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Motivation for a psychological approach; Research methods; Programming as human performance; Programming style; Software quality evaluation; Team organizations and group processes; Database systems and data models; Database query and manipulation languages; Natural language; Interactive interface issues; Designing interactive systems.
Throughout human history, thoughts, values and behaviours have been coloured by language and the prevailing view of the universe. With the advent of Quantum Mechanics, relativity, non-Euclidean geometries, non-Aristotelian logic and General Semantics, the scientific view of the world has changed dramatically from just a few decades ago. Nonetheless, human thinking is still deeply rooted in the cosmology of the middle ages. This is the book to change your way of perceiving yourself -- and the universe. Some say it's materialistic, others call it scientific and still others insist it's mystical. It is all of these -- and none. The book for the 21st Century, complete with exercises. Picks up where "Prometheus Rising" left off. Some say it's materialistic, others call it scientific and still others insist it's mystical. It is all of these -- and none.
Discover or Revisit One of the Most Popular Books in Computing This landmark 1971 classic is reprinted with a new preface, chapter-by-chapter commentary, and straight-from-the-heart observations on topics that affect the professional life of programmers. Long regarded as one of the first books to pioneer a people-oriented approach to computing, The Psychology of Computer Programming endures as a penetrating analysis of the intelligence, skill, teamwork, and problem-solving power of the computer programmer. Finding the chapters strikingly relevant to today's issues in programming, Gerald M. Weinberg adds new insights and highlights the similarities and differences between now and then. Using a conversational style that invites the reader to join him, Weinberg reunites with some of his most insightful writings on the human side of software engineering. Topics include egoless programming, intelligence, psychological measurement, personality factors, motivation, training, social problems on large projects, problem-solving ability, programming language design, team formation, the programming environment, and much more. Dorset House Publishing is proud to make this important text available to new generations of programmers--and to encourage readers of the first edition to return to its valuable lessons.
Build Applications, Websites, and Software Solutions that Feel Faster, More Efficient, and More Considerate of Users’ Time! One hidden factor powerfully influences the way users react to your software, hardware, User Interfaces (UI), or web applications: how those systems utilize users’ time. Now, drawing on the nearly 40 years of human computer interaction research–including his own pioneering work–Dr. Steven Seow presents state-of-the-art best practices for reflecting users’ subjective perceptions of time in your applications and hardware. Seow begins by introducing a simple model that explains how users perceive and expend time as they interact with technology. He offers specific guidance and recommendations related to several key aspects of time and timing–including user tolerance, system responsiveness, progress indicators, completion time estimates, and more. Finally, he brings together proven techniques for impacting users’ perception of time drawn from multiple disciplines and industries, ranging from psychology to retail, animal research to entertainment. • Discover how time and timing powerfully impact user perception, emotions, and behavior • Systematically make your applications more considerate of users’ time • Avoid common mistakes that consistently frustrate or infuriate users • Manage user perceptions and tolerance, and build systems that are perceived as faster • Optimize “flow” to make users feel more productive, empowered, and creative • Make reasonable and informed tradeoffs that maximize limited development resources • Learn how to test usability issues related to time–including actual vs. perceived task duration Designing and Engineering Time is for every technology developer, designer, engineer, architect, usability specialist, manager, and marketer. Using its insights and techniques, technical and non-technical professionals can work together to build systems and applications that provide far more value–and create much happier users. Steven C. Seow has a unique combination of experience in both experimental psychology and software usability. He joined Microsoft as a User Researcher after completing his Ph.D. in Experimental Psychology at Brown University with a research focus on human timing and information theory models of human performance. Seow holds Bachelor’s and Master’s Degrees in Forensic Psychology from John Jay College of Criminal Justice, and wrote his master’s thesis on distortions in time perception. For more information about Steven Seow and his research, visit his website at www.StevenSeow.com. informit.com/aw
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.
Covering a variety of areas including software analysis, design, coding and maintenance, this text details the research conducted since the 1970s in this fast-developing field before going on to define a computer program from the viewpoint of computing and cognitive psychology. The two essential sides of programming, software production and software understanding, are given detailed treatment, with parallels drawn throughout between studies on processing texts written in natural language and processing computer programs. Of particular interest to researchers, practitioners and graduates in cognitive psychology, cognitive ergonomics and computer science.
"Learning Statistics with R" covers the contents of an introductory statistics class, as typically taught to undergraduate psychology students, focusing on the use of the R statistical software and adopting a light, conversational style throughout. The book discusses how to get started in R, and gives an introduction to data manipulation and writing scripts. From a statistical perspective, the book discusses descriptive statistics and graphing first, followed by chapters on probability theory, sampling and estimation, and null hypothesis testing. After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book. For more information (and the opportunity to check the book out before you buy!) visit http://ua.edu.au/ccs/teaching/lsr or http://learningstatisticswithr.com
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.
An industry insider explains why there is so much bad software—and why academia doesn't teach programmers what industry wants them to know. Why is software so prone to bugs? So vulnerable to viruses? Why are software products so often delayed, or even canceled? Is software development really hard, or are software developers just not that good at it? In The Problem with Software, Adam Barr examines the proliferation of bad software, explains what causes it, and offers some suggestions on how to improve the situation. For one thing, Barr points out, academia doesn't teach programmers what they actually need to know to do their jobs: how to work in a team to create code that works reliably and can be maintained by somebody other than the original authors. As the size and complexity of commercial software have grown, the gap between academic computer science and industry has widened. It's an open secret that there is little engineering in software engineering, which continues to rely not on codified scientific knowledge but on intuition and experience. Barr, who worked as a programmer for more than twenty years, describes how the industry has evolved, from the era of mainframes and Fortran to today's embrace of the cloud. He explains bugs and why software has so many of them, and why today's interconnected computers offer fertile ground for viruses and worms. The difference between good and bad software can be a single line of code, and Barr includes code to illustrate the consequences of seemingly inconsequential choices by programmers. Looking to the future, Barr writes that the best prospect for improving software engineering is the move to the cloud. When software is a service and not a product, companies will have more incentive to make it good rather than “good enough to ship."
Aimed at improving a programmers ability for altering code to fit changing requirements and for detecting and correcting errors, this book argues for a new way of thinking about maintaining software. It proposes the use of a set of human factors principles that govern the programmer-software-event world interactions and form the core of the maintenance process. The book is thus highly valuable for systems analysts and programmers, managers seeking to reduce costs, researchers looking at solutions to the maintenance problem, and students learning to write clear unambiguous programs.