As software R&D investment increases, the benefits from short feedback cycles using technologies such as continuous deployment, experimentation-based development, and multidisciplinary teams require a fundamentally different strategy and process. This book will cover the three overall challenges that companies are grappling with: speed, data and ecosystems. Speed deals with shortening the cycle time in R&D. Data deals with increasing the use of and benefit from the massive amounts of data that companies collect. Ecosystems address the transition of companies from being internally focused to being ecosystem oriented by analyzing what the company is uniquely good at and where it adds value.

As software R&D investment increases, the benefits from short feedback cycles using technologies such as continuous deployment, experimentation-based development, and multidisciplinary teams require a fundamentally different strategy and process. This book will cover the three overall challenges that companies are grappling with: speed, data and ecosystems. Speed deals with shortening the cycle time in R&D. Data deals with increasing the use of and benefit from the massive amounts of data that companies collect. Ecosystems address the transition of companies from being internally focused to being ecosystem oriented by analyzing what the company is uniquely good at and where it adds value.

This book celebrates the 10-year anniversary of Software Center (a collaboration between 18 European companies and five Swedish universities) by presenting some of the most impactful and relevant journal or conference papers that researchers in the center have published over the last decade.

The book is organized around the five themes around which research in Software Center is organized, i.e. Continuous Delivery, Continuous Architecture, Metrics, Customer Data and Ecosystems Driven Development, and AI Engineering. The focus of the Continuous Delivery theme is to help companies to continuously build high quality products with the right degree of automation. The Continuous Architecture theme addresses challenges that arise when balancing the need for architectural quality and more agile ways of working with shorter development cycles. The Metrics theme studies and provides insight to understand, monitor and improve software processes, products and organizations. The fourth theme, Customer Data and Ecosystem Driven Development, helps companies make sense of the vast amounts of data that are continuously collected from products in the field. Eventually, the theme of AI Engineering addresses the challenge that many companies struggle with in terms of deploying machine- and deep-learning models in industrial contexts with production quality. Each theme has its own part in the book and each part has an introduction chapter and then a carefully selected reprint of the most important papers from that theme.

This book provides essential insights on the adoption of modern software engineering practices at large companies producing software-intensive systems, where hundreds or even thousands of engineers collaborate to deliver on new systems and new versions of already deployed ones. It is based on the findings collected and lessons learned at the Software Center (SC), a unique collaboration between research and industry, with Chalmers University of Technology, Gothenburg University and Malmö University as academic partners and Ericsson, AB Volvo, Volvo Car Corporation, Saab Electronic Defense Systems, Grundfos, Axis Communications, Jeppesen (Boeing) and Sony Mobile as industrial partners.

The 17 chapters present the “Stairway to Heaven” model, which represents the typical evolution path companies move through as they develop and mature their software engineering capabilities. The chapters describe theoretical frameworks, conceptual models and, most importantly, the industrial experiences gained by the partner companies in applying novel software engineering techniques.

The book’s structure consists of six parts. Part I describes the model in detail and presents an overview of lessons learned in the collaboration between industry and academia. Part II deals with the first step of the Stairway to Heaven, in which R&D adopts agile work practices. Part III of the book combines the next two phases, i.e., continuous integration (CI) and continuous delivery (CD), as they are closely intertwined. Part IV is concerned with the highest level, referred to as “R&D as an innovation system,” while Part V addresses a topic that is separate from the Stairway to Heaven and yet critically important in large organizations: organizational performance metrics that capture data, and visualizations of the status of software assets, defects and teams. Lastly, Part VI presents the perspectives of two of the SC partner companies.

The success of product line engineering techniques in the last 15 years has popularized the use of software variability as a key modeling approach for describing the commonality and variability of systems at all stages of the software lifecycle. Software product lines enable a family of products to share a common core platform, while allowing for product specific functionality being built on top of the platform. Many companies have exploited the concept of software product lines to increase the resources that focus on highly differentiating functionality and thus improve their competitiveness with higher quality and reusable products and decreasing the time-to-market condition.

Many books on product line engineering either introduce specific product line techniques or include brief summaries of industrial cases. From these sources, it is difficult to gain a comprehensive understanding of the various dimensions and aspects of software variability. Here the editors address this gap by providing a comprehensive reference on the notion of variability modeling in the context of software product line engineering, presenting an overview of the techniques proposed for variability modeling and giving a detailed perspective on software variability management.

Their book is organized in four main parts, which guide the reader through the various aspects and dimensions of software variability. Part 1 which is mostly written by the editors themselves introduces the major topics related to software variability modeling, thus providing a multi-faceted view of both technological and management issues. Next, part 2 of the book comprises four separate chapters dedicated to research and commercial tools. Part 3 then continues with the most practical viewpoint of the book presenting three different industry cases on how variability is managed in real industry projects. Finally, part 4 concludes the book and encompasses six different chapters on emerging research topics in software variability like e.g. service-oriented or dynamic software product lines, or variability and aspect orientation.

Each chapter briefly summarizes “What you will learn in this chapter”, so both expert and novice readers can easily locate the topics dealt with. Overall, the book captures the current state of the art and best practices, and indicates important open research challenges as well as possible pitfalls. Thus it serves as a reference for researchers and practitioners in software variability management, allowing them to develop the next set of solutions, techniques and methods in this complicated and yet fascinating field of software engineering.

As software R&D investment increases, the benefits from short feedback cycles using technologies such as continuous deployment, experimentation-based development, and multidisciplinary teams require a fundamentally different strategy and process. This book will cover the three overall challenges that companies are grappling with: speed, data and ecosystems. Speed deals with shortening the cycle time in R&D. Data deals with increasing the use of and benefit from the massive amounts of data that companies collect. Ecosystems address the transition of companies from being internally focused to being ecosystem oriented by analyzing what the company is uniquely good at and where it adds value.

As software R&D investment increases, the benefits from short feedback cycles using technologies such as continuous deployment, experimentation-based development, and multidisciplinary teams require a fundamentally different strategy and process. This book will cover the three overall challenges that companies are grappling with: speed, data and ecosystems. Speed deals with shortening the cycle time in R&D. Data deals with increasing the use of and benefit from the massive amounts of data that companies collect. Ecosystems address the transition of companies from being internally focused to being ecosystem oriented by analyzing what the company is uniquely good at and where it adds value.

This book celebrates the 10-year anniversary of Software Center (a collaboration between 18 European companies and five Swedish universities) by presenting some of the most impactful and relevant journal or conference papers that researchers in the center have published over the last decade.

The book is organized around the five themes around which research in Software Center is organized, i.e. Continuous Delivery, Continuous Architecture, Metrics, Customer Data and Ecosystems Driven Development, and AI Engineering. The focus of the Continuous Delivery theme is to help companies to continuously build high quality products with the right degree of automation. The Continuous Architecture theme addresses challenges that arise when balancing the need for architectural quality and more agile ways of working with shorter development cycles. The Metrics theme studies and provides insight to understand, monitor and improve software processes, products and organizations. The fourth theme, Customer Data and Ecosystem Driven Development, helps companies make sense of the vast amounts of data that are continuously collected from products in the field. Eventually, the theme of AI Engineering addresses the challenge that many companies struggle with in terms of deploying machine- and deep-learning models in industrial contexts with production quality. Each theme has its own part in the book and each part has an introduction chapter and then a carefully selected reprint of the most important papers from that theme.

This book provides essential insights on the adoption of modern software engineering practices at large companies producing software-intensive systems, where hundreds or even thousands of engineers collaborate to deliver on new systems and new versions of already deployed ones. It is based on the findings collected and lessons learned at the Software Center (SC), a unique collaboration between research and industry, with Chalmers University of Technology, Gothenburg University and Malmö University as academic partners and Ericsson, AB Volvo, Volvo Car Corporation, Saab Electronic Defense Systems, Grundfos, Axis Communications, Jeppesen (Boeing) and Sony Mobile as industrial partners.

The 17 chapters present the “Stairway to Heaven” model, which represents the typical evolution path companies move through as they develop and mature their software engineering capabilities. The chapters describe theoretical frameworks, conceptual models and, most importantly, the industrial experiences gained by the partner companies in applying novel software engineering techniques.

The book’s structure consists of six parts. Part I describes the model in detail and presents an overview of lessons learned in the collaboration between industry and academia. Part II deals with the first step of the Stairway to Heaven, in which R&D adopts agile work practices. Part III of the book combines the next two phases, i.e., continuous integration (CI) and continuous delivery (CD), as they are closely intertwined. Part IV is concerned with the highest level, referred to as “R&D as an innovation system,” while Part V addresses a topic that is separate from the Stairway to Heaven and yet critically important in large organizations: organizational performance metrics that capture data, and visualizations of the status of software assets, defects and teams. Lastly, Part VI presents the perspectives of two of the SC partner companies.

The success of product line engineering techniques in the last 15 years has popularized the use of software variability as a key modeling approach for describing the commonality and variability of systems at all stages of the software lifecycle. Software product lines enable a family of products to share a common core platform, while allowing for product specific functionality being built on top of the platform. Many companies have exploited the concept of software product lines to increase the resources that focus on highly differentiating functionality and thus improve their competitiveness with higher quality and reusable products and decreasing the time-to-market condition.

Many books on product line engineering either introduce specific product line techniques or include brief summaries of industrial cases. From these sources, it is difficult to gain a comprehensive understanding of the various dimensions and aspects of software variability. Here the editors address this gap by providing a comprehensive reference on the notion of variability modeling in the context of software product line engineering, presenting an overview of the techniques proposed for variability modeling and giving a detailed perspective on software variability management.

Their book is organized in four main parts, which guide the reader through the various aspects and dimensions of software variability. Part 1 which is mostly written by the editors themselves introduces the major topics related to software variability modeling, thus providing a multi-faceted view of both technological and management issues. Next, part 2 of the book comprises four separate chapters dedicated to research and commercial tools. Part 3 then continues with the most practical viewpoint of the book presenting three different industry cases on how variability is managed in real industry projects. Finally, part 4 concludes the book and encompasses six different chapters on emerging research topics in software variability like e.g. service-oriented or dynamic software product lines, or variability and aspect orientation.

Each chapter briefly summarizes “What you will learn in this chapter”, so both expert and novice readers can easily locate the topics dealt with. Overall, the book captures the current state of the art and best practices, and indicates important open research challenges as well as possible pitfalls. Thus it serves as a reference for researchers and practitioners in software variability management, allowing them to develop the next set of solutions, techniques and methods in this complicated and yet fascinating field of software engineering.