Software Engineering at Google: Lessons Learned from Programming Over Time
- Forfattere
- Indlæser
- Forlag
Today, software engineers need to know not only how to program effectively but also how to develop proper engineering practices to make their codebase sustainable and healthy. This book emphasizes this difference between programming and software engineering.
How can software engineers manage a living codebase that evolves and responds to changing requirements and demands over the length of its life? Based on their experience at Google, software engineers Titus Winters and Hyrum Wright, along with technical writer Tom Manshreck, present a candid and insightful look at how some of the world's leading practitioners construct and maintain software. This book covers Google's unique engineering culture, processes, and tools and how these aspects contribute to the effectiveness of an engineering organization.
You'll explore three fundamental principles that software organizations should keep in mind when designing, architecting, writing, and maintaining code:
How time affects the sustainability of software and how to make your code resilient over time How scale affects the viability of software practices within an engineering organization What trade-offs a typical engineer needs to make when evaluating design and development decisions
© 2021 Ascent Audio (Lydbog): 9781663728050
Udgivelsesdato
Lydbog: 29. januar 2021
Bøger, der ligner Software Engineering at Google: Lessons Learned from Programming Over Time
- Fundamentals of Software Architecture: An Engineering Approach Neal Ford, Mark Richards
- Building Microservices: Designing Fine-Grained Systems Sam Newman
- Clean Architecture: A Craftsman's Guide to Software Structure and Design Robert C. Martin
- Clean Agile: Back to Basics Robert C. Martin
- Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems Martin Kleppmann
- Fundamentals of Data Engineering: Plan and Build Robust Data Systems Matt Housley, Joe Reis
- Coders at Work: Reflections on the Craft of Programming Peter Seibel
- Monolith to Microservices: Evolutionary Patterns to Transform Your Monolith Sam Newman
- The Clean Coder: A Code of Conduct for Professional Programmers Robert C. Martin
- Data Mesh: Delivering Data-Driven Value at Scale Zhamak Dehghani
- Software Architecture: The Hard Parts: Modern Trade-Off Analyses for Distributed Architectures Neal Ford, Mark Richards, Zhamak Dehghani, Pramod Sadalage
- AI and Machine Learning for Coders: A Programmer's Guide to Artificial Intelligence Laurence Moroney
- Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking Foster Provost, Tom Fawcett
- Site Reliability Engineering: How Google Runs Production Systems Chris Jones, Betsy Beyer, Jennifer Petoff, Niall Richard Murphy
- Learning Systems Thinking: Essential Non-Linear Skills and Practices for Software Professionals Diana Montalion
- Managing Humans: Biting and Humorous Tales of a Software Engineering Manager Michael Lopp
- Security Chaos Engineering: Sustaining Resilience in Software and Systems Aaron Rinehart, Kelly Shortridge
- Machine Learning Interviews: Kickstart Your Machine Learning and Data Career Susan Shu Chang
- Database Internals: A Deep Dive into How Distributed Data Systems Work, 1st Edition Alex Petrov
- The Innovation Ultimatum: How Six Strategic Technologies Will Reshape Every Business in the 2020s Steve Brown
- AI at the Edge: Solving Real-World Problems with Embedded Machine Learning Jenny Plunkett, Daniel Situnayake
- Clean Code: A Handbook of Agile Software Craftsmanship Robert C. Martin
- Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python Sofien Kaabar
- Economics in Plain English: 300+ Essential Economic Terms You Need to Know David A Mayer
- Deep Learning John D. Kelleher
- Information Architecture: For the Web and Beyond Louis Rosenfeld, Jorge Arango, Peter Morville
- AI and the Future of Banking Tony Boobier
- Shocks, Crises, and False Alarms: How to Assess True Macroeconomic Risk Paul Swartz, Philipp Carlsson-Szlezak
- The Business of Venture Capital : The Art of Raising a Fund, Structuring Investments, Portfolio Management and Exits, 3rd Edition: The Art of Raising a Fund, Structuring Investments, Portfolio Management, and Exits, 3rd Edition Mahendra Ramsinghani
- Prompt Engineering for Generative AI: Future-Proof Inputs for Reliable AI Outputs Mike Taylor, James Phoenix
- The Little Book of Valuation: How to Value a Company, Pick a Stock, and Profit, Updated Edition Aswath Damodaran
- The Politics Industry: How Political Innovation Can Break Partisan Gridlock and Save Our Democracy Michael E. Porter, Katherine M. Gehl
- Designing Machine Learning Systems: An Iterative Process for Production-Ready Applications Chip Huyen
- The Year in Tech, 2024: The Insights You Need from Harvard Business Review Harvard Business Review
- Neuroplasticity Moheb Costandi
- Google Cloud Cookbook: Practical Solutions for Building and Deploying Cloud Services, 1st Edition Rui Costa, Drew Hodun
- Kissinger the Negotiator: Lessons from Dealmaking at the Highest Level James K. Sebenius, R. Nicholas Burns, Robert H. Mnookin
- Automate This: How Algorithms Came to Rule Our World Christopher Steiner
- Artificial Intelligence: Modern Magic or Dangerous Future? Yorick Wilks
- A Hacker's Mind: How the Powerful Bend Society's Rules, and How to Bend them Back Bruce Schneier
- Casual Artificial Intelligence John K. Thompson, Judith S. Hurwitz
- The Digital Mindset: What It Really Takes to Thrive in the Age of Data, Algorithms, and AI Tsedal Neeley, Paul Leonardi
- The Engineering Executive's Primer: Impactful Technical Leadership Will Larson
- Gorillas Can Dance: Lessons from Microsoft and Other Corporations on Partnering with Startups Shameen Prashantham
- Boombustology: Spotting Financial Bubbles Before They Burst (2nd Edition): Spotting Financial Bubbles Before They Burst 2nd Edition Vikram Mansharamani
- Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning Alex J. Gutman, Jordan Goldmeier
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