This volume constitutes the refereed proceedings of the 28th European Conference on Systems, Software and Services Process Improvement, EuroSPI 2021, held in Krems, Austria, in September 2021*.The 42 full papers and 9 short papers presented were carefully reviewed and selected from 100 submissions. The volume presents core research contributions and selected industrial contributions. Core research contributions: SPI and emerging software and systems engineering paradigms; SPI and team skills and diversity; SPI and recent innovations; SPI and agile; SPI and standards and safety and security norms; SPI and good/bad SPI practices in improvement; SPI and functional safety and cybersecurity; digitalisation of industry, infrastructure and e-mobility. Selected industrial contributions: SPI and emerging software and systems engineering paradigms; SPI and recent innovations; SPI and agile; SPI and standards and safety and security norms; SPI and good/bad SPI practices in improvement; SPI and functional safety and cybersecurity; digitalisation of industry, infrastructure and e-mobility; virtual reality. *The conference was partially held virtually due to the COVID-19 pandemic.

This book presents contemporary empirical methods in software engineering related to the plurality of research methodologies, human factors, data collection and processing, aggregation and synthesis of evidence, and impact of software engineering research. The individual chapters discuss methods that impact the current evolution of empirical software engineering and form the backbone of future research. Following an introductory chapter that outlines the background of and developments in empirical software engineering over the last 50 years and provides an overview of the subsequent contributions, the remainder of the book is divided into four parts: Study Strategies (including e.g. guidelines for surveys or design science); Data Collection, Production, and Analysis (highlighting approaches from e.g. data science, biometric measurement, and simulation-based studies); Knowledge Acquisition and Aggregation (highlighting literature research, threats to validity, and evidence aggregation); and Knowledge Transfer (discussing open science and knowledge transfer with industry). Empirical methods like experimentation have become a powerful means of advancing the field of software engineering by providing scientific evidence on software development, operation, and maintenance, but also by supporting practitioners in their decision-making and learning processes. Thus the book is equally suitable for academics aiming to expand the field and for industrial researchers and practitioners looking for novel ways to check the validity of their assumptions and experiences. Chapter 17 is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book focuses on mathematical modeling, describes the process of constructing and evaluating models, discusses the challenges and delicacies of the modeling process, and explicitly outlines the required rules and regulations so that the reader will be able to generalize and reuse concepts in other problems by relying on mathematical logic.Undergraduate and postgraduate students of different academic disciplines would find this book a suitable option preparing them for jobs and research fields requiring modeling techniques. Furthermore, this book can be used as a reference book for experts and practitioners requiring advanced skills of model building in their jobs.

This book constitutes the refereed proceedings of the 14th International Conference on the Quality of Information and Communications Technology, QUATIC 2021, held in Algarve, Portugal*, in September 2021. The 30 full papers and 9 short papers were carefully reviewed and selected from 98 submissions. The papers are organized in topical sections: ICT verification and validation; software evolution; process modeling, improvement and assessment; quality aspects in quantum computing; safety, security, and privacy; quality aspects in machine learning, AI and data analytics; evidence-based software quality engineering; quality in cyber-physical systems; software quality education and training. *The conference was held virtually due to the COVID-19 pandemic.

Apply the industrial engineering science of invention and assembly to how software is described, planned, and built, allowing you to be free to flex your practices according to your needs, putting principle over habit and rules.Reading about Agile practices is like reading diet advice. Everything sounds unique and good; everything starts with good intentions. Then reality sets in. Organizations adapt their practices, but lose sight of grounding principles. A bias toward ceremonies, metrics, and recipes comes at the expense of efficiently getting the real work done. Managers and developers are incentivized to game the system. Organizational metrics become detached from the reality of what is being delivered and how.The Agile Codex shows you how to describe a software project as an acyclic dependency tree of sized work items, scoped to be operated on by one software engineer each and completed within a week. It provides Open Source tooling to help you visualize, sequence and assign these work items to account for risk and increase predictability in your delivery times. You'll see the value of doing this as it applies to efficiently planning and adjusting software projects in the face of learning and change. Finally, the book covers the collaborative agile principles required to bring this skill set and practice to a software team.Throughout the book you'll be reminded that software engineering is not a rote task - it is primarily a skilled, creative act. As such, you'll see that we need to account for the space needed to research, plan, create, and adjust. The Agile practices serving the codex deal with this intersection between the engineering problem of software delivery flow, and the human reality of how work is described, owned, executed, and transitioned from one state to another.Everything an agile team does must serve the codex. The creation and the care and feeding of this structured tree of work sets the frame in which all other team actions take place and against which all successes or failures can be evaluated.

Maintaining a practical perspective, Python Programming: A Practical Approach acquaints you with the wonderful world of programming. The book is a starting point for those who want to learn Python programming. The backbone of any programming, which is the data structure and components such as strings, lists, etc., have been illustrated with many examples and enough practice problems to instill a level of self-confidence in the reader. Drawing on knowledge gained directly from teaching Computer Science as a subject and working on a wide range of projects related to ML, AI, deep learning, and blockchain, the authors have tried their best to present the necessary skills for a Python programmer. Once the foundation of Python programming is built and the readers are aware of the exact structure, dimensions, processing, building blocks, and representation of data, they can readily take up their specific problems from the area of interest and solve them with the help of Python. These include, but are not limited to, operators, control flow, strings, functions, module processing, object-oriented programming, exception and file handling, multithreading, synchronization, regular expressions, and Python database programming. This book on Python programming is specially designed to keep readers busy with learning fundamentals and generates a sense of confidence by attempting the assignment problems. We firmly believe that explaining any particular technology deviates from learning the fundamentals of a programming language. This book is focused on helping readers attempt implementation in their areas of interest through the skills imparted through this book. We have attempted to present the real essence of Python programming, which you can confidently apply in real life by using Python as a tool. Salient Features Based on real-world requirements and solution. Simple presentation without avoiding necessary details of the topic. Executable programs on almost every topic. Plenty of exercise questions, designed to test readers' skills and understanding. Purposefully designed to be instantly applicable, Python Programming: A Practical Approach provides implementation examples so that the described subject matter can be immediately implemented due to the well-known versatility of Python in handling different data types with ease.

Extensive research conducted by the Hasso Plattner Design Thinking Research Program at Stanford University in Palo Alto, California, USA, and the Hasso Plattner Institute in Potsdam, Germany, has yielded valuable insights on why and how design thinking works. The participating researchers have identified metrics, developed models, and conducted studies, which are featured in this book, and in the previous volumes of this series. This volume provides readers with tools to bridge the gap between research and practice in design thinking with varied real world examples. Several different approaches to design thinking are presented in this volume. Acquired frameworks are leveraged to understand design thinking team dynamics. The contributing authors lead the reader through new approaches and application fields and show that design thinking can tap the potential of digital technologies in a human-centered way. In a final section, new ideas in neurodesign at Stanford University and at Hasso Plattner Institute in Potsdam are elaborated upon thereby challenging the reader to consider newly developed methodologies and provide discussion of how these insights can be applied to various sectors. Special emphasis is placed on understanding the mechanisms underlying design thinking at the individual and team levels. Design thinking can be learned. It has a methodology that can be observed across multiple settings and accordingly, the reader can adopt new frameworks to modify and update existing practice. The research outcomes compiled in this book are intended to inform and provide inspiration for all those seeking to drive innovation - be they experienced design thinkers or newcomers.

Customer experience engineering applied to the engineering department is rare, but needed. Most companies keep support, UX, engineering, product, and CX separate. To address this gap, this book highlights roles and techniques that are proven to accelerate issue detection and prevention by 30% or more. With the author's vast experience in tech support, he has developed techniques and skills that allow engineers to gain customer insights faster and through new and insightful sources that are within their reach. You will develop a deep understanding of the impact of issues; understand and optimize the speed of the engineering feedback loop (issue resolution time); and develop the ability to calculate the cost of the issues or customer friction to the business (in aggregate and on a case-by-case basis). Organizations can save significant money and add additional revenue by addressing customer friction proactively in collaboration with product, engineering, and site reliability engineering (SRE) functions and reduce the average time of an issue resolution by 80%. The cross-functional leadership, mentoring, and engineering techniques you'll learn from this proactive stance are very valuable and teachable, and this book will show you the path forward. What You Will Learn Gain the techniques and tools necessary to validate customer journey success in production Contribute to customer-centric key performance indicators (KPIs) on executive dashboards Create meaningful insights and data points that allowed the feedback loop to be optimized and efficient Who This Book is For Professionals participating in the value stream of digital software engineering for the benefit of customer experiences, directly or indirectly. You may be an engineer practicing DevOps or site reliability, or you might be a product owner, UX designer, or researcher. You might be working in support and seeking for new ways to engage with your engineering teams.

This book constitutes selected papers from the Second International Conference on Microelectronic Devices, Circuits and Systems, ICMDCS 2021, held in Vellore, India, in February 2021. The 32 full papers and 6 short papers presented were thoroughly reviewed and selected from 103 submissions. They are organized in the topical sections on digital design for signal, image and video processing; VLSI testing and verification; emerging technologies and IoT; nano-scale modelling and process technology device; analog and mixed signal design; communication technologies and circuits; technology and modelling for micro electronic devices; electronics for green technology.

This monograph discusses software reuse and how it can be applied at different stages of the software development process, on different types of data and at different levels of granularity. Several challenging hypotheses are analyzed and confronted using novel data-driven methodologies, in order to solve problems in requirements elicitation and specification extraction, software design and implementation, as well as software quality assurance. The book is accompanied by a number of tools, libraries and working prototypes in order to practically illustrate how the phases of the software engineering life cycle can benefit from unlocking the potential of data. Software engineering researchers, experts, and practitioners can benefit from the various methodologies presented and can better understand how knowledge extracted from software data residing in various repositories can be combined and used to enable effective decision making and save considerable time and effort through software reuse. Mining Software Engineering Data for Software Reuse can also prove handy for graduate-level students in software engineering.

This is the first book organized around code clone analysis. To cover the broad studies of code clone analysis, this book selects past research results that are important to the progress of the field and updates them with new results and future directions. The first chapter provides an introduction for readers who are inexperienced in the foundation of code clone analysis, defines clones and related terms, and discusses the classification of clones. The chapters that follow are categorized into three main parts to present 1) major tools for code clone analysis, 2) fundamental topics such as evaluation benchmarks, clone visualization, code clone searches, and code similarities, and 3) applications to actual problems. Each chapter includes a valuable reference list that will help readers to achieve a comprehensive understanding of this diverse field and to catch up with the latest research results. Code clone analysis relies heavily on computer science theories such as pattern matching algorithms, computer language, and software metrics. Consequently, code clone analysis can be applied to a variety of real-world tasks in software development and maintenance such as bug finding and program refactoring. This book will also be useful in designing an effective curriculum that combines theory and application of code clone analysis in university software engineering courses.

This book constitutes the refereed proceedings of the 27th International Symposium on Model Checking Software, SPIN 2021, held virtually in July 2021.The 3 full papers, 4 tool papers, and 1 case study presented together with 2 invited talks were carefully reviewed and selected from 20 submissions. Topics covered include formal verification techniques for automated analysis of software; formal analysis for modeling languages, such as UML/state charts; formal specification languages, temporal logic, design-by-contract; model checking, automated theorem proving, including SAT and SMT; verifying compilers; abstraction and symbolic execution techniques; and much more.

This book addresses mechanisms for reducing model heterogeneity induced by the absence of explicit semantics expression in the formal techniques used to specify design models. More precisely, it highlights the advances in handling both implicit and explicit semantics in formal system developments, and discusses different contributions expressing different views and perceptions on the implicit and explicit semantics. The book is based on the discussions at the Shonan meeting on this topic held in 2016, and includes contributions from the participants summarising their perspectives on the problem and offering solutions. Divided into 5 parts: domain modelling, knowledge-based modelling, proof-based modelling, assurance cases, and refinement-based modelling, and offers inspiration for researchers and practitioners in the fields of formal methods, system and software engineering, domain knowledge modelling, requirement analysis, and explicit and implicit semantics of modelling languages.

Utilize a set of practical guidelines to help your Agile organization elevate software design quality as an important business driver to achieve customer satisfaction and, ultimately, higher revenue for your company. This is the first book to focus on a holistic quality view-what it is and how it links to overall business enhancements. The real-world examples used in this book allow you to learn and apply similar strategies and guidelines to help create a quality blueprint for your organization. Five pillars of quality are defined that can be used for any industry and, once internalized, can serve as a set of tools to continuously improve and measure the key factors impacting quality. What You'll Learn Be aware of the key elements in any transformation that involves culture Link quality and business outcomes Understand quality and its holistic definition and why continuous improvement is still a relevant approach in enhancing quality Follow guidelines with specific examples that can be applied to any product release in any type of industry to improve quality and enhance Agile processes Utilize relevant metrics to measure and continuously improve to make incremental positive changes Who This Book Is For Individuals at various levels in organizations-from Agile scrum teams, all the way up to executive leadership

This book constitutes the refereed proceedings of the Software Engineering and Algorithms section of the 10th Computer Science On-line Conference 2021 (CSOC 2021), held on-line in April 2021. Software engineering research and its applications to intelligent algorithms take an essential role in computer science research. In this book, modern research methods, application of machine and statistical learning in the software engineering research are presented.

This book summarizes the research findings presented at the 13th International Joint Conference on Knowledge-Based Software Engineering (JCKBSE 2020), which took place on August 24-26, 2020. JCKBSE 2020 was originally planned to take place in Larnaca, Cyprus. Unfortunately, the COVID-19 pandemic forced it be rescheduled as an online conference. JCKBSE is a well-established, international, biennial conference that focuses on the applications of artificial intelligence in software engineering. The 2020 edition of the conference was organized by Hiroyuki Nakagawa, Graduate School of Information Science and Technology, Osaka University, Japan, and George A. Tsihrintzis and Maria Virvou, Department of Informatics, University of Piraeus, Greece. This research book is a valuable resource for experts and researchers in the field of (knowledge-based) software engineering, as well as general readers in the fields of artificial and computational Intelligence and, more generally, computer science wanting to learn more about the field of (knowledge-based) software engineering and its applications. An extensive list of bibliographic references at the end of each paper helps readers to probe further into the application areas of interest to them.

A comprehensive guide to understanding the standard and most recent advances in the design of reliable computer systems. It is organized into three sections, beginning with an in-depth review of existing reliability techniques and evaluation criteria for both hardware and software. also examined are the models for detecting faults and predicting failures, and the financial considerations which are inherent in the design, purchase, operation, and maintenance of a reliable system.

Covers IoT-cloud convergence with a focus on complex industrial IoT case studies Discusses the broad background of IoT-cloud convergence architectures and their fundamentals along with resource provisioning mechanisms Emphasizes the use of context in developing context aware IoT solutions Presents a novel C-model that explains the IoT application development phases Discusses a simplified convergence model that depicts the role of cloud in an IoT application

A complete introduction to building robust and reliable software Beginning Software Engineering demystifies the software engineering methodologies and techniques that professional developers use to design and build robust, efficient, and consistently reliable software. Free of jargon and assuming no previous programming, development, or management experience, this accessible guide explains important concepts and techniques that can be applied to any programming language. Each chapter ends with exercises that let you test your understanding and help you elaborate on the chapter's main concepts. Everything you need to understand waterfall, Sashimi, agile, RAD, Scrum, Kanban, Extreme Programming, and many other development models is inside! * Describes in plain English what software engineering is * Explains the roles and responsibilities of team members working on a software engineering project * Outlines key phases that any software engineering effort must handle to produce applications that are powerful and dependable * Details the most popular software development methodologies and explains the different ways they handle critical development tasks * Incorporates exercises that expand upon each chapter's main ideas * Includes an extensive glossary of software engineering terms

The topics covered in this book range from modeling and programming languages and environments, via approaches for design and verification, to issues of ethics and regulation. In terms of techniques, there are results on model-based engineering, product lines, mission specification, component-based development, simulation, testing, and proof. Applications range from manufacturing to service robots, to autonomous vehicles, and even robots than evolve in the real world. A final chapter summarizes issues on ethics and regulation based on discussions from a panel of experts. The origin of this book is a two-day event, entitled RoboSoft, that took place in November 2019, in London. Organized with the generous support of the Royal Academy of Engineering and the University of York, UK, RoboSoft brought together more than 100 scientists, engineers and practitioners from all over the world, representing 70 international institutions. The intended readership includes researchers and practitioners with all levels of experience interested in working in the area of robotics, and software engineering more generally. The chapters are all self-contained, include explanations of the core concepts, and finish with a discussion of directions for further work. Chapters 'Towards Autonomous Robot Evolution', 'Composition, Separation of Roles and Model-Driven Approaches as Enabler of a Robotics Software Ecosystem' and 'Verifiable Autonomy and Responsible Robotics' are available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.

This book details the conceptual foundations, design and implementation of the domain-specific language (DSL) development system DjDSL. DjDSL facilitates design-decision-making on and implementation of reusable DSL and DSL-product lines, and represents the state-of-the-art in language-based and composition-based DSL development. As such, it unites elements at the crossroads between software-language engineering, model-driven software engineering, and feature-oriented software engineering. The book is divided into six chapters. Chapter 1 ("DSL as Variable Software") explains the notion of DSL as variable software in greater detail and introduces readers to the idea of software-product line engineering for DSL-based software systems. Chapter 2 ("Variability Support in DSL Development") sheds light on a number of interrelated dimensions of DSL variability: variable development processes, variable design-decisions, and variability-implementation techniques for DSL. The three subsequent chapters are devoted to the key conceptual and technical contributions of DjDSL: Chapter 3 ("Variable Language Models") explains how to design and implement the abstract syntax of a DSL in a variable manner. Chapter 4 ("Variable Context Conditions") then provides the means to refine an abstract syntax (language model) by using composable context conditions (invariants). Next, Chapter 5 ("Variable Textual Syntaxes") details solutions to implementing variable textual syntaxes for different types of DSL. In closing, Chapter 6 ("A Story of a DSL Family") shows how to develop a mixed DSL in a step-by-step manner, demonstrating how the previously introduced techniques can be employed in an advanced example of developing a DSL family. The book is intended for readers interested in language-oriented as well as model-driven software development, including software-engineering researchers and advanced software developers alike. An understanding of software-engineering basics (architecture, design, implementation, testing) and software patterns is essential. Readers should especially be familiar with the basics of object-oriented modelling (UML, MOF, Ecore) and programming (e.g., Java).

Deliver Any Service Far More Effectively, Based on What Customers Really Want As service stacks grow more complex, it becomes even tougher to deliver on-demand IT services that meet customers' expectations for speed, consistency, reliability, security, privacy, and value. Layering on new cloud technologies, architectural approaches, or methodologies can aggravate the problem by widening the gap between what delivery teams think they're delivering and what customers actually experience. In Lean DevOps, technical leader Robert Benefield helps you escape this spiral, reverse bad habits, and regain the situational awareness you need to deliver the right services in the right way. Writing for delivery team members and their leaders, Benefield shows how to improve information flow throughout your organization, so you can move toward your customers' target outcomes. He identifies problems arising from traditional approaches to managing teams, debunks excuses often used to prevent progress, and offers realistic recommendations for everything from requirements to incentives. * Understand key dynamics that impact service delivery, and avoid focusing on the wrong issues * Give your delivery teams stronger abilities to learn and improve * Improve team maturity and implement prerequisites for effective use of automation and AI/ML * Optimize key service delivery elements, from instrumentation to queue masters and cycles * Organize and manage workflows more effectively * Handle governance associated with internal controls and external legal/regulatory requirements * Leverage the power of Lean and Mission Command to accelerate innovation, empower subordinates, and drive the outcomes you want

The three-volume set CCIS 1419, CCIS 1420, and CCIS 1421 contains the extended abstracts of the posters presented during the 23rd International Conference on Human-Computer Interaction, HCII 2021, which was held virtually in July 2021. The total of 1276 papers and 241 posters included in the 39 HCII 2021 proceedings volumes was carefully reviewed and selected from 5222 submissions.The posters presented in these three volumes are organized in topical sections as follows: Part I: HCI theory and methods; perceptual, cognitive and psychophisiological aspects of interaction; designing for children; designing for older people; design case studies; dimensions of user experience; information, language, culture and media. Part II: interaction methods and techniques; eye-tracking and facial expressions recognition; human-robot interaction; virtual, augmented and mixed reality; security and privacy issues in HCI; AI and machine learning in HCI. Part III: interacting and learning; interacting and playing; interacting and driving; digital wellbeing, eHealth and mHealth; interacting and shopping; HCI, safety and sustainability; HCI in the time of pandemic.

This book covers several topics related to domain-specific language (DSL) engineering in general and how they can be handled by means of the JetBrains Meta Programming System (MPS), an open source language workbench developed by JetBrains over the last 15 years. The book begins with an overview of the domain of language workbenches, which provides perspectives and motivations underpinning the creation of MPS. Moreover, technical details of the language underneath MPS together with the definition of the tool's main features are discussed. The remaining ten chapters are then organized in three parts, each dedicated to a specific aspect of the topic. Part I "MPS in Industrial Applications" deals with the challenges and inadequacies of general-purpose languages used in companies, as opposed to the reasons why DSLs are essential, together with their benefits and efficiency, and summarizes lessons learnt by using MPS. Part II about "MPS in Research Projects" covers the benefits of text-based languages, the design and development of gamification applications, and research fields with generally low expertise in language engineering. Eventually, Part III focuses on "Teaching and Learning with MPS" by discussing the organization of both commercial and academic courses on MPS. MPS is used to implement languages for real-world use. Its distinguishing feature is projectional editing, which supports practically unlimited language extension and composition possibilities as well as a flexible mix of a wide range of textual, tabular, mathematical and graphical notations. The number and diversity of the presented use-cases demonstrate the strength and malleability of the DSLs defined using MPS. The selected contributions represent the current state of the art and practice in using JetBrains MPS to implement languages for real-world applications.