London vs Chicago

Adopting an integrated approach to TDD.

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Separation of Concerns

Building modularity.

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Managing
Technical Debt

Don't let tech debt manage you.

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Canary Release

Screening your software to ensure it's ready for prime time.

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Testing in Production

What if I told you that you can test your software in production?  Well, you can with the right testing strategy and correct deployment methods.  A DevOps approach to delivery will enable your team to conduct limited manual testing of new functionality, extensions, and patches in a production environment before releasing to your customers.  Although it should never replace the unit, service, and system-level testing in your lower environments, it can help to ensure that your software will run as expected in production.

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Always Releasable

Promote continuous delivery by always keeping your software in a releasable state.  Gain high confidence that your software works by integrating changes continuously, while leveraging a deployment pipeline to ensure that your software build is always releasable.  Do not isolate new development within feature branches.  A better way is to integrate those changes earlier by applying them directly on the trunk with a mature suite of tests to protect the build.  Employ DevOps patterns to always keep your software releasable in the midst of constant change.

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Test Organization

Organize your xUnit test packages, classes, and methods in a way that makes it easy to find, understand, and maintain your tests.  While this is relatively easy with a small number of tests, effectively managing a lot of them takes some planning.  Although there is no single best practice, there are organizational strategies that will go a long way to help keep your tests and test fixtures well organized.  These strategies will also help to promote test code reuse, simplify running test subsets, manage the lifetime of test fixtures, and optimize test execution by managing resources that are expensive to allocate.

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Separation of Concerns

Build flexible, highly adaptive software systems by separating all but those parts of a system that are closely related and require direct interaction.  All other parts of the system should be designed and built independently, while having little to no knowledge of other parts of the system or the system as a whole.  This can be achieved by encapsulating cohesive information and logic into isolated layers, made of reusable components, containing cohesively bound classes which serve single actors, that are composed of small, single-purpose functions.

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Isolate the SUT

Promote testability of your software by isolating the System Under Test (SUT) to ensure that each test verifies only the intended condition.  This will foster Defect Localization and support Repeatable Tests, while minimizing overlap and dependencies between tests.  This will also impede attempts to verify complex states or multiple scenarios due to lack of control of all inputs to the SUT.  Clarify the control points and observation points of the SUT to facilitate effective interactions with the SUT.

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Acceptance Testing

Build automated tests that verify that the acceptance criteria of a user story have been met and demonstrate that the system delivers the value expected by the customer.  These tests are best implemented using the domain language without reference to the application’s user interface (UI).  This will greatly simplify the test fixtures, access to test results, and obscure GUI components.  This, of course, requires a well-factored architecture that decouples all business rules and application logic from the UI.

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Immobility

Avoid this design smell by building software from which it is easy to extract and reuse internal components in new environments.  This smell is often caused by dependencies that are tightly integrated with other parts of the system.  Promote mobility by decoupling components from low-level implementations, such as data persistence, logging, user interfaces, etc.  For example, business rules should be encapsulated within components to enable reuse across multiple systems.

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Rigidity

Avoid this design smell by building software that is flexible and easy to change.  Rigidity is often observed when a small change forces a complete rebuild and redeploy.  Small changes should be able to be built, tested, and deployed very quickly and independently of each other.  Long build times are a symptom of high coupling.  To promote flexibility, manage the dependencies between modules to ensure when one module changes, the others remain unaffected.

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Fragility

Avoid this design smell by building software that is highly modular, highly cohesive, and loosely coupled.  A change to one part of your system should never break another part that is completely unrelated.  High level policies (i.e. business rules) should never be impacted by changes to low level implementations (i.e. data persistence).  Even related functionality should be decoupled enough to extend functionality without affecting related components.  There are many engineering patterns and practices that facilitate flexibility, extensibility, adaptability, along with many other qualities that inhibit fragility.

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Two Hats

As software is developed by making behavioral and structural changes, do not attempt to do both at the same time.  Wear one hat to add new capabilities (including tests) without changing existing code, then wear the other hat to restructure the code without changing behavior.  Build software by swapping hats frequently to develop and test very small capabilities, then refactor to improve the design and the overall quality of the code.

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Software Evolution

Build your initial features quickly, then evolve your software based on customer feedback.  This demands having a good suite of tests to prevent cruft and promote refactoring without the fear of breaking those features.  This also requires being able to recognize design smells.  These smells will permeate your software due to bad decisions caused by carelessness and false expedience.  Manage the dependencies within your software to ensure a loosely coupled architecture and...

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Slow Tests

Build your software and your tests in ways that minimize test execution time.  Common causes for long running tests include over-engineered test fixtures, asynchronous code, components with high latency, Test Overlap, and too many tests due to a tightly coupled architecture.  This causes bottlenecks in Continuous Integration, inhibits rapid feedback facilitated by automated testing, and constrains frequent code merges that are required for Trunk-Based Development.

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I’ll Fix It Later

Do not fool yourself into thinking you will ever go back and actually rewrite your code the right way.  Any experienced developer will tell you it rarely happens (even with the best of intentions).  And every time you save that cruft for later, you’re introducing Technical Debt, which will do nothing but slow you down.  To go fast, you must go well.  Trading quality for velocity will catch up to you very quickly and slow you down much more than if you had written good code to start.  This does not mean you should...

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Trunk-Based Development

Embrace continuous delivery by frequently integrating small batches of work directly into the source control trunk (at least once daily).  Short-lived branches can be used to implement pull requests or to isolate release candidates, but should never persist longer than a day.  Utilize Feature Toggles to turn off features that are not yet ready for release.  Pull the Andon Cord and fix regression errors immediately to keep the trunk in a healthy and deployable state.

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Repeatable Tests

Write tests such that each produces the same result from a given initial state without any manual intervention between runs.  Unit tests must verify Single Test Conditions by executing a single code path through the System Under Test (SUT) and executing the same, exact code path each time it runs.  Verifying one condition for each test helps to minimize Test Overlap and ensures we have fewer tests to maintain if we later modify the SUT.  Isolating the SUT ensures that we only have to focus on code paths through a single object. 

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The Technical Discipline of Being Agile™

Agile was created by 17 technical leaders in the software industry who crafted a lightweight development process that was intended to heal the divide between business and developers.  They also established technical norms that would mitigate common issues such as excessive cruft, tightly coupled architectures, rigid code, immature test suites, technical debt, along with other anti-patterns that slowed delivery of high quality software.  This course examines the characteristics of good and bad software and explores technical practices that resolve the issues and enable teams to deliver great software fast.

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Managing Technical Debt

To maintain business, market, and technological advantages, you must effectively manage technical debt incurred within all artifacts that define, implement, and validate your software.  This course examines what technical debt is, explains why defining a quality model is essential to understanding technical debt and teaches how to effectively manage risks associated with impacts to that model.  Discussions will encompass tracking quality issues as defects vs. technical debt, dealing with code smells, and methods for minimizing technical debt.

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Principles & Practices of Test-Driven Development

This course teaches the principles and practices of Test-Driven Development (TDD) and demonstrates how proper software design evolves through application of the eXtreme Programming principle of Test First.  Unit testing principles are introduced, along with a thorough discussion on the benefits of TDD.  An application is developed (from start to finish) during this course to explain step-by-step and demonstrate first-hand how a high quality, testable design evolves by applying the three laws of Test-Driven Development.

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computer Code Kata

Prime Transformation

A good TDD developer is one who can apply transformations well.  What are transformations?  They are the opposite of refactoring.  While refactoring is changing the structure of code without changing its behavior, transformations are changes to code that generalize behavior without changing its structure.  In this kata, you will create a function to calculate the prime factors of a given integer using TDD while applying transformations to pass the tests.

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Doug Klugh

Software Craftsman

Software Development and DevOps Leader, Microsoft developer, and Agile Coach.