Apress Access Books

Your framework will be built with Spring-Boot, Gradle, and Junit. And it will support HP QC integration, Allure (TDD, BDD), Extent (BDD), and customized Pdf reporting (TDD, BDD). Extensive utilities are provided, such as HP ALM integration, device management utilities, email reporting, pdf reporting, OCR utility, Log utility, and more! There’s also a special chapter on internationalization/localization testing in multiple languages. After reading this book, you’ll have full confidence in your ability to build new test automation frameworks for yourself. 

What You'll Learn

• Design an enterprise level mobile test automation framework capable of supporting both TDD and BDD 
  
• Work with the latest open source tools and coding best practices 
  
• Build with Spring-Boot, Gradle, and Junit while supporting HP QC integration, Allure, Extent, and customized PDF reporting

Who This Book Is For

Software professionals working in test automation. Recent engineering graduates who have programming knowledge and want to prepare for a role in mobile test automation should also find it helpful.

You will start off learning basic concepts and get a bird's-eye view of the enabling technologies to ensure that you feel comfortable with the tools and terminology. From there, you will learn about some of the more popular options in the .NET ecosystem, understand their attributes and shortcomings, and learn why the Uno Platform is ideal for building a cross-platform application that targets Android, iOS, Windows, WASM (Web Assembly), Linux, and MacOS.

Then, you will follow a product release timeline that takes you through building an application, introducing key concepts at every step of the way. Each section of the book is chock full of tips and edge case documentations for the different platforms.

What You Will Learn

• Manage multi-targeting solutions: specifically, how to handle the different project heads
• Effectively write cross-platform software and handle the edge cases of the different platforms
• Understand the fundamentals of working with Uno Platform WinUI apps
• Explore enterprise-grade application architecture using MVVM
• Understand Dependency Injection and how it applies to application architecture

Who This Book Is For

Developers who understand some basics of C# and object-oriented programming

Build solid software with modern and safe concurrency features. Concurrency is one of the hardest problems in computer science. For years, computer scientists and engineers have developed different strategies for dealing with concurrency. However, the original concurrency primitives are complicated and difficult to understand, and even harder to implement.

You’ll start by exploring why concurrency is hard to implement in a traditional system. Explaining the definition of concurrency and what its primitives are will help you understand why they are hard to use correctly. These concepts will become clearer as you work through the sample projects. The book’s focus then shifts exclusively to the new APIs, helping you understand how the integration of the system with the language itself makes it easier for you to write concurrent code without overstepping the bounds of the concurrency safe zone.

By the end of the book, you’ll have a solid foundation for working safely with concurrent code using the new async/await APIs.

What You'll Learn

• Understand concurrency and its traditional problems
• Work with the new async/await API and all its features, from the basic usage and await keywords, to task groups and async sequences.
• Implement modern and safe concurrent code that you can start using right away

Who This Book Is For 

Experienced iOS developers at a semi-senioror senior level. Knowledge on the Grand Central Dispatch is a bonus, but not required.

• Optimize your resume for applications
• Standard tips for interviewing in software engineer positions
• Become a mentor and leader at your job

Use this practical guide to analyze and troubleshoot SQL Server performance using wait statistics. You'll learn to identify precisely why your queries are running slowly. And you'll know how to measure the amount of time consumed by each bottleneck so you can focus attention on making the largest improvements first. This edition is updated to cover analysis of wait statistics current with SQL Server 2022. Whether you are new to wait statistics, or already familiar with them, this book provides a deeper understanding on how wait statistics are generated and what they mean for your SQL Server instance’s performance. 

The book goes beyond the most common wait types into the more complex and performance-threatening wait types. You’ll learn about per-query wait statistics and session-based wait statistics, and the types of problems they can help you solve. The different wait types are categorized by their area of impact, including CPU, IO, Latching, Locking, and many more.

Clear examples are included to help you gain practical knowledge of why and how specific wait times increase or decrease, how they impact your SQL Server’s performance, and what you can do to improve performance. After reading this book, you won’t want to be without the valuable information that wait statistics provide regarding where you should be spending your limited tuning time to maximize performance and value to your business. 

What You'll Learn

• Understand how the SQL Server engine processes requests
• Identify resource bottlenecks in a running SQL Server instance
• Locate wait statistics information inside DMVs and Query Store
• Analyze the root cause of sub-optimal performance
• Diagnose I/O contention and locking contention
• Benchmark SQL Server performance
• Improve database performance by lowering overall wait time 

Who This Book Is For

Database administrators who want to identify and resolve performance bottlenecks, those who want to learn more about how the SQL Server engine accesses and uses resources inside SQL Server, and administrators concerned with achieving—and knowing they have achieved—optimal performance

Examine the working details for real-world Java programs used for system integration with IBM Software, applying various API libraries (as used by Banking and Insurance companies). This book includes the step-by-step procedure to use the IBM FileNet Case Manager 5.3.3 Case Builder solution and the similar IBM System, IBM Business Automation Workflow to create an Audit System. 

You'll learn how to implement the workflow with a client Java Message Service (JMS) java method developed with Workflow Custom Operations System Step components. Using IBM Cognos Analytics Version 11.2, you'll be able to create new views for IBM Case Manager Analytics for custom time dimensions. The book also explains the SQL code and procedures required to create example Online Analytical Processing (OLAP) cubes with multi-level time dimensions for IBM Case Manager analytics.

IBM Software Systems Integration features the most up to date systems software procedures using tested API calls.

What You Will Learn

• Review techniques for generating custom IBM JMS code
• Create a new custom view for a multi-level time dimension
  
• See how a java program can provide the IBM FileNet document management API calls for content store folder and document replication
• Configure Java components for content engine events
  

Who This Book Is For

• Monitor and resolve production issues in your Kafka clusters
• Provision Kafka clusters with the lowest costs and still handle the required loads
• Perform root cause analyses of issues affecting your Kafka clusters
• Know the ways in which your Kafka cluster can affect its consumers and producers
• Prevent or minimize data loss and delays in data streaming
• Forestall production issues through an understanding of common failure points
• Create checklists for troubleshooting your Kafka clusters when problems occur

This book is an essential guide designed to equip you with the vital tools and knowledge needed to excel in data science. Master the end-to-end process of data collection, processing, validation, and imputation using R, and understand fundamental theories to achieve transparency with literate programming, renv, and Git--and much more. Each chapter is concise and focused, rendering complex topics accessible and easy to understand.

Data Insight Foundations caters to a diverse audience, including web developers, mathematicians, data analysts, and economists, and its flexible structure allows enables you to explore chapters in sequence or navigate directly to the topics most relevant to you.

While examples are primarily in R, a basic understanding of the language is advantageous but not essential. Many chapters, especially those focusing on theory, require no programming knowledge at all. Dive in and discover how to manipulate data, ensure reproducibility, conduct thorough literature reviews, collect data effectively, and present your findings with clarity.

What You Will Learn

• Data Management: Master the end-to-end process of data collection, processing, validation, and imputation using R.
• Reproducible Research: Understand fundamental theories and achieve transparency with literate programming, renv, and Git.
• Academic Writing: Conduct scientific literature reviews and write structured papers and reports with Quarto.
• Survey Design: Design well-structured surveys and manage data collection effectively.
• Data Visualization: Understand data visualization theory and create well-designed and captivating graphics using ggplot2.

Who this Book is For

Career professionals such as research and data analysts transitioning from academia to a professional setting where production quality significantly impacts career progression. Some familiarity with data analytics processes and an interest in learning R or Python are ideal. 

Does getting online seem overwhelmingly difficult?  Are you paying too much for your hosting solution? Have you always wanted to have a blog but don’t know where to start? Do you settle for a Facebook page for your business website but know you need more?  The solution to these problems is choosing the right tools. This book will guide you through the process of setting up a Publii-based publishing platform and hosting your site for free on GitHub. 

Publii is a free, open source, desktop application that runs on Windows, Mac, and Linux and makes building the website or blog you dream of is a simple process.   This book walks you through the process of installing and using Publii, setting up accounts on GitHub and hosting a static blog or website there.  You will gain background insights on here to get no-cost imagery for website, how to leverage AI to generate ideas, outlines, and images. You’ll also review search engine optimization (SEO) best practices to ensure your site is searchable. 

Designing Websites with Publii and GitHub Pages is your roadmap to creating a website and understanding how the publishing workflow works.

What You Will Learn 

• Use text editors such as WYSIWYG, Block, and Markdown
• Make a page from a post.
• Work on advanced processes such as installing themes and plugins
• Manage and back up your data
• Explore GDRP and cooking banner considerations

Who This Book Is For 

Those with limited or no programming or compute skills who want to learn how to set up a website.

This books helps you embark on the journey to master the art of Appium automation, from installation all the way to building a Plugin and Driver. It covers the Appium 3.0 version which is the latest version which involves a complete re-architecture. 

You'll begin by following step-by-step instructions on installing Appium, configuring Node packages, and creating a simple test. In these initial chapters, you'll gain an understanding of Appium Architecture and the command lifecycle. Once you understand the basics, the book will then guide you in testing automation for Android and iOS, both for real devices and for emulators. These chapters also provide instructions on how to run tests in parallel, native shell commands, and how to prepare iOS real devices for test automation. Chapters also cover low-level technical implementations, which will enable you to contribute to Appium and open a way to open-source software contributions.

Following this, you'll discuss the intricacies of configuring and developing robust method wrappers, a crucial skill for supporting multiple test suites with both native commands. The book goes beyond the basics, exploring techniques to make test suites faster when running tests in CI like Jenkins, GitHub Actions, as well as cloud environments like Lambda Test, BrowserStack. It will also help you understand advanced topics such as gestures, plugin development, and continuous testing in CI environments.

By the end of this book, you'll have developed the expertise to debug Appium command failures and construct a sophisticated test automation framework, as well as excel in your Appium test automation endeavours and deliver reliable, efficient testing solutions.

What You'll Learn:

• Master advanced techniques in Appium Mobile Test Automation.
• Solve common challenges encountered in real-world projects and strategize to overcome them.
• Test automation for various platforms like TV apps, Roku, Raspberry Pi, and more.
• Contribute to the Appium project and engage in open-source contributions.

Who is this book for:

Software Testers, software architects, QA engineers, and DevOps engineers

Written from the perspective of an experienced IT expert, this book leverages a maturity model framework to guide organizations through each stage of adopting, securing, scaling, and tracking the value of low-code AI responsibly and efficiently. Unlike other works that focus only on AI’s technical aspects, this book boasts a practical roadmap for responsible AI adoption and provides a clear, structured maturity model that guides organizations from foundational steps to advanced, responsible AI practices.

In a world where organizations are under pressure to innovate quickly and responsibly, this book provides a structured approach, addressing essential elements such as data management, governance, ethics and compliance in low-code AI environments. Each chapter represents a maturity level, from foundational to optimized, offering readers insights, practical steps and examples to support their journey.

The Low-Code AI Maturity Model takes a comprehensive look into the transformative potential of low-code and AI.

What You Will Learn

• Identify, assess and mitigate risks to ensure stable and reliable AI deployments
• Implement robust governance, aligning with compliance standards and ethical principles at each maturity stage
• Evaluate the real business value and ROI of AI projects, empowering data-driven decision-making

Who This Book Is For

IT leaders, decision-makers, and technology enthusiasts interested in the transformative potential of low-code and AI

Leverage Generative AI within the R programming environment and prepare for future directions and how new innovations can be applied in the R ecosystem. This pioneering book is designed to bridge the gap between the advanced realms of Generative AI and the practical, statistical computing power of R.

You’ll begin with an introduction to Generative AI principles and its significance in the current data-driven landscape. You’ll then dive into the practicalities of implementing generative models such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) in R. See how R, most known for its statistical analysis, can also be used for creative synthetic data, improving model robustness, and generating innovative insights from data.

Additionally, this book addresses the demand for ethical AI by emphasizing the use of synthetic data to tackle privacy and data scarcity issues—concerns particularly relevant in healthcare, finance, and social research. We are at a pivotal moment in the evolution of AI and data science. With AI's growing importance, the book's focus on R makes advanced techniques more accessible, promoting ethical and innovative data science practice, preparing readers for upcoming trends.

What You Will Learn

• Grasp the core concepts of Generative AI and its significance in the broader AI landscape.
• Implement various generative models in R, such as GANS and VAEs.
• Generate high-quality synthetic data.
• Apply advanced techniques for improving efficiency and effectiveness of models for different applications.
• Understand Gen AI ethical considerations.

Who This Book Is For

Data scientists and statisticians with intermediate R programming skills who want to expand into Generative AI for data analysis and problem-solving. AI enthusiasts and data analysts looking to apply Generative AI techniques in R to enhance their analytical capabilities.

AI will fundamentally change the way business is conducted across most industries. Organizations that excel at leveraging secure, responsible AI to advance their strategic objectives will have a distinct advantage. Those that do not may see their market share erode.

This book provides a guide for organizations to integrate AI in alignment with the organization's strategic goals. The framework provides a roadmap for adopting secure, responsible, and resilient AI, from initial strategy development to ongoing operations that will help advance market leadership.

Part one of the book discusses laying a solid foundation to ensure successful AI integration, beginning with developing an AI strategy aligned with strategic business objectives, such as product and service differentiation, market expansion, and process optimization.

Part Two takes a deep dive into ensuring secure and safe AI adoption. It proposes a secure-by-design approach to AI development that considers AI-specific attack vectors and associated security practices throughout the AI lifecycle.

Developing and deploying secure, responsible, and resilient AI is not a one-time effort. Therefore, Part Three discusses operationalizing AI and integrating it throughout the enterprise to ensure continued success. This section focuses on scaling AI applications and continuous improvement, including establishing metrics and conducting a post-deployment ROI evaluation. Finally, it discusses how to foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.

What You Will Learn:

• Develop an AI integration strategy aligned with the organization's strategic goals and objectives.
• Incorporate a secure-by-design approach to AI integration that considers AI-specific attack vectors and applies traditional and AI-specific defense methods, such as adversarial development, model behavior monitoring, drift analysis, input validation and filtering, and output filtering.
• Establish an AI governance and risk management framework to ensure ongoing compliance with applicable legislation, industry standards, organizational policies, and responsible AI principles.
• Operationalize and scale AI applications to ensure resilient production usage and facilitate continuous improvement.
• Foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.

Who This Book is for:

The primary audience includes business leaders, AI practitioners, AI executives, AI governance professionals, and cybersecurity leaders looking to integrate AI as a strategic differentiator and to enhance business operations. Higher education would be a secondary audience.