Ai Driven Test Strategies Enhancing Quality And Efficiency In Software Development
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Ai Driven Test Strategies Enhancing Quality And Efficiency In Software Development
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Author : Phani Durga Nanda Kishore Kommisetty
language : en
Publisher: JEC PUBLICATION
Release Date :
Ai Driven Test Strategies Enhancing Quality And Efficiency In Software Development written by Phani Durga Nanda Kishore Kommisetty and has been published by JEC PUBLICATION this book supported file pdf, txt, epub, kindle and other format this book has been release on with Business & Economics categories.
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Mastering Design Patterns For Layered Testing
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Author : Manish Saini
language : en
Publisher: Orange Education Pvt Ltd
Release Date : 2025-04-19
Mastering Design Patterns For Layered Testing written by Manish Saini and has been published by Orange Education Pvt Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-19 with Computers categories.
TAGLINE Master Layered Test Automation and Build Integrate and Deploy with Confidence KEY FEATURES ● Implement automated testing across UI, API, and backend for robust coverage ● Seamlessly integrate test automation with CI/CD pipelines for efficiency ● Master advanced testing strategies for microservices and distributed systems DESCRIPTION In today’s fast-paced software development landscape, ensuring application quality requires a strategic approach to test automation. Mastering Design Patterns for Layered Testing empowers you with the knowledge and tools to design, implement, and optimize automation across UI, API, and backend layers using Python’s powerful ecosystem. Starting with foundational concepts like test design patterns and the Test Pyramid, the book delves into practical implementations of unit testing, integration testing, API testing, and contract testing. You’ll learn how to integrate automated tests into CI/CD pipelines using GitHub Actions, generate detailed test reports with Allure, and address modern testing challenges such as microservices and containerized environments. Real-world case studies illustrate how to apply these techniques in production settings. A dedicated chapter on Generative AI in testing explores its applications in test case generation and test data creation. Whether you're an intermediate tester looking to enhance your automation skills or an experienced professional seeking to learn advanced strategies, this book provides the expertise needed to build scalable and reliable test automation frameworks that drive software quality and efficiency. Stay ahead of the curve—master next-gen test automation before it’s too late! WHAT WILL YOU LEARN ● Design and implement scalable test automation across all application layers ● Build robust test frameworks using Python’s advanced testing ecosystem ● Seamlessly integrate automated tests into modern CI/CD pipelines ● Apply advanced testing patterns for APIs, microservices, and UI components ● Utilize contract testing and performance testing for reliable applications ● Leverage Generative AI to enhance test coverage and efficiency WHO IS THIS BOOK FOR? This book is ideal for QA engineers and developers with intermediate programming skills who want to elevate their test automation expertise. A foundational understanding of testing concepts, web technologies, APIs, and Git version control will enable readers to fully grasp and implement the advanced automation strategies covered. TABLE OF CONTENTS 1. Introduction to Strategic Test Design 2. Understanding Test Design Patterns 3. Unit Testing Strategies 4. Integration Testing Approaches 5. API Testing Techniques 6. Contract Testing 7. Distributing Tests Across UI, API, and Backend Layers 8. Integrating Tests into CI/CD Pipelines 9. Advanced CI/CD Strategies 10. Future of Test Automation 11. Leveraging Generative AI in Testing Index
Engineering The Future Ai Augmented Devsecops And Cloud Native Platforms For The Enterprise 2025
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Author : Author:1-Chandrakanth Devarakadra Anantha, Author:2-Dr Priyanka Kaushik
language : en
Publisher: RAVEENA PRAKASHAN OPC PVT LTD
Release Date :
Engineering The Future Ai Augmented Devsecops And Cloud Native Platforms For The Enterprise 2025 written by Author:1-Chandrakanth Devarakadra Anantha, Author:2-Dr Priyanka Kaushik and has been published by RAVEENA PRAKASHAN OPC PVT LTD this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
PREFACE The rapid evolution of technology has fundamentally altered how enterprises operate, with a significant shift towards cloud-native platforms and AI-powered tools. The convergence of artificial intelligence (AI) and DevSecOps (Development, Security, and Operations) has brought about a new era in enterprise technology, one that emphasizes automation, scalability, and security in every layer of the development lifecycle. “Engineering the Future: AI-Augmented DevSecOps and Cloud-Native Platforms for the Enterprise” explores this transformative intersection, offering a comprehensive guide to understanding and leveraging AI and cloud-native technologies to drive innovation, efficiency, and security within the enterprise ecosystem. At its core, this book delves into how AI can augment DevSecOps practices to foster a more secure, agile, and efficient development pipeline. By integrating AI into the DevSecOps process, organizations can achieve enhanced automation, proactive threat detection, and real-time insights, making it easier to develop and deploy secure applications in increasingly complex cloud environments. AI-powered solutions can detect vulnerabilities, optimize workflows, and automate compliance checks, allowing development teams to focus on innovation without sacrificing security. As businesses embrace cloud-native architectures, where microservices and containerization enable greater flexibility and scalability, the need for AI to facilitate seamless operations across distributed systems becomes ever more critical. The enterprise landscape has witnessed an unprecedented shift towards cloud-first strategies, which have revolutionized the way applications are developed, deployed, and maintained. Cloud-native platforms enable enterprises to accelerate their digital transformation, providing the agility to rapidly scale and innovate while ensuring robust security measures are embedded into every stage of the development lifecycle. Cloud-native technologies, such as Kubernetes, containerization, and serverless architectures, have become essential building blocks for modern enterprise applications. However, with this new paradigm come complex challenges in managing infrastructure, maintaining security, and ensuring smooth integration across diverse environments. This book offers insights into how AI-augmented DevSecOps practices can address these challenges, enabling organizations to stay ahead in an increasingly competitive and fast-paced business world. The synergy between AI and cloud-native platforms is particularly evident in the areas of continuous integration and continuous delivery (CI/CD), where AI-driven tools can enhance deployment efficiency and reduce human errors. By automating repetitive tasks, AI-powered systems free up valuable developer time, allowing them to focus on higher-value activities that directly contribute to business growth. Furthermore, AI’s predictive capabilities enable proactive decision-making, identifying potential bottlenecks, vulnerabilities, or failures before they affect production environments. This is especially important as enterprises adopt multi-cloud and hybrid cloud strategies, where seamless integration, monitoring, and security across various cloud platforms are critical to maintaining operational continuity. Security is at the forefront of every conversation in the world of DevSecOps, particularly as cyber threats become more sophisticated and persistent. AI plays a vital role in strengthening security frameworks by automating threat detection, identifying abnormal patterns, and responding to incidents in real-time. The integration of AI into security processes within DevSecOps workflows helps organizations address vulnerabilities faster and more efficiently, reducing the window of opportunity for attackers. This book examines how AI can enhance traditional security measures, enabling organizations to secure their cloud-native applications against ever-evolving threats. As enterprises continue to evolve in the digital age, the role of AI in augmenting DevSecOps and cloud-native platforms will only grow more pivotal. Organizations that embrace these technologies will be better positioned to innovate at scale while ensuring their applications remain secure and resilient. This book is designed for IT leaders, product managers, developers, and security professionals who are seeking to navigate the complexities of AI, DevSecOps, and cloud-native technologies. Whether you are looking to integrate AI into your DevSecOps pipeline, adopt cloud-native architectures, or enhance your enterprise’s security posture, “Engineering the Future” provides the necessary tools, frameworks, and strategies to succeed in this rapidly evolving landscape. In the pages that follow, you will gain a deeper understanding of how AI can drive automation and intelligence in DevSecOps practices, how cloud-native platforms are transforming enterprise IT operations, and how organizations can seamlessly integrate these technologies to build the secure, scalable, and agile applications of tomorrow. Welcome to the future of enterprise technology—one where AI and cloud-native platforms work hand in hand to drive innovation, security, and operational excellence. Authors
Intelligent Computing
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Author : Kohei Arai
language : en
Publisher: Springer Nature
Release Date : 2025-07-08
Intelligent Computing written by Kohei Arai and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-08 with Computers categories.
This book compiles a curated selection of insightful, rigorously researched, and state-of-the-art papers presented at the Computing Conference 2025, hosted in London, UK, on June 19–20, 2025. Drawing submissions from across the globe, the conference received 473 papers, each subjected to a stringent double-blind peer-review process. Of these, 169 papers were accepted for inclusion, reflecting exceptional scholarship and innovation across disciplines such as IoT, artificial intelligence, computing, data science, networking, data security, and privacy. Researchers, academics, and industry leaders converged to share pioneering ideas, transformative methodologies, and practical solutions to real-world challenges. By bridging academic theory and industrial application, the conference catalyzed opportunities for knowledge synthesis and interdisciplinary progress. The diverse contributions within this proceedings not only address contemporary technological issues but also anticipate future trends, offering frameworks for continued exploration. We trust this collection will serve as an indispensable reference for researchers, practitioners, and policymakers navigating the evolving landscapes of computing and digital innovation. As we reflect on the conference’s outcomes, we are confident that the insights and collaborations forged here will inspire sustained advancements in these critical fields. May the ideas within these pages spark further inquiry, drive technological evolution, and contribute meaningfully to solving the challenges of our interconnected world.
Advancing Software Engineering Through Ai Federated Learning And Large Language Models
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Author : Sharma, Avinash Kumar
language : en
Publisher: IGI Global
Release Date : 2024-05-02
Advancing Software Engineering Through Ai Federated Learning And Large Language Models written by Sharma, Avinash Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-02 with Computers categories.
The rapid evolution of software engineering demands innovative approaches to meet the growing complexity and scale of modern software systems. Traditional methods often need help to keep pace with the demands for efficiency, reliability, and scalability. Manual development, testing, and maintenance processes are time-consuming and error-prone, leading to delays and increased costs. Additionally, integrating new technologies, such as AI, ML, Federated Learning, and Large Language Models (LLM), presents unique challenges in terms of implementation and ethical considerations. Advancing Software Engineering Through AI, Federated Learning, and Large Language Models provides a compelling solution by comprehensively exploring how AI, ML, Federated Learning, and LLM intersect with software engineering. By presenting real-world case studies, practical examples, and implementation guidelines, the book ensures that readers can readily apply these concepts in their software engineering projects. Researchers, academicians, practitioners, industrialists, and students will benefit from the interdisciplinary insights provided by experts in AI, ML, software engineering, and ethics.
Artificial Intelligence For Cloud Native Software Engineering
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Author : Chelliah, Pethuru Raj
language : en
Publisher: IGI Global
Release Date : 2025-05-07
Artificial Intelligence For Cloud Native Software Engineering written by Chelliah, Pethuru Raj and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-07 with Computers categories.
Artificial intelligence is transforming software engineering by automating development, testing, deployment, and security processes, leading to more efficient and high-quality software solutions. AI-powered tools enhance scalability, reliability, and real-time analytics, enabling businesses to optimize operations and improve decision-making. As cloud-native architectures gain traction, AI-driven innovations are reshaping the way software is designed, maintained, and evolved, driving a new era of intelligent and adaptive technology solutions. Artificial Intelligence for Cloud-Native Software Engineering explores the transformative impact of AI on the software engineering lifecycle, highlighting its role in automating and enhancing various stages of software development. It provides a comprehensive overview of how AI technologies can assist software architects and engineers in creating high-quality, enterprise-grade software efficiently. Covering topics such as source code creation, data security, and multiparameter optimization, this book is an excellent resource for software engineers, computer scientists, professionals, researchers, scholars, academicians, and more.
Integrating Artificial Intelligence With Devops
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Author : Sumanth Tatineni
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-03-15
Integrating Artificial Intelligence With Devops written by Sumanth Tatineni and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-15 with Computers categories.
Unlock the future of software development with Integrating Artificial Intelligence with DevOps: Advanced Techniques, Predictive Analytics, and Automation for Real-Time Optimization and Security in Modern Software Development. This comprehensive monograph is a must-read for professionals seeking to revolutionize their DevOps workflows through the power of AI. Dive deep into the intricate integration of Artificial Intelligence within DevOps practices and discover advanced methodologies that enhance every stage of the software development lifecycle. From predictive analytics and intelligent automation to real-time optimization and robust security measures, this book offers a wealth of knowledge for optimizing software delivery. Explore practical applications, in-depth case studies, and best practices that illustrate the transformative potential of AI in DevOps. Each chapter builds on the previous, providing a seamless and cohesive narrative that guides readers through foundational concepts to advanced implementations. Whether you're looking to improve CI/CD pipelines, automate testing and monitoring, manage infrastructure more efficiently, or enhance security with AI-driven techniques, this book equips you with the tools and insights needed to ensure high-quality, secure, and efficient software delivery. Join the vanguard of modern software development with Integrating Artificial Intelligence with DevOps, and harness AI to achieve real-time optimization and unparalleled security in your DevOps processes.
Software Testing Exam Guide
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Author : Cybellium
language : en
Publisher: Cybellium Ltd
Release Date : 2024-10-26
Software Testing Exam Guide written by Cybellium and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Study Aids categories.
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Machine Learning For Software Quality And Reliability Transforming Software Engineering
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Author : Hariprasad Sivaraman
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2020-11-13
Machine Learning For Software Quality And Reliability Transforming Software Engineering written by Hariprasad Sivaraman and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-13 with Computers categories.
As software systems grow in complexity, ensuring quality, reliability, and efficiency has become more challenging than ever. Machine Learning for Software Quality and Reliability explores how AI-driven techniques are revolutionizing software engineering, enhancing defect prediction, automating testing, and optimizing performance. This book provides a deep dive into machine learning applications across the software development lifecycle. Readers will discover how ML models improve defect detection, automate test case generation, and enhance predictive maintenance, reducing downtime and increasing system stability. Key topics include supervised and unsupervised learning for software quality, anomaly detection for reliability engineering, and ML- powered root cause analysis. By integrating real-world case studies from leading technology companies, the book demonstrates how AI- driven quality assurance improves efficiency and scalability across industries. Learn how Google, Microsoft, and Netflix leverage ML to enhance software reliability, minimize bugs, and optimize continuous integration/continuous deployment (CI/CD) pipelines. With a focus on practical implementation, Machine Learning for Software Quality and Reliability equips software engineers, IT leaders, and quality assurance professionals with actionable insights to integrate ML into their workflows. Whether you ' re seeking to automate testing, enhance system resilience, or improve software reliability, this book provides the roadmap to harnessing AI for the next generation of high-quality software development.
Human Vs Chatgpt Language Of Advertising In Beauty Products Advertisements
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Author : Ida Skubis
language : en
Publisher: CRC Press
Release Date : 2024-11-21
Human Vs Chatgpt Language Of Advertising In Beauty Products Advertisements written by Ida Skubis and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-21 with Computers categories.
This book systematically investigates the linguistic strategies employed in beauty product advertising to assess their persuasive and manipulative effects. The work is divided into two sections: a review of relevant literature and an empirical analysis of advertisements. The analysis initially focuses on the linguistic features of advertisements created by humans prior to the introduction of ChatGPT, examining the linguistic measures used and their methods of persuasion and manipulation. Subsequent sections provide a detailed examination of advertisements generated by ChatGPT versions 3.5 and 4.0, analysing the artificial intelligence’s use of linguistic techniques. This includes a meta-analysis where ChatGPT itself discusses the linguistic strategies it employs. The ultimate goal is to compare and contrast the effectiveness and linguistic devices used in advertisements crafted by humans and those by ChatGPT, analysing how AI influences the language of advertising and its impact on consumer behaviour.