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Are you working on a codebase where cost overruns, death marches, and heroic fights with legacy code monsters are the norm? Battle these adversaries with novel ways to identify and prioritize technical debt, based on behavioral data from how developers work with code. And that's just for starters. Because good code involves social design, as well as technical design, you can find surprising dependencies between people and code to resolve coordination bottlenecks among teams. Best of all, the techniques build on behavioral data that you already have: your version-control system. Join the fight for better code! Use statistics and data science to uncover both problematic code and the behavioral patterns of the developers who build your software. This combination gives you insights you can't get from the code alone. Use these insights to prioritize refactoring needs, measure their effect, find implicit dependencies between different modules, and automatically create knowledge maps of your system based on actual code contributions. In a radical, much-needed change from common practice, guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Discover a comprehensive set of practical analysis techniques based on version-control data, where each point is illustrated with a case study from a real-world codebase. Because the techniques are language neutral, you can apply them to your own code no matter what programming language you use. Guide organizational decisions with objective data by measuring how well your development teams align with the software architecture. Apply research findings from social psychology to software development, ensuring you get the tools you need to coach your organization towards better code. If you're an experienced programmer, software architect, or technical manager, you'll get a new perspective that will change how you work with code. What You Need: You don't have to install anything to follow along in the book. TThe case studies in the book use well-known open source projects hosted on GitHub. You'll use CodeScene, a free software analysis tool for open source projects, for the case studies. We also discuss alternative tooling options where they exist.
The idea for this workshop originated when I came across and read Martin Zelkowitz's book on Requirements for Software Engineering Environments (the proceedings of a small workshop held at the University of Maryland in 1986). Although stimulated by the book I was also disappointed in that it didn't adequately address two important questions - "Whose requirements are these?" and "Will the environment which meets all these requirements be usable by software engineers?". And thus was the decision made to organise this workshop which would explicitly address these two questions. As time went by setting things up, it became clear that our workshop would happen more than five years after the Maryland workshop and thus, at the same time as addressing the two questions above, this workshop would attempt to update the Zelkowitz approach. Hence the workshop acquired two halves, one dominated by discussion of what we already know about usability problems in software engineering and the other by discussion of existing solutions (technical and otherwise) to these problems. This scheme also provided a good format for bringing together those in the HeI community concerned with the human factors of software engineering and those building tools to solve acknowledged, but rarely understood problems.
Jack the Ripper and legacy codebases have more in common than you'd think. Inspired by forensic psychology methods, you'll learn strategies to predict the future of your codebase, assess refactoring direction, and understand how your team influences the design. With its unique blend of forensic psychology and code analysis, this book arms you with the strategies you need, no matter what programming language you use. Software is a living entity that's constantly changing. To understand software systems, we need to know where they came from and how they evolved. By mining commit data and analyzing the history of your code, you can start fixes ahead of time to eliminate broken designs, maintenance issues, and team productivity bottlenecks. In this book, you'll learn forensic psychology techniques to successfully maintain your software. You'll create a geographic profile from your commit data to find hotspots, and apply temporal coupling concepts to uncover hidden relationships between unrelated areas in your code. You'll also measure the effectiveness of your code improvements. You'll learn how to apply these techniques on projects both large and small. For small projects, you'll get new insights into your design and how well the code fits your ideas. For large projects, you'll identify the good and the fragile parts. Large-scale development is also a social activity, and the team's dynamics influence code quality. That's why this book shows you how to uncover social biases when analyzing the evolution of your system. You'll use commit messages as eyewitness accounts to what is really happening in your code. Finally, you'll put it all together by tracking organizational problems in the code and finding out how to fix them. Come join the hunt for better code! What You Need: You need Java 6 and Python 2.7 to run the accompanying analysis tools. You also need Git to follow along with the examples.
This book identifies areas that represent new needs and opportunities for human factors research in the coming decades. It is forward-looking, problem oriented, and selectively focused on national or global problems, including productivity in organizations, education and training, employment and disabilities, health care, and environmental change; technology issues, including communications technology and telenetworking, information access and usability, emerging technologies, automation, and flexible manufacturing, and advanced transportation systems; and human performance, including cognitive performance under stress and aiding intellectual work.
A successful digital transformation must start with a conversational transformation. Today, software organizations are transforming the way work gets done through practices like Agile, Lean, and DevOps. But as commonly implemented as these methods are, many transformations still fail, largely because the organization misses a critical step: transforming their culture and the way people communicate. Agile Conversations brings a practical, step-by-step guide to using the human power of conversation to build effective, high-performing teams to achieve truly Agile results. Consultants Douglas Squirrel and Jeffrey Fredrick show readers how to utilize the Five Conversations to help teams build trust, alleviate fear, answer the “whys,” define commitments, and hold everyone accountable.These five conversations give teams everything they need to reach peak performance, and they are exactly what’s missing from too many teams today. Stop focusing on processes and practices that leave your organization stuck with culture-less rituals. Instead, unleash the unique human power of conversation.
This is the first handbook to cover comprehensively both software engineering and knowledge engineering - two important fields that have become interwoven in recent years. Over 60 international experts have contributed to the book. Each chapter has been written in such a way that a practitioner of software engineering and knowledge engineering can easily understand and obtain useful information. Each chapter covers one topic and can be read independently of other chapters, providing both a general survey of the topic and an in-depth exposition of the state of the art. Practitioners will find this handbook useful when looking for solutions to practical problems. Researchers can use it for quick access to the background, current trends and most important references regarding a certain topic.The handbook consists of two volumes. Volume One covers the basic principles and applications of software engineering and knowledge engineering.Volume Two will cover the basic principles and applications of visual and multimedia software engineering, knowledge engineering, data mining for software knowledge, and emerging topics in software engineering and knowledge engineering.
Psychology provides a backdrop for most of the study of human*b1computer interaction. In this volume the psychological issues that pertain to programming, rather than systems design, are examined in four sections: Theoretical and Methodological Issues; Language Design and Skill Acquisition; Expert Programming; and the Future.****The book was inspired by working groups in France and the United Kingdom but also includes work by major North American figures (such as Curtis and Soloway). It is the first comprehensive work on this topic since the early 1980s.
Provides a framework for thinking about how software developers and development teams create software, as well as presenting strategies and techniques for improving individual and team performance
This volume presents papers from the 10th Working Conference of the IFIP WG 8.6 on the adoption and diffusion of information systems and technologies. It explores the dynamics of how some technological innovation efforts succeed while others fail. The book looks to expand the research agenda, paying special attention to the areas of theoretical perspectives, methodologies, and organizational sectors.