and teaches you the functional techniques you can use to simplify these systems so that they're easier to test and debug. Available in PDF (ePub, kindle, and liveBook formats coming soon). about the technologyEven experienced developers struggle with software systems that sprawl across distributed servers and APIs, are filled with redundant code, and are difficult to reliably test and modify. Adopting ways of thinking derived from functional programming can help you design and refactor your codebase in ways that reduce complexity, rather than encouraging it. Grokking Simplicity lays out how to use functional programming in a professional environment to write a codebase that's easier to test and reuse, has fewer bugs, and is better at handling the asynchronous nature of distributed systems. about the bookIn Grokking Simplicity, you'll learn techniques and, more importantly, a mindset that will help you tackle common problems that arise when software gets complex. Veteran functional programmer Eric Normand guides you to a crystal-clear understanding of why certain features of modern software are so prone to complexity and introduces you to the functional techniques you can use to simplify these systems so that they're easier to read, test, and debug. Through hands-on examples, exercises, and numerous self-assessments, you'll learn to organize your code for maximum reusability and internalize methods to keep unwanted complexity out of your codebase. Regardless of the language you're using, the ways of thinking in this book will help recognize problematic code and tame even the most complex software. what's inside Apply functional programming principles to reduce codebase complexity Work with data transformation pipelines for code that's easier to test and reuse Tools for modeling time to simplify asynchrony 60 exercises and 100 questions to test your knowledge about the readerFor experienced programmers. Examples are in JavaScript. about the author Eric Normand has been a functional programmer since 2001 and has been teaching functional programming online and in person since 2007. Visit LispCast.com to see more of his credentials.