From the Book:
“Clean code that works” is Ron Jeffries’ pithy phrase. The goal is clean code that works, and for a whole bunch of reasons:
Clean code that works is a predictable way to develop. You know when you are finished, without having to worry about a long bug trail.Clean code that works gives you a chance to learn all the lessons that the code has to teach you. If you only ever slap together the first thing you think of, you never have time to think of a second, better, thing. Clean code that works improves the lives of users of our software.Clean code that works lets your teammates count on you, and you on them.Writing clean code that works feels good.But how do you get to clean code that works? Many forces drive you away from clean code, and even code that works. Without taking too much counsel of our fears, here’s what we do—drive development with automated tests, a style of development called “Test-Driven Development” (TDD for short). 
In Test-Driven Development, you:
Write new code only if you first have a failing automated test.Eliminate duplication.

Two simple rules, but they generate complex individual and group behavior. Some of the technical implications are:You must design organically, with running code providing feedback between decisionsYou must write your own tests, since you can’t wait twenty times a day for someone else to write a testYour development environment must provide rapid response to small changesYour designs must consist of many highly cohesive, loosely coupled components, just to make testing easy

The two rules imply an order to the tasks ofprogramming:
1. Red—write a little test that doesn’t work, perhaps doesn’t even compile at first
2. Green—make the test work quickly, committing whatever sins necessary in the process
3. Refactor—eliminate all the duplication created in just getting the test to work


Red/green/refactor. The TDD’s mantra.

Assuming for the moment that such a style is possible, it might be possible to dramatically reduce the defect density of code and make the subject of work crystal clear to all involved. If so, writing only code demanded by failing tests also has social implications:
If the defect density can be reduced enough, QA can shift from reactive to pro-active workIf the number of nasty surprises can be reduced enough, project managers can estimate accurately enough to involve real customers in daily developmentIf the topics of technical conversations can be made clear enough, programmers can work in minute-by-minute collaboration instead of daily or weekly collaborationAgain, if the defect density can be reduced enough, we can have shippable software with new functionality every day, leading to new business relationships with customers


So, the concept is simple, but what’s my motivation? Why would a programmer take on the additional work of writing automated tests? Why would a programmer work in tiny little steps when their mind is capable of great soaring swoops of design? Courage.
Courage
Test-driven development is a way of managing fear during programming. I don’t mean fear in a bad way, pow widdle prwogwammew needs a pacifiew, but fear in the legitimate, this-is-a-hard-problem-and-I-can’t-see-the-end-from-the-beginning sense. If pain is nature’s way of saying “Stop!”, fear is nature’s way of saying “Be careful.” Being careful is good, but fear has a host of other effects:
Makes you tentativeMakes you want to communicate lessMakes you shy from feedbackMakes you grumpy

None of these effects are helpful when programming, especially when programming something hard. So, how can you face a difficult situation and:
Instead of being tentative, begin learning concretely as quickly as possible.Instead of clamming up, communicate more clearly.Instead of avoiding feedback, search out helpful, concrete feedback.(You’ll have to work on grumpiness on your own.) 

Imagine programming as turning a crank to pull a bucket of water from a well. When the bucket is small, a free-spinning crank is fine. When the bucket is big and full of water, you’re going to get tired before the bucket is all the way up. You need a ratchet mechanism to enable you to rest between bouts of cranking. The heavier the bucket, the closer the teeth need to be on the ratchet.

The tests in test-driven development are the teeth of the ratchet. Once you get one test working, you know it is working, now and forever. You are one step closer to having everything working than you were when the test was broken. Now get the next one working, and the next, and the next. By analogy, the tougher the programming problem, the less ground should be covered by each test.

Readers of Extreme Programming Explained will notice a difference in tone between XP and TDD. TDD isn’t an absolute like Extreme Programming. XP says, “Here are things you must be able to do to be prepared to evolve further.” TDD is a little fuzzier. TDD is an awareness of the gap between decision and feedback during programming, and techniques to control that gap. “What if I do a paper design for a week, then test-drive the code? Is that TDD?” Sure, it’s TDD. You were aware of the gap between decision and feedback and you controlled the gap deliberately.

That said, most people who learn TDD find their programming practice changed for good. “Test Infected” is the phrase Erich Gamma coined to describe this shift. You might find yourself writing more tests earlier, and working in smaller steps than you ever dreamed would be sensible. On the other hand, some programmers learn TDD and go back to their earlier practices, reserving TDD for special occasions when ordinary programming isn’t making progress.

There are certainly programming tasks that can’t be driven solely by tests (or at least, not yet). Security software and concurrency, for example, are two topics where TDD is not sufficient to mechanically demonstrate that the goals of the software have been met. Security relies on essentially defect-free code, true, but also on human judgement about the methods used to secure the software. Subtle concurrency problems can’t be reliably duplicated by running the code.

Once you are finished reading this book, you should be ready to:
Start simplyWrite automated testsRefactor to add design decisions one at a time

This book is organized into three sections.
An example of writing typical model code using TDD. The example is one I got from Ward Cunningham years ago, and have used many times since, multi-currency arithmetic. In it you will learn to write tests before code and grow a design organically.An example of testing more complicated logic, including reflection and exceptions, by developing a framework for automated testing. This example also serves to introduce you to the xUnit architecture that is at the heart of many programmer-oriented testing tools. In the second example you will learn to work in even smaller steps than in the first example, including the kind of self-referential hooha beloved of computer scientists.Patterns for TDD. Included are patterns for the deciding what tests to write, how to write tests using xUnit, and a greatest hits selection of the design patterns and refactorings used in the examples.

I wrote the examples imagining a pair programming session. If you like looking at the map before wandering around, you may want to go straight to the patterns in Section 3 and use the examples as illustrations. If you prefer just wandering around and then looking at the map to see where you’ve been, try reading the examples through and refering to the patterns when you want more detail about a technique, then using the patterns as a reference.

Several reviewers have commented they got the most out of the examples when they started up a programming environment and entered the code and ran the tests as they read.

A note about the examples. Both examples, multi-currency calculation and a testing framework, appear simple. There are (and I have seen) complicated, ugly, messy ways of solving the same problems. I could have chosen one of those complicated, ugly, messy solutions to give the book an air of “reality.” However, my goal, and I hope your goal, is to write clean code that works. Before teeing off on the examples as being too simple, spend 15 seconds imagining a programming world in which all code was this clear and direct, where there were no complicated solutions, only apparently complicated problems begging for careful thought. TDD is a practice that can help you lead yourself to exactly that careful thought.

Test Driven Development: By Example

Traditional engineering instruction is deductive, beginning with theories and progressing to the applications of those theories Alternative teaching approaches are more inductive Topics are introduced by presenting specific observations, case studies or problems, and theories are taught or the students are helped to discover them only after the need to know them has been established This study reviews several of the most commonly used inductive teaching methods, including inquiry learning, problem-based learning, project-based learning, case-based teaching, discovery learning, and just-in-time teaching The paper defines each method, highlights commonalities and specific differences, and reviews research on the effectiveness of the methods While the strength of the evidence varies from one method to another, inductive methods are consistently found to be at least equal to, and in general more effective than, traditional deductive methods for achieving a broad range of learning outcomes

Inductive Teaching and Learning Methods: Definitions, Comparisons, and Research Bases

A decade of agile methodologies

Software engineering comprehends several disciplines devoted to prevent and remedy malfunctions and to warrant adequate behaviour. Testing, the subject of this paper, is a widespread validation approach in industry, but it is still largely ad hoc, expensive, and unpredictably effective. Indeed, software testing is a broad term encompassing a variety of activities along the development cycle and beyond, aimed at different goals. Hence, software testing research faces a collection of challenges. A consistent roadmap of the most relevant challenges to be addressed is here proposed. In it, the starting point is constituted by some important past achievements, while the destination consists of four identified goals to which research ultimately tends, but which remain as unreachable as dreams. The routes from the achievements to the dreams are paved by the outstanding research challenges, which are discussed in the paper along with interesting ongoing work.

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Software Testing Research: Achievements, Challenges, Dreams

The challenge of problem-based learning

Test-driven development creates software in very short iterations with minimal upfront design. This strategy requires writing automated tests prior to developing functional code in small, rapid iterations. Although developers have been applying TDD in various forms for several decades, this software development strategy has continued to gain increased attention as one of the core extreme programming practices.

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Test-driven development concepts, taxonomy, and future direction

Support for test-driven development [TDD] is growing in many development contexts beyond its common association with extreme programming. By focusing on how TDD influences design characteristics, we hope to raise awareness of TDD as a design approach and assist others in decisions on whether and how to adopt TDD. Our results indicate that test-first programmers are more likely to write software in more and smaller units that are less complex and more highly tested. We weren't able to confirm claims that TDD improves cohesion while lowering coupling, but we anticipate ways to clarify the questions these design characteristics raised. In particular, we're working to eliminate the confounding factor of accessor usage in the cohesion metrics.

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Does Test-Driven Development Really Improve Software Design Quality?

Test-driven learning (TDL) is an approach to teaching computer programming that involves introducing and exploring new concepts through automated unit tests. TDL offers the potential of teaching testing for free, of improving programmer comprehension and ability, and of improving software quality both in terms of design quality and reduced defect density.This paper introduces test-driven learning as a pedagogical tool. It will provide examples of how TDL can be incorporated at multiple levels in computer science and software engineering curriculum for beginning through professional programmers. In addition, the relationships between TDL and test-driven development will be explored.Initial evidence indicates that TDL can improve student comprehension of new concepts while improving their testing skills with no additional instruction time. In addition, by learning to construct programs in a test-driven manner, students are expected to be more likely to develop their own code with a test-driven approach, likely resulting in improved software designs and quality.

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Test-driven learning: intrinsic integration of testing into the CS/SE curriculum

Test-driven development (TDD) is an agile software development strategy that addresses both design and testing. This paper describes a controlled experiment that examines the effects of TDD on internal software design quality. The experiment was conducted with undergraduate students in a software engineering course. Students in three groups completed semester-long programming projects using either an iterative Test-First (TDD), iterative Test-Last, or linear Test-Last approach. Results from this study indicate that TDD can be an effective software design approach improving both code-centric aspects such as object decomposition, test coverage, and external quality, and developer-centric aspects including productivity and confidence. In addition, iterative development approaches that include automated testing demonstrated benefits over a more traditional linear approach with manual tests. This study demonstrates the viability of teaching TDD with minimal effort in the context of a relatively traditional development approach. Potential dangers with TDD are identified regarding programmer motivation and discipline. Pedagogical implications and instructional techniques which may foster TDD adoption will also be referenced.

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On the Influence of Test-Driven Development on Software Design

Coercing new programmers to adopt disciplined development practices such as thorough unit testing is a challenging endeavor. Test-driven development (TDD) has been proposed as a solution to improve both software design and testing. Test-driven learning (TDL) has been proposed as a pedagogical approach for teaching TDD without imposing significant additional instruction time.This research evaluates the effects of students using a test-first (TDD) versus test-last approach in early programming courses, and considers the use of TDL on a limited basis in CS1 and CS2. Software testing, programmer productivity, programmer performance, and programmer opinions are compared between test-first and test-last programming groups. Results from this research indicate that a test-first approach can increase student testing and programmer performance, but that early programmers are very reluctant to adopt a test-first approach, even after having positive experiences using TDD. Further, this research demonstrates that TDL can be applied in CS1/2, but suggests that a more pervasive implementation of TDL may be necessary to motivate and establish disciplined testing practice among early programmers.

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David S. Janzen

Papers

Test-driven development concepts, taxonomy, and future direction

Does Test-Driven Development Really Improve Software Design Quality?

Test-driven learning: intrinsic integration of testing into the CS/SE curriculum

On the Influence of Test-Driven Development on Software Design

Test-driven learning in early programming courses