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The Evidence-Driven Software Engineer: Practical Systems for Quality, Speed, and Continuous Delivery
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ISBN13: 9798170222131
Publisher: Independently Published
Pages: 230
Weight: 0.95
Height: 0.60 Width: 6.00 Depth: 9.00
Language: English
Publisher: Independently Published
Pages: 230
Weight: 0.95
Height: 0.60 Width: 6.00 Depth: 9.00
Language: English
Build Better Software by Replacing Assumptions with Evidence.
Software teams are surrounded by frameworks, tools, methodologies, productivity claims, and technical opinions. But the strongest engineering decisions are not based on trends or whoever speaks the loudest-they are based on measurable evidence, rapid feedback, disciplined experimentation, and a clear understanding of trade-offs.
Software teams are surrounded by frameworks, tools, methodologies, productivity claims, and technical opinions. But the strongest engineering decisions are not based on trends or whoever speaks the loudest-they are based on measurable evidence, rapid feedback, disciplined experimentation, and a clear understanding of trade-offs.
The Evidence-Driven Software Engineer: Practical Systems for Quality, Speed, and Continuous Delivery is a practical guide for developers, technical leads, engineering managers, architects, students, and growing software teams who want to improve how software is designed, tested, delivered, operated, and continuously improved.
Rather than prescribing one best methodology, this book teaches you how to evaluate engineering practices in your own environment and determine what actually works.
Inside, you will learn how to:
Make better technical and architectural decisions using evidence instead of assumptions
Measure delivery performance without falling into vanity metrics or developer surveillance
Improve software quality, maintainability, reliability, security, and changeability
Design testing strategies that provide faster and more useful feedback
Build effective continuous integration and continuous delivery systems
Reduce deployment risk through progressive delivery and reliable recovery practices
Use observability, SLOs, error budgets, and incident evidence to strengthen production reliability
Integrate security throughout the software-development lifecycle
Evaluate AI-assisted development without blindly trusting productivity claims or generated code
Build engineering teams that support experimentation, learning, psychological safety, and accountability
Identify bottlenecks and improve the entire software-delivery system
Create practical 30-, 60-, and 90-day engineering improvement plans
The book also includes practical diagrams, decision frameworks, case-study scenarios, checklists, review questions, engineering metrics guidance, Architecture Decision Record templates, experiment-planning tools, incident-review resources, and an Evidence-Driven Engineering Toolkit designed for real-world application.
Every major practice is examined through four essential questions:
What does it mean?
Why does it matter?
How should it be applied?
How can you tell whether it is actually working?
Whether you are improving an established engineering organisation, modernising a legacy system, building a growing software product, leading a technical team, or preparing for professional software-development work, this book provides a structured framework for turning engineering decisions into measurable learning.
Stop copying practices simply because successful companies use them.
Start building an engineering system that can prove what works in your context.
The Evidence-Driven Software Engineer is a practical roadmap for creating software systems-and engineering teams-that can deliver quality, speed, reliability, and continuous improvement with greater confidence.
Rather than prescribing one best methodology, this book teaches you how to evaluate engineering practices in your own environment and determine what actually works.
Inside, you will learn how to:
Make better technical and architectural decisions using evidence instead of assumptions
Measure delivery performance without falling into vanity metrics or developer surveillance
Improve software quality, maintainability, reliability, security, and changeability
Design testing strategies that provide faster and more useful feedback
Build effective continuous integration and continuous delivery systems
Reduce deployment risk through progressive delivery and reliable recovery practices
Use observability, SLOs, error budgets, and incident evidence to strengthen production reliability
Integrate security throughout the software-development lifecycle
Evaluate AI-assisted development without blindly trusting productivity claims or generated code
Build engineering teams that support experimentation, learning, psychological safety, and accountability
Identify bottlenecks and improve the entire software-delivery system
Create practical 30-, 60-, and 90-day engineering improvement plans
The book also includes practical diagrams, decision frameworks, case-study scenarios, checklists, review questions, engineering metrics guidance, Architecture Decision Record templates, experiment-planning tools, incident-review resources, and an Evidence-Driven Engineering Toolkit designed for real-world application.
Every major practice is examined through four essential questions:
What does it mean?
Why does it matter?
How should it be applied?
How can you tell whether it is actually working?
Whether you are improving an established engineering organisation, modernising a legacy system, building a growing software product, leading a technical team, or preparing for professional software-development work, this book provides a structured framework for turning engineering decisions into measurable learning.
Stop copying practices simply because successful companies use them.
Start building an engineering system that can prove what works in your context.
The Evidence-Driven Software Engineer is a practical roadmap for creating software systems-and engineering teams-that can deliver quality, speed, reliability, and continuous improvement with greater confidence.
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