Ivan Mistrik

Collaborative Software Engineering: Challenges and Prospects

Much work is presently ongoing in collaborative software engineering research. This work is beginning to make serious inroads into our ability to more effectively practice collaborative software engineering, with best practices, processes, tools, metrics, and other techniques becoming available for day-to-day use. However, we have not yet reached the point where the practice of collaborative software engineering is routine, without surprises, and generally as optimal as possible. This chapter summarizes the main findings of this book, draws some conclusions on these findings and looks at the prospects for software engineers in dealing with the challenges of collaborative software development. The chapter ends with prospects for collaborative software engineering.

Collaborative Software Engineering: Concepts and Techniques

Collaboration is a central activity in software engineering, as all but the most trivial projects involve multiple engineers working together. Hence, understanding software engineering collaboration is important for both engineers and researchers. This chapter presents a framework for understanding software engineering collaboration, focused on three key insights: (1) software engineering collaboration is model-based, centered on the creation and negotiation of shared meaning within the project artifacts that contain the models that describe the final working system; (2) software project management is a cross-cutting concern that creates the organizational structures under which collaboration is fostered (or dampened); and (3) global software engineering introduces many forms of distance – spatial, temporal, socio-cultural – into existing pathways of collaboration. Analysis of future trends highlight several ways engineers will be able to improve project collaboration, specifically, software development environments will shift to being totally Web-based, thereby opening the potential for social network site integration, greater participation by end-users in project development, and greater ease in global software engineering. Just as collaboration is inherent in software engineering, so are the fundamental tensions inherent in fostering collaboration; the chapter ends with these.

Architectural Knowledge Management in Global Software Development: A Review

Architectural Knowledge Management (AKM) aims to coordinate the knowledge produced and used during architecting a software system. Managing architectural knowledge effectively is a task that becomes even more critical and complex when operating in a distributed environment. Thus, software architectural practices, processes, and tools that work in collocated software development don’t necessarily scale up in a distributed environment. In this paper, we perform a literature review that looks at AKM in a Global Software Development (GSD) context. We attempt to synthesize AKM concepts, practices, tools and challenges important in GSD. In order to provide a common understanding for the central concepts of AKM in GSD in an abstract way, we have created a metamodel which is based on our literature review. The metamodel defines a set of architecture knowledge and global software development entities and their relationships.

Relating software requirements and architectures

Requirements engineering and software architecture have become established areas of software engineering research, education, and practice. Requirements engineering is concerned with discovering the purpose of a software system and the contexts in which it will be used (Nuseibeh and Easterbrook, 2000). Software architecture is concerned with the study of the structure of software, including its topology, properties, constituent components and their relationships and patterns of combination (Perry and Wolf, 1992). There have been significant research advances made in both software requirements and architectures, and fundamental differences and relationships between the two areas have come to light which are outlined.

Knowledge Management in the Global Software Engineering Environment

In this paper we consider the importance of explicit knowledge management, taking into account the growth of global software engineering and the importance of corporate knowledge. We conclude by suggesting specific areas of research which should be considered important for the implementation of knowledge management within global software engineering environments

Economics-Driven Software Architecture: Introduction

The purpose of this book is to introduce and discuss the concept of economics-driven software architecture (EDSA). The book covers various aspects of economics-driven architecting, including architecture-based economic modeling, tools and techniques for modularity decision support, the architecture and its relationship to project inception and evolution, economic aspects of architecture-based project management, architecture and its effects on risk management, and its relationship to agility.The purpose of this book is to introduce and discuss the concept of economics-driven software architecture (EDSA). The book covers various aspects of economics-driven architecting, including architecture-based economic modeling, tools and techniques for modularity decision support, the architecture and its relationship to project inception and evolution, economic aspects of architecture-based project management, architecture and its effects on risk management, and its relationship to agility.

The future of software engineering IN and FOR the cloud

Experts are predicting the cloud software market to grow at a high rate in the coming years. Merrill Lynch and Gartner predict the cloud computing market to be worth between

Introduction: relating requirements and architectures

160 and

Quality Concerns in Large Scale and Complex Software-intensive Systems

150 billion in 2013. Many computing services have now migrated to the cloud and many applications are becoming cloud-based and function as standalone or in orchestration with other cloud-based services. With the advent of the cloud and the reliance on Big Data, cloud-based systems are driving our digital economy and increasingly becoming pervasive in many daily applications. Cloud has become the backbone for many e-businesses; engineering, scientific and experimental processes; real-time control and monitoring data intensive systems such as disaster management, weather and climate predictions, which heavily depends on the Big Data thing. The dependability of these systems and their continuous evolution are essential pre-requisite for the success and prosperous growth of our digital economy. The “cloud wave” has urged the need for advancing the fundamentals of cloud software engineering, supporting the emergence and the advancement of this emergent digital economy.

Relating System Quality and Software Architecture: Foundations and Approaches

This book describes current understanding and use of the relationship between software requirements and software architectures.