Caitlin Sadowski(editor)
Dr. Caitlin Sadowski is a software engineer at Google in Mountain View, California, where she aims to understand and improve developer workflows. Currently, she is helping Chrome developers make data-driven decisions as the manager of the Chrome Metrics team. In the past, she made static analysis useful at Google by creating the Tricorder program analysis platform, and then co-founded a team that provides ongoing insight into how developers spend their time and what makes them effective (the Engineering Productivity Research team). She has a PhD from the University of California at Santa Cruz where she worked on a variety of research topics related to programming languages, software engineering, and human computer interaction. She enjoys baking with her three-year-old, Naru.Dr. Caitlin Sadowski is a software engineer at Google in Mountain View, California, where she aims to understand and improve developer workflows. Currently, she is helping Chrome developers make data-driven decisions as the manager of the Chrome Metrics team. In the past, she made static analysis useful at Google by creating the Tricorder program analysis platform, and then co-founded a team that provides ongoing insight into how developers spend their time and what makes them effective (the Engineering Productivity Research team). She has a PhD from the University of California at Santa Cruz where she worked on a variety of research topics related to programming languages, software engineering, and human computer interaction. She enjoys baking with her three-year-old, Naru.
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Dr. Caitlin Sadowski is a software engineer at Google in Mountain View, California, where she aims to understand and improve developer workflows. Currently, she is helping Chrome developers make data-driven decisions as the manager of the Chrome Metrics team. In the past, she made static analysis useful at Google by creating the Tricorder program analysis platform, and then co-founded a team that provides ongoing insight into how developers spend their time and what makes them effective (the Engineering Productivity Research team). She has a PhD from the University of California at Santa Cruz where she worked on a variety of research topics related to programming languages, software engineering, and human computer interaction. She enjoys baking with her three-year-old, Naru.
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Rethinking Productivity in Software Engineering
Get the most out of this Open Access foundational reference and improve the productivity of your software teams. This open access book collects the wisdom of the 2017 "Dagstuhl" seminar on productivity in software engineering, a meeting of community leaders, who came together with the goal of rethinking traditional definitions and measures of productivity. The results of their work, Rethinking Productivity in Software Engineering, includes chapters covering definitions and core concepts related to productivity, guidelines for measuring productivity in specific contexts, best practices and pitfalls, and theories and open questions on productivity. You'll benefit from the many short chapters, each offering a focused discussion on one aspect of productivity in software engineering. Readers in many fields and industries will benefit from their collected work. Developers wanting to improve their personal productivity, will learn effective strategies for overcoming common issues that interfere with progress. Organizations thinking about building internal programs for measuring productivity of programmers and teams will learn best practices from industry and researchers in measuring productivity. And researchers can leverage the conceptual frameworks and rich body of literature in the book to effectively pursue new research directions.
