Ivan Mistrik

Bio: Ivan Mistrik is an academic researcher. The author has contributed to research in topics: Software architecture & Software development. The author has an hindex of 10, co-authored 25 publications receiving 255 citations.

Collaborative Software Engineering: Challenges and Prospects

Abstract: 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

Abstract: 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

Abstract: 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.

Software Architecture for Big Data and the Cloud

Abstract: Software Architecture for Big Data and the Cloud is designed to be a single resource that brings together research on how software architectures can solve the challenges imposed by building big data software systems. The challenges of big data on the software architecture can relate to scale, security, integrity, performance, concurrency, parallelism, and dependability, amongst others. Big data handling requires rethinking architectural solutions to meet functional and non-functional requirements related to volume, variety and velocity. The book's editors have varied and complementary backgrounds in requirements and architecture, specifically in software architectures for cloud and big data, as well as expertise in software engineering for cloud and big data. This book brings together work across different disciplines in software engineering, including work expanded from conference tracks and workshops led by the editors. Key Features : - Discusses systematic and disciplined approaches to building software architectures for cloud and big data with state-of-the-art methods and techniques - Presents case studies involving enterprise, business, and government service deployment of big data applications - Shares guidance on theory, frameworks, methodologies, and architecture for cloud and big data

Relating System Quality and Software Architecture

Abstract: System Quality and Software Architecture collects state-of-the-art knowledge on how to intertwine software quality requirements with software architecture and how quality attributes are exhibited by the architecture of the system. Contributions from leading researchers and industry evangelists detail the techniques required to achieve quality management in software architecting, and the best way to apply these techniques effectively in various application domains (especially in cloud, mobile and ultra-large-scale/internet-scale architecture) Taken together, these approaches show how to assess the value of total quality management in a software development process, with an emphasis on architecture. The book explains how to improve system quality with focus on attributes such as usability, maintainability, flexibility, reliability, reusability, agility, interoperability, performance, and more. It discusses the importance of clear requirements, describes patterns and tradeoffs that can influence quality, and metrics for quality assessment and overall system analysis. The last section of the book leverages practical experience and evidence to look ahead at the challenges faced by organizations in capturing and realizing quality requirements, and explores the basis of future work in this area.Explains how design decisions and method selection influence overall system quality, and lessons learned from theories and frameworks on architectural qualityShows how to align enterprise, system, and software architecture for total qualityIncludes case studies, experiments, empirical validation, and systematic comparisons with other approaches already in practice.

Curating GitHub for engineered software projects

Abstract: Software forges like GitHub host millions of repositories. Software engineering researchers have been able to take advantage of such a large corpora of potential study subjects with the help of tools like GHTorrent and Boa. However, the simplicity in querying comes with a caveat: there are limited means of separating the signal (e.g. repositories containing engineered software projects) from the noise (e.g. repositories containing home work assignments). The proportion of noise in a random sample of repositories could skew the study and may lead to researchers reaching unrealistic, potentially inaccurate, conclusions. We argue that it is imperative to have the ability to sieve out the noise in such large repository forges. We propose a framework, and present a reference implementation of the framework as a tool called reaper, to enable researchers to select GitHub repositories that contain evidence of an engineered software project. We identify software engineering practices (called dimensions) and propose means for validating their existence in a GitHub repository. We used reaper to measure the dimensions of 1,857,423 GitHub repositories. We then used manually classified data sets of repositories to train classifiers capable of predicting if a given GitHub repository contains an engineered software project. The performance of the classifiers was evaluated using a set of 200 repositories with known ground truth classification. We also compared the performance of the classifiers to other approaches to classification (e.g. number of GitHub Stargazers) and found our classifiers to outperform existing approaches. We found stargazers-based classifier (with 10 as the threshold for number of stargazers) to exhibit high precision (97%) but an inversely proportional recall (32%). On the other hand, our best classifier exhibited a high precision (82%) and a high recall (86%). The stargazer-based criteria offers precision but fails to recall a significant portion of the population.

Software engineering economics

Abstract: This paper summarizes the current state of the art and recent trends in software engineering economics. It provides an overview of economic analysis techniques and their applicability to software engineering and management. It surveys the field of software cost estimation, including the major estimation techniques available, the state of the art in algorithmic cost models, and the outstanding research issues in software cost estimation.

MODAClouds: a model-driven approach for the design and execution of applications on multiple clouds

Abstract: Cloud computing is emerging as a major trend in the ICT industry. While most of the attention of the research community is focused on considering the perspective of the Cloud providers, offering mechanisms to support scaling of resources and interoperability and federation between Clouds, the perspective of developers and operators willing to choose the Cloud without being strictly bound to a specific solution is mostly neglected. We argue that Model-Driven Development can be helpful in this context as it would allow developers to design software systems in a cloud-agnostic way and to be supported by model transformation techniques into the process of instantiating the system into specific, possibly, multiple Clouds. The MODAClouds (MOdel-Driven Approach for the design and execution of applications on multiple Clouds) approach we present here is based on these principles and aims at supporting system developers and operators in exploiting multiple Clouds for the same system and in migrating (part of) their systems from Cloud to Cloud as needed. MODAClouds offers a quality-driven design, development and operation method and features a Decision Support System to enable risk analysis for the selection of Cloud providers and for the evaluation of the Cloud adoption impact on internal business processes. Furthermore, MODAClouds offers a run-time environment for observing the system under execution and for enabling a feedback loop with the design environment. This allows system developers to react to performance fluctuations and to re-deploy applications on different Clouds on the long term.

The (R) Evolution of social media in software engineering

Abstract: Software developers rely on media to communicate, learn, collaborate, and coordinate with others. Recently, social media has dramatically changed the landscape of software engineering, challenging some old assumptions about how developers learn and work with one another. We see the rise of the social programmer who actively participates in online communities and openly contributes to the creation of a large body of crowdsourced socio-technical content. In this paper, we examine the past, present, and future roles of social media in software engineering. We provide a review of research that examines the use of different media channels in software engineering from 1968 to the present day. We also provide preliminary results from a large survey with developers that actively use social media to understand how they communicate and collaborate, and to gain insights into the challenges they face. We find that while this particular population values social media, traditional channels, such as face-to-face communication, are still considered crucial. We synthesize findings from our historical review and survey to propose a roadmap for future research on this topic. Finally, we discuss implications for research methods as we argue that social media is poised to bring about a paradigm shift in software engineering research.