Refactoring is a disciplined technique for restructuring an existing body of code, altering its internal structure without changing its external behavior. Its heart is a series of small behavior preserving transformations. Each transformation (called a “refactoring”) does little, but a sequence of these transformations can produce a significant restructuring. Since each refactoring is small, it's less likely to go wrong. The system is kept fully working after each refactoring, reducing the chances that a system can get seriously broken during the restructuring.

A common debate in software development projects is between spending time on improving the quality of the software versus concentrating on releasing more valuable features. Usually the pressure to deliver functionality dominates the discussion, leading many developers to complain that they don't have time to work on architecture and code quality. This debate is based on the assumption that increasing quality also increases costs, which is our common experience. But the counter-intuitive reality is that internal software quality removes the cruft that slows down developing new features, thus decreasing the cost of enhancing the software.

Refactoring has grown into a well-known technique, and most software development teams at least claim to be doing refactoring regularly. Many teams, however, don't appreciate the different workflows that refactoring can be used in, and thus miss opportunities to effectively incorporate refactoring into their development activities. In this deck I explore various different workflows. I hope it will encourage teams to integrate refactoring more deeply into their work, resulting in a better designed code-bases that will make it quicker and easier to add new features.

Modern web development has many challenges, and of those security is both very important and often under-emphasized. While such techniques as threat analysis are increasingly recognized as essential to any serious development, there are also some basic practices which every developer can and should be doing as a matter of course.

Observability in our software systems has always been valuable and has become even more so in this era of cloud and microservices. However, the observability we add to our systems tends to be rather low level and technical in nature, and too often it seems to require littering our codebase with crufty, verbose calls to various logging, instrumentation, and analytics frameworks. This article describes a pattern that cleans up this mess and allows us to add business-relevant observability in a clean, testable way.

When I write code that deals with external services, I find it valuable to separate that access code into separate objects. Here I show how I would refactor some congealed code into a common pattern of this separation.

Often designs techniques are used to make a system more flexible, but end up being harder to work with. One of the reasons is that explicitness is a property that often gets forgotten in design.

You can use metadata based approaches to remove the pain from tedious data oriented tasks.

Guidelines on when to make a new user defined type (or class) for values.

Kent Beck came up with his four rules of simple design while he was developing ExtremeProgramming in the late 1990's. I express them like this.

A code smell is a surface indication that usually corresponds to a deeper problem in the system. The term was first coined by Kent Beck while helping me with my Refactoring book.

The term 'command query separation' was coined by Bertrand Meyer in his book “Object Oriented Software Construction“ - a book that is one of the most influential OO books during the early days of OO. (The first edition is the one that had the influence, the second edition is good but you'll need several months in a gym before you can lift it.)

One of the most powerful tools in writing maintainable code is break large methods into well-named smaller methods - a technique Kent Beck refers to as the Composed Method pattern.

Whenever two or three values are gathered together - turn them into a $%#$%^ object.

-- Me (it was funnier with the voices)

This is one of my favorite CodeSmells from the refactoring book. You spot it when you constantly see the same few data items passed around together. start and end are a good example of a data clump wanting to be a range. Often data clumps are primitive values that nobody thinks to turn into an object.

Is it worth the effort to design software well?

(Here's an addition to your dictionary.)

Detestable (adjective): software that isn't testable.

During my career, I've heard many arguments about how long a function should be. This is a proxy for the more important question - when should we enclose code in its own function? Some of these guidelines were based on length, such as functions should be no larger than fit on a screen . Some were based on reuse - any code used more than once should be put in its own function, but code only used once should be left inline. The argument that makes most sense to me, however, is the separation between intention and implementation. If you have to spend effort into looking at a fragment of code to figure out what it's doing, then you should extract it into a function and name the function after that “what”. That way when you read it again, the purpose of the function leaps right out at you, and most of the time you won't need to care about how the function fulfills its purpose - which is the body of the function.

In my view the Gang of Four is the best book ever written on object-oriented design - possibly of any style of design. This book has been enormously influential on the software industry - just look at the Java and .NET libraries which are crawling with GOF patterns.

Self-Testing Code is the name I used in Refactoring to refer to the practice of writing comprehensive automated tests in conjunction with the functional software. When done well this allows you to invoke a single command that executes the tests - and you are confident that these tests will illuminate any bugs hiding in your code.

Software systems are prone to the build up of cruft - deficiencies in internal quality that make it harder than it would ideally be to modify and extend the system further. Technical Debt is a metaphor, coined by Ward Cunningham, that frames how to think about dealing with this cruft, thinking of it like a financial debt. The extra effort that it takes to add new features is the interest paid on the debt.

Test-Driven Development (TDD) is a technique for building software that guides software development by writing tests. It was developed by Kent Beck in the late 1990's as part of Extreme Programming. In essence we follow three simple steps repeatedly:

Yagni originally is an acronym that stands for “You Aren't Gonna Need It”. It is a mantra from ExtremeProgramming that's often used generally in agile software teams. It's a statement that some capability we presume our software needs in the future should not be built now because “you aren't gonna need it”.