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Rethinking Productivity in Software Engineering

Overview of attention for book
Cover of 'Rethinking Productivity in Software Engineering'

Table of Contents

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    Book Overview
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    Chapter 1 The Mythical 10x Programmer
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    Chapter 2 No Single Metric Captures Productivity
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    Chapter 3 Why We Should Not Measure Productivity
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    Chapter 4 Defining Productivity in Software Engineering
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    Chapter 5 A Software Development Productivity Framework
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    Chapter 6 Individual, Team, Organization, and Market: Four Lenses of Productivity
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    Chapter 7 Software Productivity Through the Lens of Knowledge Work
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    Chapter 8 Factors That Influence Productivity: A Checklist
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    Chapter 9 How Do Interruptions Affect Productivity?
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    Chapter 10 Happiness and the Productivity of Software Engineers
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    Chapter 11 Dark Agile: Perceiving People As Assets, Not Humans
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    Chapter 12 Developers’ Diverging Perceptions of Productivity
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    Chapter 13 Human-Centered Methods to Boost Productivity
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    Chapter 14 Using Biometric Sensors to Measure Productivity
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    Chapter 15 How Team Awareness Influences Perceptions of Developer Productivity
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    Chapter 16 Software Engineering Dashboards: Types, Risks, and Future
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    Chapter 17 The COSMIC Method for Measuring the Work-Output Component of Productivity
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    Chapter 18 Benchmarking: Comparing Apples to Apples
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    Chapter 19 Removing Software Development Waste to Improve Productivity
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    Chapter 20 Organizational Maturity: The Elephant Affecting Productivity
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    Chapter 21 Does Pair Programming Pay Off?
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    Chapter 22 Fitbit for Developers: Self-Monitoring at Work
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    Chapter 23 Reducing Interruptions at Work with FlowLight
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    Chapter 24 Enabling Productive Software Development by Improving Information Flow
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    Chapter 25 Mindfulness as a Potential Tool for Productivity
Overall attention for this book and its chapters
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Mentioned by

2 news outlets
1 blog
502 tweeters


11 Dimensions

Readers on

56 Mendeley
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Rethinking Productivity in Software Engineering
Published by
Apress, December 2018
DOI 10.1007/978-1-4842-4221-6
978-1-4842-4220-9, 978-1-4842-4221-6

Sadowski, Caitlin, Zimmermann, Thomas

Twitter Demographics

The data shown below were collected from the profiles of 502 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 56 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 56 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 12 21%
Student > Ph. D. Student 11 20%
Student > Bachelor 10 18%
Professor > Associate Professor 5 9%
Other 3 5%
Other 8 14%
Unknown 7 13%
Readers by discipline Count As %
Computer Science 29 52%
Business, Management and Accounting 5 9%
Psychology 4 7%
Engineering 3 5%
Economics, Econometrics and Finance 1 2%
Other 5 9%
Unknown 9 16%