Take the pain out of managing serverless applications. Knative, a collection of Kubernetes extensions curated by Google, simplifies building and running serverless systems. Knative in Action guides you through the Knative toolkit, showing you how to launch, modify, and monitor event-based apps built using cloud-hosted functions like AWS Lambda. You'll learn how to use Knative Serving to develop software that is easily deployed and autoscaled, how to use Knative Eventing to wire together disparate systems into a consistent whole, and how to integrate Knative into your shipping pipeline. about the technologyWith Knative, managing a serverless application's full lifecycle is a snap. Knative builds on Kubernetes orchestration features, making it easy to deploy and run serverless apps. It handles low-level chores-such as starting and stopping instances-so you can concentrate on features and behavior. about the book Knative in Action teaches you to build complex and efficient serverless applications. You'll dive into Knative's unique design principles and grasp cloud native concepts like handling latency-sensitive workloads. You'll deliver updates with Knative Serving and interlink apps, services, and systems with Knative Eventing. To keep you moving forward, every example includes deployment advice and tips for debugging. what's inside Deploy a service with Knative Serving Connect systems with Knative Eventing Autoscale responses for different traffic surges Develop, ship, and operate software about the readerFor software developers comfortable with CLI tools and an OO language like Java or Go. about the author Jacques Chester has worked in Pivotal and VMWare R&D since 2014, contributing to Knative and other projects.

This book is about a significant step forward in software development. It brings state-of-the-art ontology reasoning into mainstream software development and its languages. Ontology Driven Software Development is the essential, comprehensive resource on enabling technologies, consistency checking and process guidance for ontology-driven software development (ODSD). It demonstrates how to apply ontology reasoning in the lifecycle of software development, using current and emerging standards and technologies. You will learn new methodologies and infrastructures, additionally illustrated using detailed industrial case studies. The book will help you: Learn how ontology reasoning allows validations of structure models and key tasks in behavior models. Understand how to develop ODSD guidance engines for important software development activities, such as requirement engineering, domain modeling and process refinement. Become familiar with semantic standards, such as the Web Ontology Language (OWL) and the SPARQL query language. Make use of ontology reasoning, querying and justification techniques to integrate software models and to offer guidance and traceability supports. This book is helpful for undergraduate students and professionals who are interested in studying how ontologies and related semantic reasoning can be applied to the software development process. In addition, itwill also be useful for postgraduate students, professionals and researchers who are going to embark on their research in areas related to ontology or software engineering.

"Specification and transformation of programs" is short for a methodology of software development where, from a formal specification of a problem to be solved, programs correctly solving that problem are constructed by stepwise application of formal, semantics-preserving transformation rules. The approach considers programming as a formal activity. Consequently, it requires some mathematical maturity and, above all, the will to try something new. A somewhat experienced programmer or a third- or fourth-year student in computer science should be able to master most of this material - at least, this is the level I have aimed at. This book is primarily intended as a general introductory textbook on transformational methodology. As with any methodology, reading and understanding is necessary but not sufficient. Therefore, most of the chapters contain a set of exercises for practising as homework. Solutions to these exercises exist and can, in principle, be obtained at nominal cost from the author upon request on appropriate letterhead. In addition, the book also can be seen as a comprehensive account of the particular transformational methodology developed within the Munich CIP project.

This book examines the requirements, risks, and solutions to improve the security and quality of complex cyber-physical systems (C-CPS), such as production systems, power plants, and airplanes, in order to ascertain whether it is possible to protect engineering organizations against cyber threats and to ensure engineering project quality. The book consists of three parts that logically build upon each other. Part I "Product Engineering of Complex Cyber-Physical Systems" discusses the structure and behavior of engineering organizations producing complex cyber-physical systems, providing insights into processes and engineering activities, and highlighting the requirements and border conditions for secure and high-quality engineering. Part II "Engineering Quality Improvement" addresses quality improvements with a focus on engineering data generation, exchange, aggregation, and use within an engineering organization, and the need for proper data modeling and engineering-result validation. Lastly, Part III "Engineering Security Improvement" considers security aspects concerning C-CPS engineering, including engineering organizations' security assessments and engineering data management, security concepts and technologies that may be leveraged to mitigate the manipulation of engineering data, as well as design and run-time aspects of secure complex cyber-physical systems. The book is intended for several target groups: it enables computer scientists to identify research issues related to the development of new methods, architectures, and technologies for improving quality and security in multi-disciplinary engineering, pushing forward the current state of the art. It also allows researchers involved in the engineering of C-CPS to gain a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in their future research and development activities. Lastly, it offers practicing engineers and managers with engineering backgrounds insights into the benefits and limitations of applicable methods, architectures, and technologies for selected use cases.

"Meta-Programming and Model-Driven Meta-Program Development: Principles, Processes and Techniques" presents an overall analysis of meta-programming, focusing on insights of meta-programming techniques, heterogeneous meta-program development processes in the context of model-driven, feature-based and transformative approaches.

The fundamental concepts of meta-programming are still not thoroughly understood, in this well organized book divided into three parts the authors help to address this. Chapters include: Taxonomy of fundamental concepts of meta-programming; Concept of structural heterogeneous meta-programming based on the original meta-language; Model-driven concept and feature-based modeling to the development process of meta-programs; Equivalent meta-program transformations and metrics to evaluate complexity of feature-based models and meta-programs; Variety of academic research case studies within different application domains to experimentally verify the soundness of the investigated approaches.

Both authors are professors at Kaunas University of Technology with 15 years research and teaching experience in the field. "Meta-Programming and Model-Driven Meta-Program Development: Principles, Processes and Techniques" is aimed at post-graduates in computer science and software engineering and researchers and program system developers wishing to extend their knowledge in this rapidly evolving sector of science and technology.

For real-time systems, the worst-case execution time (WCET) is the key objective to be considered. Traditionally, code for real-time systems is generated without taking this objective into account and the WCET is computed only after code generation. Worst-Case Execution Time Aware Compilation Techniques for Real-Time Systems presents the first comprehensive approach integrating WCET considerations into the code generation process. Based on the proposed reconciliation between a compiler and a timing analyzer, a wide range of novel optimization techniques is provided. Among others, the techniques cover source code and assembly level optimizations, exploit machine learning techniques and address the design of modern systems that have to meet multiple objectives.

Using these optimizations, the WCET of real-time applications can be reduced by about 30% to 45% on the average. This opens opportunities for decreasing clock speeds, costs and energy consumption of embedded processors. The proposed techniques can be used for all types real-time systems, including automotive and avionics IT systems.

At the dawn of the 21st century and the information age, communication and c- puting power are becoming ever increasingly available, virtually pervading almost every aspect of modern socio-economical interactions. Consequently, the potential for realizing a signi?cantly greater number of technology-mediated activities has emerged. Indeed, many of our modern activity ?elds are heavily dependant upon various underlying systems and software-intensive platforms. Such technologies are commonly used in everyday activities such as commuting, traf?c control and m- agement, mobile computing, navigation, mobile communication. Thus, the correct function of the forenamed computing systems becomes a major concern. This is all the more important since, in spite of the numerous updates, patches and ?rmware revisions being constantly issued, newly discovered logical bugs in a wide range of modern software platforms (e. g. , operating systems) and software-intensive systems (e. g. , embedded systems) are just as frequently being reported. In addition, many of today's products and services are presently being deployed in a highly competitive environment wherein a product or service is succeeding in most of the cases thanks to its quality to price ratio for a given set of features. Accordingly, a number of critical aspects have to be considered, such as the ab- ity to pack as many features as needed in a given product or service while c- currently maintaining high quality, reasonable price, and short time -to- market.

The subject of this book is the control of software engineering. The rapidly increasing demand for software is accompanied by a growth in the number of products on the market, as well as their size and complexity. Our ability to control software engineering is hardly keeping pace with this growth. As a result, software projects are often late, software products sometimes lack the required quality and the productivity improvements achieved by software engineering are insufficient to keep up with the demand This book describes ways to improve software engineering control. It argues that this should be expanded to include control of the development, maintenance and reuse of software, thus making it possible to apply many of the ideas and concepts that originate in production control and quality control. The book is based on research and experience accumulated over a number of years. During this period I had two employers: Eindhoven University of Technology and Philips Electronics. Research is not a one-man activity and I would like to thank the following persons for their contributions to the successful completion of this project. First and foremost my Ph. D. advisers Theo Bemelmans, Hans van Vliet and Fred Heemstra whose insights and experience proved invaluable at every stage. Many thanks are also due to Rob Kusters and Fred Heemstra for their patience in listening to my sometimes wild ideas and for being such excellent colleagues.

This book analyses quantitative open source software (OSS) reliability assessment and its applications, focusing on three major topic areas: the Fundamentals of OSS Quality/Reliability Measurement and Assessment; the Practical Applications of OSS Reliability Modelling; and Recent Developments in OSS Reliability Modelling. Offering an ideal reference guide for graduate students and researchers in reliability for open source software (OSS) and modelling, the book introduces several methods of reliability assessment for OSS including component-oriented reliability analysis based on analytic hierarchy process (AHP), analytic network process (ANP), and non-homogeneous Poisson process (NHPP) models, the stochastic differential equation models and hazard rate models. These measurement and management technologies are essential to producing and maintaining quality/reliable systems using OSS.

Software product lines are emerging as a critical new paradigm for software development. Product lines are enabling organizations to achieve impressive time-to-market gains and cost reductions. With the increasing number of product lines and product-line researchers and practitioners, the time is right for a comprehensive examination of the issues surrounding the software product line approach. The Software Engineering Institute at Carnegie Mellon University is proud to sponsor the first conference on this important subject. This book comprises the proceedings of the First Software Product Line Conference (SPLC1), held August 28-31, 2000, in Denver, Colorado, USA. The twenty-seven papers of the conference technical program present research results and experience reports that cover all aspects of software product lines. Topics include business issues, enabling technologies, organizational issues, and life-cycle issues. Emphasis is placed on experiences in the development and fielding of product lines of complex systems, especially those that expose problems in the design, development, or evolution of software product lines. The book will be essential reading for researchers and practitioners alike.

This book draws new attention to domain-specific conceptual modeling by presenting the work of thought leaders who have designed and deployed specific modeling methods. It provides hands-on guidance on how to build models in a particular domain, such as requirements engineering, business process modeling or enterprise architecture. In addition to these results, it also puts forward ideas for future developments. All this is enriched with exercises, case studies, detailed references and further related information. All domain-specific methods described in this volume also have a tool implementation within the OMiLAB Collaborative Environment - a dedicated research and experimentation space for modeling method engineering at the University of Vienna, Austria - making these advances accessible to a wider community of further developers and users. The collection of works presented here will benefit experts and practitioners from academia and industry alike, including members of the conceptual modeling community as well as lecturers and students.

This textbook introduces the concept of embedded systems with exercises using Arduino Uno. It is intended for advanced undergraduate and graduate students in computer science, computer engineering, and electrical engineering programs. It contains a balanced discussion on both hardware and software related to embedded systems, with a focus on co-design aspects. Embedded systems have applications in Internet-of-Things (IoT), wearables, self-driving cars, smart devices, cyberphysical systems, drones, and robotics. The hardware chapter discusses various microcontrollers (including popular microcontroller hardware examples), sensors, amplifiers, filters, actuators, wired and wireless communication topologies, schematic and PCB designs, and much more. The software chapter describes OS-less programming, bitmath, polling, interrupt, timer, sleep modes, direct memory access, shared memory, mutex, and smart algorithms, with lots of C-code examples for Arduino Uno. Other topics discussed are prototyping, testing, verification, reliability, optimization, and regulations. Appropriate for courses on embedded systems, microcontrollers, and instrumentation, this textbook teaches budding embedded system programmers practical skills with fun projects to prepare them for industry products. Introduces embedded systems for wearables, Internet-of-Things (IoT), robotics, and other smart devices; Offers a balanced focus on both hardware and software co-design of embedded systems; Includes exercises, tutorials, and assignments.

Scientific applications involve very large computations that strain the resources of whatever computers are available. Such computations implement sophisticated mathematics, require deep scientific knowledge, depend on subtle interplay of different approximations, and may be subject to instabilities and sensitivity to external input. Software able to succeed in this domain invariably embeds significant domain knowledge that should be tapped for future use. Unfortunately, most existing scientific software is designed in an ad hoc way, resulting in monolithic codes understood by only a few developers. Software architecture refers to the way software is structured to promote objectives such as reusability, maintainability, extensibility, and feasibility of independent implementation. Such issues have become increasingly important in the scientific domain, as software gets larger and more complex, constructed by teams of people, and evolved over decades. In the context of scientific computation, the challenge facing mathematical software practitioners is to design, develop, and supply computational components which deliver these objectives when embedded in end-user application codes. The Architecture of Scientific Software addresses emerging methodologies and tools for the rational design of scientific software, including component integration frameworks, network-based computing, formal methods of abstraction, application programmer interface design, and the role of object-oriented languages. This book comprises the proceedings of the International Federation for Information Processing (IFIP) Conference on the Architecture of Scientific Software, which was held in Ottawa, Canada, in October 2000. It will prove invaluable reading for developers of scientific software, as well as for researchers in computational sciences and engineering.

This edited book presents scientific results of the 21st ACIS International Winter Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD2021-Winter) which was held on January 28-30, at Ho Chi Minh City, Vietnam. The aim of this conference was to bring together researchers and scientists, businessmen and entrepreneurs, teachers, engineers, computer users, and students to discuss the numerous fields of computer science and to share their experiences and exchange new ideas and information in a meaningful way and research results about all aspects (theory, applications, and tools) of computer and information science, and to discuss the practical challenges encountered along the way and the solutions adopted to solve them. The conference organizers selected the best papers from those papers accepted for presentation at the conference. The papers were chosen based on review scores submitted by members of the program committee and underwent further rigorous rounds of review. From this second round of review, 18 of most promising papers are then published in this Springer (SCI) book and not the conference proceedings. We impatiently await the important contributions that we know these authors will bring to the field of computer and information science.

"A great book to introduce developers to the essential role that logging plays in software design and support." - Trent Whiteley Logging in Action teaches you how to make your log processing a real asset for your application, all with free and open source tools. You'll use the powerful log management tool Fluentd to solve common log problems, and learn how proper log management can improve performance and make management of software solutions easier. Through useful examples like sending log driven events to Slack, you'll get hands-on experience applying structure to your unstructured data. about the technology Fluentd is a powerful log management tool that seamlessly handles messy logging data, from operational errors, to application events, and security events. It decouples log data, such as SNMP or slow database queries, from backend systems and easily sends it where it needs to go-thanks to 500+ flexible plugins covering all major services. about the book Logging in Action is a guide to streamlining your log processing, turning logged data into a tool that will boost your application's performance. It's packed with tips and tricks on how proper log management can improve your application's security, speed, and cost-effectiveness. You'll master the basics of the Fluentd management tool, then take a peek behind the scenes at how different configurations will impact and improve the way your systems function. By the time you're done, you'll be able to reliably configure Fluentd so that it can easily scale to handle even the largest data loads. what's inside Deploy Fluentd and Fluent Bit into varied environments Configure Fluentd and Fluent Bit to solve common log problems Fluentd for microservices Connect a custom log source or destination with Fluentd's extensibility framework Create a custom plugin for niche problems Logging best practices and common pitfalls about the reader For developers and operations people familiar with application logging or infrastructure monitor logs. about the author Phil Wilkins has spent over 25 years in the software industry. He works as a Technology Evangelist for Capgemini, specializing in cloud integration, APIs, and related technologies. Phil is TOGAF certified, and recognized by Oracle as an Ace Director (independent technology advocate) for his contributions to the integration and PaaS community.

This book presents a coherent description of the theoretical and practical aspects of Coloured Petri Nets (CP-nets or CPN). It shows how CP-nets have been de veloped - from being a promising theoretical model to being a full-fledged lan guage for the design, specification, simulation, validation and implementation of large software systems (and other systems in which human beings and/or com puters communicate by means of some more or less formal rules). The book contains the formal definition of CP-nets and the mathematical theory behind their analysis methods. However, it has been the intention to write the book in such a way that it also becomes attractive to readers who are more interested in applications than the underlying mathematics. This means that a large part of the book is written in a style which is closer to an engineering textbook (or a users' manual) than it is to a typical textbook in theoretical computer science. The book consists of three separate volumes. The first volume defines the net model (i. e. , hierarchical CP-nets) and the basic concepts (e. g. , the different behavioural properties such as deadlocks, fair ness and home markings). It gives a detailed presentation of many small exam ples and a brief overview of some industrial applications. It introduces the for mal analysis methods. Finally, it contains a description of a set of CPN tools which support the practical use of CP-nets.

With the increasing proliferation of information-technology and, especially, Web-based approaches to the implementation of systems and services, researchers, educators, and practitioners worldwide are experiencing a rising need for authoritative references to enhance their understanding of the most current and effective engineering practices leading to robust and successful solutions.""Integrated Approaches in Information Technology and Web Engineering: Advancing Organizational Knowledge Sharing"" presents comprehensive, research-driven insights into the field of Web engineering. This book collects over 30 authoritative articles from distinguished international researchers in information technology and Web engineering, creating an invaluable resource for library reference collections that will equip researchers and practitioners in academia and industry alike with the knowledge base to drive the next generation of innovations.

This book addresses action research (AR), one of the main research methodologies used for academia-industry research collaborations. It elaborates on how to find the right research activities and how to distinguish them from non-significant ones. Further, it details how to glean lessons from the research results, no matter whether they are positive or negative. Lastly, it shows how companies can evolve and build talents while expanding their product portfolio. The book's structure is based on that of AR projects; it sequentially covers and discusses each phase of the project. Each chapter shares new insights into AR and provides the reader with a better understanding of how to apply it. In addition, each chapter includes a number of practical use cases or examples. Taken together, the chapters cover the entire software lifecycle: from problem diagnosis to project (or action) planning and execution, to documenting and disseminating results, including validity assessments for AR studies. The goal of this book is to help everyone interested in industry-academia collaborations to conduct joint research. It is for students of software engineering who need to learn about how to set up an evaluation, how to run a project, and how to document the results. It is for all academics who aren't afraid to step out of their comfort zone and enter industry. It is for industrial researchers who know that they want to do more than just develop software blindly. And finally, it is for stakeholders who want to learn how to manage industrial research projects and how to set up guidelines for their own role and expectations.

This book presents real-world decision support systems, i.e., systems that have been running for some time and as such have been tested in real environments and complex situations; the cases are from various application domains and highlight the best practices in each stage of the system's life cycle, from the initial requirements analysis and design phases to the final stages of the project. Each chapter provides decision-makers with recommendations and insights into lessons learned so that failures can be avoided and successes repeated. For this reason unsuccessful cases, which at some point of their life cycle were deemed as failures for one reason or another, are also included. All decision support systems are presented in a constructive, coherent and deductive manner to enhance the learning effect. It complements the many works that focus on theoretical aspects or individual module design and development by offering 'good' and 'bad' practices when developing and using decision support systems. Combining high-quality research with real-world implementations, it is of interest to researchers and professionals in industry alike.

Engineering tasks are supposed to achieve defined goals under certain project constraints. Example goals of software engineering tasks include achieving a certain functionality together with some level of reliability or performance. Example constraints of software engineering tasks include budget and time limitations or experience limitations of the developers at hand. Planning of an engineering project requires the selection of techniques, methods and tools suited to achieve stated goals under given project constraints. This assumes sufficient knowledge regarding the process-product relationships (or effects) of candidate techniques, methods and tools. Planning of software projects suffers greatly from lack of knowledge regarding the process-product relationships of candidate techniques, methods and tools. Especially in the area of testing a project planner is confronted with an abundance of testing techniques, but very little knowledge regarding their effects under varying project conditions. This book offers a novel approach to addressing this problem: First, based on a comprehensive initial characterization scheme (see chapter 7) an overview of existing testing techniques and their effects under varying conditions is provided to guide the selection of testing approaches. Second, the optimisation of this knowledge base is suggested based on experience from experts, real projects and scientific experiments (chapters 8, 9, and 10). This book is of equal interest to practitioners, researchers and students. Practitioners interested in identifying ways to organize their company-specific knowledge about testing could start with the schema provided in this book, and optimise it further by applying similar strategies as offered in chapters 8 and 9.

This updated and reorganized Fifth edition of Software Testing: A Craftsman's Approach continues to be a valuable reference for software testers, developers, and engineers, by applying the strong mathematics content of previous editions to a coherent treatment of software testing. Responding to instructor and student survey input, the authors have streamlined chapters and examples. The Fifth Edition: Has a new chapter on feature interaction testing that explores the feature interaction problem and explains how to reduce tests Uses Java instead of pseudo-code for all examples including structured and object-oriented ones Presents model-based development and provides an explanation of how to conduct testing within model-based development environments Explains testing in waterfall, iterative, and agile software development projects Explores test-driven development, reexamines all-pairs testing, and explains the four contexts of software testing Thoroughly revised and updated, Software Testing: A Craftsman's Approach, Fifth Edition is sure to become a standard reference for those who need to stay up to date with evolving technologies in software testing.

This book provides a comprehensive discussion of UML/OCL methods and design flow, for automatic validation and verification of hardware and software systems. While the presented flow focuses on using satisfiability solvers, the authors also describe how these methods can be used for any other automatic reasoning engine. Additionally, the design flow described is applied to a broad variety of validation and verification tasks. The authors also cover briefly how non-functional properties such as timing constraints can be handled with the described flow.

Software testing is traditionally seen as a difficult and time consuming activity that is hard to embed in the software development process. This book provides a different view. It explains to stakeholders how testing can add value to software development and doing business, and provides the tester with practical information.

TestGoal is not just another methodology. Several good testing methodologies exist. But, like any other profession, also testing encompasses more than the simple application of a methodology. After all, strict adherence to a specific methodology is no guarantee for success. Success stems from the mindset, enthusiasm, knowledge and skill of the tester. These factors determine whether a methodology is applied successfully and whether testing takes on a result-driven character. And that's what TestGoal is about: a result-driven attitude, testing principles and expertise as fundament, and a hands-on six step plan to enable result driven testing.

Derk-Jan de Grood and his colleagues from Collis, an international software testing company, know about the main pitfalls in test projects from their extensive professional experience. TestGoal has emerged from the office floor and captures over a decade of best practice. TestGoal is made by professionals for professionals, and it combines the mindset, knowledge, and skills required to add value with testing and make software development more successful.

This book explains in a clear language how you can make testing result-driven. It explains why testing is important and describes all of the activities involved in testing. It is enriched with recognizable examples, practical tips and useful checklists. This makes it a "GO kit" that enables testers to immediately get started and add value to their organization.

While standardization has empowered the software industry to substantially scale software development and to provide affordable software to a broad market, it often does not address smaller market segments, nor the needs and wishes of individual customers. Software product lines reconcile mass production and standardization with mass customization in software engineering. Ideally, based on a set of reusable parts, a software manufacturer can generate a software product based on the requirements of its customer. The concept of features is central to achieving this level of automation, because features bridge the gap between the requirements the customer has and the functionality a product provides. Thus features are a central concept in all phases of product-line development. The authors take a developer's viewpoint, focus on the development, maintenance, and implementation of product-line variability, and especially concentrate on automated product derivation based on a user's feature selection. The book consists of three parts. Part I provides a general introduction to feature-oriented software product lines, describing the product-line approach and introducing the product-line development process with its two elements of domain and application engineering. The pivotal part II covers a wide variety of implementation techniques including design patterns, frameworks, components, feature-oriented programming, and aspect-oriented programming, as well as tool-based approaches including preprocessors, build systems, version-control systems, and virtual separation of concerns. Finally, part III is devoted to advanced topics related to feature-oriented product lines like refactoring, feature interaction, and analysis tools specific to product lines. In addition, an appendix lists various helpful tools for software product-line development, along with a description of how they relate to the topics covered in this book. To tie the book together, the authors use two running examples that are well documented in the product-line literature: data management for embedded systems, and variations of graph data structures. They start every chapter by explicitly stating the respective learning goals and finish it with a set of exercises; additional teaching material is also available online. All these features make the book ideally suited for teaching - both for academic classes and for professionals interested in self-study.

How do you build a product that delights users? You must first know who your users are and how they plan to use what you're building. With this practical book, you'll explore the often-misunderstood practice of user story mapping, and learn how it can help keep your team stay focused on users and their experience throughout the development process.

You and your team will learn that user stories aren't a way to write better specifications, but a way to organize and have better conversations. This book will help you understand what kinds of conversations you should be having, when to have them, and what to keep track of when you do.Learn the key concepts used to create a great story mapUnderstand how user stories really work, and how to make good use of them in agile and lean projectsExamine the nuts and bolts of managing stories through the development cycleUse strategies that help you continue to learn before and after the product's release to customers and users

"User Story Mapping" is ideal for agile and lean software development team members, product managers and UX practitioners in commercial product companies, and business analysts and project managers in IT organizations--whether you're new to this approach or want to understand more about it.