Most security books on Java focus on cryptography and access control, but exclude key aspects such as coding practices, logging, and web application risk assessment. Encapsulating security requirements for web development with the Java programming platform, Secure Java: For Web Application Development covers secure programming, risk assessment, and threat modeling explaining how to integrate these practices into a secure software development life cycle. From the risk assessment phase to the proof of concept phase, the book details a secure web application development process. The authors provide in-depth implementation guidance and best practices for access control, cryptography, logging, secure coding, and authentication and authorization in web application development. Discussing the latest application exploits and vulnerabilities, they examine various options and protection mechanisms for securing web applications against these multifarious threats. The book is organized into four sections: Provides a clear view of the growing footprint of web applications Explores the foundations of secure web application development and the risk management process Delves into tactical web application security development with Java EE Deals extensively with security testing of web applications This complete reference includes a case study of an e-commerce company facing web application security challenges, as well as specific techniques for testing the security of web applications. Highlighting state-of-the-art tools for web application security testing, it supplies valuable insight on how to meet important security compliance requirements, including PCI-DSS, PA-DSS, HIPAA, and GLBA. The book also includes an appendix that covers the application security guidelines for the payment card industry standards.

A Functional Start to Computing with Python enables students to quickly learn computing without having to use loops, variables, and object abstractions at the start. Requiring no prior programming experience, the book draws on Python's flexible data types and operations as well as its capacity for defining new functions. Along with the specifics of Python, the text covers important concepts of computing, including software engineering motivation, algorithms behind syntax rules, advanced functional programming ideas, and, briefly, finite state machines. Taking a student-friendly, interactive approach to teach computing, the book addresses more difficult concepts and abstractions later in the text. The author presents ample explanations of data types, operators, and expressions. He also describes comprehensions the powerful specifications of lists and dictionaries before introducing loops and variables. This approach helps students better understand assignment syntax and iteration by giving them a mental model of sophisticated data first. Web ResourceThe book's supplementary website at http://functionalfirstpython.com/ provides many ancillaries, including: Interactive flashcards on Python language elements Links to extra support for each chapter Unit testing and programming exercises An interactive Python stepper tool Chapter-by-chapter points Material for lectures

While teaching Java programming at Minnesota State University, the authors noticed that engineering students were enrolling in Java programming courses in order to obtain basic programming skills, but there were no Java books suitable for courses intended for engineers. They realized the need for a comprehensive Java programming tutorial that offers basic programming skills that can be applied in the field of engineering. With this in mind, the authors developed Java Programming for Engineers in order to meet the needs of both engineers and engineering students. The text uses the personal computer as a development platform and assumes no prior programming experience or knowledge. The only skills expected of the reader are basic keyboarding and user-level familiarity with the PC. Topics covered range from mathematical expressions to linear systems to engineering graphics. Chapters on problem solving skills and the designing of engineering applications walk readers through real word problems they might encounter. Divided into two parts, Part 1 is a description of the Java language, of the fundamentals of object orientation, input and output operations, and error handling. Part 2 is about Java programming for engineers. It starts with computer number systems, fixed- and variable-precision numeric data, mathematical programming in Java as could be of interest to engineers, and concludes with an overview of Java Graphics.

Praise for the first edition: "The well-written, comprehensive book [is] aiming to become a de facto reference for the language and its features and capabilities. The pace is appropriate for beginners; programming concepts are introduced progressively through a range of examples and then used as tools for building applications in various domains, including sophisticated data structures and algorithms Highly recommended. Students of all levels, faculty, and professionals/practitioners.D. Papamichail, University of Miami in CHOICE Magazine Mark Lewis Introduction to the Art of Programming Using Scala was the first textbook to use Scala for introductory CS courses. Fully revised and expanded, the new edition of this popular text has been divided into two books. Object-Orientation, Abstraction, and Data Structures Using Scala, Second Edition is intended to be used as a textbook for a second or third semester course in Computer Science. The Scala programming language provides powerful constructs for expressing both object orientation and abstraction. This book provides students with these tools of object orientation to help them structure solutions to larger, more complex problems, and to expand on their knowledge of abstraction so that they can make their code more powerful and flexible. The book also illustrates key concepts through the creation of data structures, showing how data structures can be written, and the strengths and weaknesses of each one. Libraries that provide the functionality needed to do real programming are also explored in the text, including GUIs, multithreading, and networking. The book is filled with end-of-chapter projects and exercises, and the authors have also posted a number of different supplements on the book website. Video lectures for each chapter in the book are also available on YouTube. The videos show constr

Written by an expert in the development of GPS systems with digital maps and navigation, Programming GPS and OpenStreetMap Applications with Java: The RealObject Application Framework provides a concrete paradigm for object-oriented modeling and programming. It presents a thorough introduction to the use of available global positioning data for the development of applications involving digital maps. The author first describes the different formats of GPS data and digital maps and shows how to use recorded GPS traces to replay and display this data on a digital map. Then, he works through in detail the processing steps of obtaining dedicated data from OpenStreetMaps and how to extract a network for a simple navigation application. For each topic covered-GPS data, OpenStreetMaps, and navigation-Java code is developed that can easily be adapted to the readers' needs and locality. Finally, all components are put together in a sample computer-game application modeled on the well-known board game, Scotland Yard. The computer game is intended to be a basis from which readers can develop and customize their own application for their desired geographical area. The developed application can be "published" on the Internet and made available for interactive multiplayer competition. This book provides a fun and interesting way to learn distributed programming with Java and real-world data. Open-source software is available on a companion website at www.roaf.de

The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.Exploring Neural Networks with C# presents the important properties of neural networks while keeping the complex mathematics to a minimum. Explaining how to build and use neural networks, it presents complicated information about neural networks structure, functioning, and learning in a manner that is easy to understand.Taking a "learn by doing" approach, the book is filled with illustrations to guide you through the mystery of neural networks. Examples of experiments are provided in the text to encourage individual research. Online access to C# programs is also provided to help you discover the properties of neural networks.Following the procedures and using the programs included with the book will allow you to learn how to work with neural networks and evaluate your progress. You can download the programs as both executable applications and C# source code from http://home.agh.edu.pl/~tad//index.php?page=programyandlang=en

As one of the results of an ambitious project, this handbook provides a well-structured directory of globally available software tools in the area of Integrated Computational Materials Engineering (ICME). The compilation covers models, software tools, and numerical methods allowing describing electronic, atomistic, and mesoscopic phenomena, which in their combination determine the microstructure and the properties of materials. It reaches out to simulations of component manufacture comprising primary shaping, forming, joining, coating, heat treatment, and machining processes. Models and tools addressing the in-service behavior like fatigue, corrosion, and eventually recycling complete the compilation. An introductory overview is provided for each of these different modelling areas highlighting the relevant phenomena and also discussing the current state for the different simulation approaches. A must-have for researchers, application engineers, and simulation software providers seeking a holistic overview about the current state of the art in a huge variety of modelling topics. This handbook equally serves as a reference manual for academic and commercial software developers and providers, for industrial users of simulation software, and for decision makers seeking to optimize their production by simulations. In view of its sound introductions into the different fields of materials physics, materials chemistry, materials engineering and materials processing it also serves as a tutorial for students in the emerging discipline of ICME, which requires a broad view on things and at least a basic education in adjacent fields.

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.

Further Electrical and Electronic Principles is a core text for pre-degree courses in electrical and electronic engineering courses. The coverage of this new edition has been brought in line with the specialist unit 'Further Electrical Principles' of the 2007 BTEC National Engineering specification from Edexcel. As the book follows a logical topic progression rather than a particular syllabus, it is also suitable for other Level 3 students on vocational courses such as Vocational AS/A Level, City & Guilds courses and NVQs.More advanced material has also been included, making this text also suitable for HNC/HND and foundation degree courses.Each chapter starts with learning outcomes tied to the syllabus. All theory is explained in detail and backed up with numerous worked examples. Students can test their understanding with end of chapter assignment questions for which answers are provided. The book also includes suggested practical assignments and handy summaries of equations. In this new edition, the layout has been improved and colour has been added to make the book more accessible for students.The textbook is supported with a free companion website featuring supplementary worked examples and additional chapters.http://books.elsevier.com/companions/9780750687478

"For software developers of all experience levels looking to improve their results, and design and implement domain-driven enterprise applications consistently with the best current state of professional practice, Implementing Domain-Driven Design will impart a treasure trove of knowledge hard won within the DDD and enterprise application architecture communities over the last couple decades." -Randy Stafford, Architect At-Large, Oracle Coherence Product Development "This book is a must-read for anybody looking to put DDD into practice." -Udi Dahan, Founder of NServiceBus Implementing Domain-Driven Design presents a top-down approach to understanding domain-driven design (DDD) in a way that fluently connects strategic patterns to fundamental tactical programming tools. Vaughn Vernon couples guided approaches to implementation with modern architectures, highlighting the importance and value of focusing on the business domain while balancing technical considerations. Building on Eric Evans' seminal book, Domain-Driven Design, the author presents practical DDD techniques through examples from familiar domains. Each principle is backed up by realistic Java examples-all applicable to C# developers-and all content is tied together by a single case study: the delivery of a large-scale Scrum-based SaaS system for a multitenant environment. The author takes you far beyond "DDD-lite" approaches that embrace DDD solely as a technical toolset, and shows you how to fully leverage DDD's "strategic design patterns" using Bounded Context, Context Maps, and the Ubiquitous Language. Using these techniques and examples, you can reduce time to market and improve quality, as you build software that is more flexible, more scalable, and more tightly aligned to business goals. Coverage includes Getting started the right way with DDD, so you can rapidly gain value from it Using DDD within diverse architectures, including Hexagonal, SOA, REST, CQRS, Event-Driven, and Fabric/Grid-Based Appropriately designing and applying Entities-and learning when to use Value Objects instead Mastering DDD's powerful new Domain Events technique Designing Repositories for ORM, NoSQL, and other databases

This book offers a new Modular Petri Net as a solution to the vast Petri net models. It presents some approaches centering around modules (known as "Petri modules"). The goal of this book is to introduce a methodology in which Petri nets are moved to a new level. In this new level, large Petri net models are made of Petri modules, which are independent and run on different computers. This book also contains the literature study on modular Petri nets and definitions for the newer Petri modules. Also, algorithms for extracting Petri modules, and algorithms for connecting Petri modules, and applications are given in this book. Besides, the ideas and algorithms given in this book are implemented in the software General-purpose Petri Net Simulator (GPenSIM). Hence, with the use of this book the readers/users would be able to know that real-life discrete event systems could be modeled, analyzed, and performance-optimized with GPenSIM.

This easy-to-use, classroom-tested textbook covers the C programming language for computer science and IT students. Designed for a compulsory fundamental course, it presents the theory and principles of C. More than 500 exercises and examples of progressive difficulty aid students in understanding all the aspects and peculiarities of the C language. The exercises test students on various levels of programming and the examples enhance their concrete understanding of programming know-how. Instructor's manual and PowerPoint slides are available upon qualifying course adoption

Software is one of the most important products in human history and is widely used by all industries and all countries. It is also one of the most expensive and labor-intensive products in human history. Software also has very poor quality that has caused many major disasters and wasted many millions of dollars. Software is also the target of frequent and increasingly serious cyber-attacks. Among the reasons for these software problems is a chronic lack of reliable quantified data. This reference provides quantified data from many countries and many industries based on about 26,000 projects developed using a variety of methodologies and team experience levels. The data has been gathered between 1970 and 2017, so interesting historical trends are available. Since current average software productivity and quality results are suboptimal, this book focuses on "best in class" results and shows not only quantified quality and productivity data from best-in-class organizations, but also the technology stacks used to achieve best-in-class results. The overall goal of this book is to encourage the adoption of best-in-class software metrics and best-in-class technology stacks. It does so by providing current data on average software schedules, effort, costs, and quality for several industries and countries. Because productivity and quality vary by technology and size, the book presents quantitative results for applications between 100 function points and 100,000 function points. It shows quality results using defect potential and DRE metrics because the number one cost driver for software is finding and fixing bugs. The book presents data on cost of quality for software projects and discusses technical debt, but that metric is not standardized. Finally, the book includes some data on three years of software maintenance and enhancements as well as some data on total cost of ownership.

The International Conference on Communications, Management, and Information Technology (ICCMIT'16) provides a discussion forum for scientists, engineers, educators and students about the latest discoveries and realizations in the foundations, theory, models and applications of systems inspired on nature, using computational intelligence methodologies, as well as in emerging areas related to the three tracks of the conference: Communication Engineering, Knowledge, and Information Technology. The best 25 papers to be included in the book will be carefully reviewed and selected from numerous submissions, then revised and expanded to provide deeper insight into trends shaping future ICT.

Attention to design patterns is unquestionably growing in software engineering because there is a strong belief that using made to measure solutions for solving frequently occurring problems encountered throughout the design phase greatly reduces the total cost and the time of developing software products. Stable Design Patterns for Software and Systems presents a new and fresh approach for creating stable, reusable, and widely applicable design patterns. It deals with the concept of stable design patterns based on software stability as a contemporary approach for building stable and highly reusable and widely applicable design patterns. This book shows that a formation approach to discovering and creating stable design patterns accords with Alexander's current understanding of architectural patterns. Stable design patterns are a type of knowledge pattern that underline human problem solving methods and appeal to the pattern community. This book examines software design patterns with respect to four central themes: How do we develop a solution for the problem through software stability concepts? This book offers a direct application of using software stability concepts for modeling solutions. How do we achieve software stability over time and design patterns that are effective to use? What are the unique roles of stable design patterns in modeling the accurate solution of the problem at hand and in providing stable and undisputed design for such problems? This book enumerates a complete and domain-less list of stable patterns that are useful for designing and modeling solutions for frequently recurring problems. What is the most efficient way to document the stable design patters to ensure efficient reusability? This book is an extension to the contemporary templates that are used in documenting design patterns. This book gives a pragmatic and a novel approach toward understanding the problem domain and in proposing stable solutions for engineering stable software systems, components, and frameworks.

In business, driving value is a key strategy and typically starts at the top of an organization. In today's digital age, driving software value is also an important, and often overlooked, key strategy. Executives, and the corporate board, need to expect the highest level of business value from the software the organization is developing, buying, and selling. In today's digital transformation marketplace, it is imperative that organizations start driving business value from software development initiatives. For many years, the cost of software development challenged organizations with questions such as: How do we allocate software development costs? Should these costs be considered an overhead expense? Are we getting the most value possible for our investment? A fundamental problem has been built into these questions - the focus on cost. In almost every other part of the organization, maximizing profit or, in the case of a not-for-profit, maximizing the funds available, provides a clear focus with metrics to determine success or failure. In theory, simply aligning software spending with the maximizing profit goals should be sufficient to avoid any questions about value for money. Unfortunately, this alignment hasn't turned out to be so simple, and the questions persist, particularly at the strategic or application portfolio level. In this book, Michael D.S. Harris describes how a software business value culture-one where all stakeholders, including technology and business-have a clear understanding of the goals and expected business value from software development. The book shows readers how they can transform software development from a cost or profit center to a business value center. Only a culture of software as a value center enables an organization to constantly maximize business value flow through software development. If your organization is starting to ask how it can change software from a cost-center to a value-center, this book is for you.

The Pacific Symposium on Biocomputing (PSB) 2020 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2020 will be held on January 3 -7, 2020 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2020 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.

This book provides techniques for offshore center managers and head office managers to motivate and manage globally distributed teams, which are spread across the offshore center and the head office, and thereby achieve higher productivity. Readers learn how to integrate the offshore center with the head office to make the offshore team an extension of the head office. While integrating teams with the head office, offshore center managers can still retain independence and authority to meet team aspirations. The book provides insight into devising new organizational structures to balance the authority and responsibilities of offshore center and head office managers. Head office managers responsible for managing globally distributed projects learn how to achieve a higher success rate on their projects and be better rewarded for their efforts in offshoring. Head office managers also learn techniques to make more significant contributions in their expatriate assignments to the offshore center. This book guides both the offshore center managers and the head office managers to fully realize the potential of the offshore center, which can result in higher revenues and profitability.

Going where no book on software measurement and metrics has previously gone, this critique thoroughly examines a number of bad measurement practices, hazardous metrics, and huge gaps and omissions in the software literature that neglect important topics in measurement. The book covers the major gaps and omissions that need to be filled if data about software development is to be useful for comparisons or estimating future projects. Among the more serious gaps are leaks in reporting about software development efforts that, if not corrected, can distort data and make benchmarks almost useless and possibly even harmful. One of the most common leaks is that of unpaid overtime. Software is a very labor-intensive occupation, and many practitioners work very long hours. However, few companies actually record unpaid overtime. This means that software effort is underreported by around 15%, which is too large a value to ignore. Other sources of leaks include the work of part-time specialists who come and go as needed. There are dozens of these specialists, and their combined effort can top 45% of total software effort on large projects. The book helps software project managers and developers uncover errors in measurements so they can develop meaningful benchmarks to estimate software development efforts. It examines variations in a number of areas that include: Programming languages Development methodology Software reuse Functional and nonfunctional requirements Industry type Team size and experience Filled with tables and charts, this book is a starting point for making measurements that reflect current software development practices and realities to arrive at meaningful benchmarks to guide successful software projects.

The book is a focused survey on probabilistic program semantics, conceived to tell a coherent story with a uniform notation. It is grouped into three themes: Part I is for 'users' of the techniques who will be developing actual programs; Part II gives mathematical foundations intended for those studying exactly how it was done and how to build semantic structures/models in their own work; and Part III describes a very 'hot' research direction, temporal logic and model checking. Topics and features: - introduces readers to very up-to-date research in the mathematics of rigorous development of randomized (probabilistic) algorithms- illustrates by example the typical steps necessary in computer science to build a mathematical model of any programming paradigm- presents results of a large and integrated body of research in the area of 'quantitative' program logics. An advanced research survey monograph, integrating three major topic areas.

Declining test scores, burgeoning drop-out rates, poor showings in international comparisons-the malaise of public education seems to grow everyday. In this context, technology has emerged as one of the hopes of a renewed educational enterprise. Yet modern information-processing technologies have proved far from a panacea for the ills of education. Software Goes to School describes why that is the case in its consideration of three broad themes. The first part of the book addresses the question of what it means to understand. What constitutes understanding something? What are our principle resources in teaching for understanding? The second part of the book focuses front and centre on what technology can offer in teaching for understanding. Individual chapters examine how technologies afford new ways of representing complex concepts and make available new means by which students can manipulate abstract entities in a "hands-on" way. The last part of the book discusses the complexities of realistic educational settings, explores what happens when technology-based innovations are introduced, and examines the means by which a pedagogy of understanding can take root and thrive. Authored by an eminent group of researchers, this book offers numerous practical guidelines on how computers and software can work together for the betterment of the teaching process. Students and professionals in educational psychology, developmental psychology, and educational computing-as well as concerned parents-will want to read this stimulating new work.

Winner of 2020 PMI David I. Cleland Project Management Literature Award This book is a complete project management toolkit for project leaders in business, research and industry. Projects are approved and financed to generate benefits. Project Management: A Benefit Realisation Approach proposes a complete framework that supports this objective - from project selection and definition, through execution, and beyond implementation of deliverables until benefits are secured. The book is the first to explain the creation of organisational value by suggesting a complete, internally-consistent and theoretically rigorous benefit-focused project management methodology, supported with an analytical technique: benefit engineering. Benefit engineering offers a practical approach to the design and maintenance of an organisation's project portfolio. Building upon the authors' earlier successful book, Project Management for the Creation of Organisational Value, this comprehensively revised and expanded new book contains the addition of new chapters on project realisation. The book offers a rigorous explanation of how benefits emerge from a project. This approach is developed and strengthened - resulting in a completely client-oriented view of a project. Senior executives, practitioners, students and academics will find in this book a comprehensive guide to the conduct of projects, which includes robust models, a set of consistent principles, an integrated glossary, enabling tools, illustrative examples and case studies.

This is the first book to seriously address the disconnection between nimble Agile teams and other groups in the enterprise, including enterprise architecture, the program management office (PMO), human resources, and even business executives. When an enterprise experiments with practice improvements, software development teams often jump on board with excitement, while other groups are left to wonder how they will fit in. We address how these groups can adapt to Agile teams. More importantly, we show how many Agile teams cause their own problems, damaging scalability and sustainability, by requiring special treatment, and by failing to bridge the gaps between themselves and other groups. We call this phenomenon "Agile illth." Adopting a set of "best practices" is not enough. All of us, Agile teams and the corporate groups, must change our intentions and worldviews to be more compatible with the success of the enterprise. Join us on the journey to enterprise agility. It is a crooked path, fraught with danger, confusion and complexity. It is the only way to reach the pinnacles we hope to experience in the form of better business value delivered faster for less cost.

Software Engineering for Science provides an in-depth collection of peer-reviewed chapters that describe experiences with applying software engineering practices to the development of scientific software. It provides a better understanding of how software engineering is and should be practiced, and which software engineering practices are effective for scientific software. The book starts with a detailed overview of the Scientific Software Lifecycle, and a general overview of the scientific software development process. It highlights key issues commonly arising during scientific software development, as well as solutions to these problems. The second part of the book provides examples of the use of testing in scientific software development, including key issues and challenges. The chapters then describe solutions and case studies aimed at applying testing to scientific software development efforts. The final part of the book provides examples of applying software engineering techniques to scientific software, including not only computational modeling, but also software for data management and analysis. The authors describe their experiences and lessons learned from developing complex scientific software in different domains. About the Editors Jeffrey Carver is an Associate Professor in the Department of Computer Science at the University of Alabama. He is one of the primary organizers of the workshop series on Software Engineering for Science (http://www.SE4Science.org/workshops). Neil P. Chue Hong is Director of the Software Sustainability Institute at the University of Edinburgh. His research interests include barriers and incentives in research software ecosystems and the role of software as a research object. George K. Thiruvathukal is Professor of Computer Science at Loyola University Chicago and Visiting Faculty at Argonne National Laboratory. His current research is focused on software metrics in open source mathematical and scientific software.

"Not only for MacOS and Linux users, but also a great resource for Windows PS users." - Bruce Bergman Learn PowerShell in a Month of Lunches: Covers Windows, Linux, and macOS is a task-focused tutorial for administering Linux and macOS systems using Microsoft PowerShell. Adapted by PowerShell team members Travis Plunk and Tyler Leonhardt from the bestselling Learn Windows PowerShell in a Month of Lunches by community legends Don Jones and Jeffrey Hicks, it features Linux-based examples covering core language features and admin tasks. Designed for busy IT professionals, this innovative guide will take you from the basics to PowerShell proficiency through 25 tutorials you can do in your lunch break. about the technology The PowerShell scripting language and administrative shell was initially created for Windows, providing a high-quality command-line interface and awesome automation features. As part of Microsoft's ongoing strategy to support non-Windows platforms with its Azure cloud service and .NET Core framework, PowerShell now runs on Linux and macOS. Like Bash, PowerShell can execute and script nearly any aspect of Linux, so you can easily manage repetitive daily tasks, servers, Cloud resources, Continuous Integration pipelines, and more. Because PowerShell is a full-featured programming language, however, it provides capability well beyond traditional shell scripting languages, such as the ability to treat OS components as objects. about the book Learn PowerShell in a Month of Lunches: Covers Windows, Linux, and macOS is a user-friendly tutorial to managing Linux and macOS systems with PowerShell. It's based on the bestselling Learn Windows PowerShell in a Month of Lunches, which has introduced PowerShell to nearly 100,000 readers. You'll learn how PowerShell shapes up to Bash or Python scripting as you write and run simple scripts that automate boring daily tasks. As you progress through the book, you'll use PowerShell to write Continuous Integration Pipelines and manage cloud-based servers. Just set aside one hour a day for a month, and you'll be automating tasks faster than you ever thought possible! what's inside - Why you should use PowerShell on Linux and macOS - Background jobs and automation techniques - Simple scripting to automate repetitive daily tasks - Common syntax and commands cheat sheet - Each lesson takes you an hour or less about the reader For IT professionals comfortable administering Windows or Linux. No previous experience with PowerShell or Bash required. about the author Travis Plunk has been a Software Engineer on various PowerShell teams since 2013, and at Microsoft since 1999. He was involved in open sourcing PowerShell and has worked on the project full time since shortly after the project was announced. James Petty is a Microsoft MVP, and the CEO and Executive Director for the DevOps Collective and PowerShell.org. Tyler Leonhardt has been a Software Engineer on the PowerShell team since 2017, and at Microsoft since 2016. He is a core maintainer of the PowerShell extension for Visual Studio Code. Learn Windows PowerShell in a Month of Lunches was written by PowerShell community legends Don Jones and Jeffrey Hicks, who have years of experience as successful PowerShell trainers.