This often leads them to produce code that is not readable. The following code snippet will perform what it is intended to do, although it contains elements written using terrible naming conventions and this affects the code's readability:. Code can be easily understood when written using the programming language's coding style and convention while avoiding the bad code pitfalls discussed earlier.
However, source code documentation is very valuable and its importance in software projects cannot be overemphasized. Brief and meaningful documentation of classes and methods can give developers a quick insight into their internal structures and operations.
Understanding a complex or poorly written class becomes a nightmare when there is no proper documentation in place. When the original programmer that wrote the code is no longer around to provide clarifications, valuable productive time can be lost trying to understand how the class or method is implemented.
Though many articles have been written and discussions have been initiated at various developers' conferences on different types of testing—test-driven development, behavior-driven development, and acceptance test-driven development — it is very concerning that there are developers that continuously develop and ship software applications that are not thoroughly tested or tested at all.
Shipping applications that are poorly tested can have catastrophic consequences and maintenance problems. Notable is NASA's Mars Climate Orbiter launched on December 11, that failed just as the orbiter approached Mars, due to a software error caused by an error in conversion where the orbiter's program code was calculating a metric in pounds instead of newtons. A simple unit testing of the particular module responsible for calculating the metrics could have detected the error and maybe prevented the failure.
Also, according to the State of Test-First Methodologies Report , a survey of the adoption of test-first methodologies of more than software organizations from 15 different countries, conducted by a testing services company named QASymphony , revealed that nearly half of the survey respondents had not implemented a test-first methodology in the applications they had developed.
Writing clean code requires a conscious effort of maintaining professionalism and following best industry standards throughout the stages of the software development process. Bad code should be avoided right from the onset of software project development, because the accumulation of bad debt through bad code can slow down software project completion and create future issues after the software has been deployed to production. To avoid bad code, you have to be lazy, as the general saying goes that lazy programmers are the best and smartest programmers because they hate repetitive tasks, such as having to go back to fix issues that could have been prevented.
Try to use programming styles and approaches that avoid writing bad code, to avoid having to rewrite your code in order to fix avoidable issues, bugs, or to pay technical debts. Loose coupling is the direct opposite of tight coupling. This is a good object-oriented programming practice of separation of concerns by allowing components to have little or no information of the internal workings and implementation of other components.
Communication is done through interfaces. This approach allows for an easy substitution of components without many changes to the entire code base. The sample code in the Tight coupling section can be refactored to allow loose coupling:. Bad code can be avoided through the use of a good development architecture and design strategy.
This will ensure that development teams and organizations have a high-level architecture, strategy, practices, guidelines, and governance plans that team members must follow to prevent cutting corners and avoiding bad code throughout the development process.
Through continuous learning and improvement, software development team members can develop thick skins towards writing bad code. The sample code snippet in the Bad or broken designs section can be refactored to be thread-safe and avoid thread-related issues, as shown in the following code:. Programming styles and coding formats that result in code smell should be avoided. By adequately paying attention to the details, bad code pointers discussed in the Code smell section should be avoided.
The replicated lines of code in the two methods of the source code mentioned in the Code smell section can be refactored to a third method.
This avoids replication of code and allows for easy modifications:. Development teams should have guidelines, principles, and coding conventions and standards developed jointly by the team members and should be constantly updated and refined.
These, when used effectively, will prevent code smell in the software code base and allow for the easy identification of potential bad code by team members. Using the guidelines in C coding conventions facilitates the mastery of writing clean, readable, easy to modify, and maintainable code. Use variable names that are descriptive and represent what they are used for, as shown in the following code:.
Also, having more than one statement or declaration on a line clogs readability. Comments should be on a new line and not at the end of the code.
You should always try to write self-documenting code. This can be achieved through good programming style. W rite code in such a manner that your classes, methods, and other objects are self-documenting. A new developer should be able to pick your code and not have to be stressed out before understanding what the code does and its internal structure.
Coding elements should be descriptive and meaningful to provide an insight to the reader. In situations where you have to document a method or class to provide further clarity, adopt the Keep It Simple Short KISS approach, briefly stating the reasons for a certain decision.
Check the following code snippet; nobody wants to have to read two pages of documentation for a class containing lines of code:.
Each time I enter a discussion with folks not practicing test-driven development, they mostly have one thing in common, which is that it consumes time and resources and it does not really give a return on investment. I usually reply to them by asking which is better, detecting bugs and potential bottlenecks and fixing them while the application is being developed or hotfixing bugs when the application is in production?
Test-driven development will save you a lot of problems and ensure you produce robust and issue-free applications. To avoid future problems resulting from issues when making modifications to a system in production as a result of changes in user requirements, as well as bugs which get exposed because of inherent bad code in a code base and accumulated technical debt, you need to have the mindset of developing with the future in mind and embracing changes.
Use flexible patterns and always employ good object-oriented development and design principles when writing code. The requirements of most software projects change over their life cycles. It is wrong to assume that a component or part might not change, so try and put a mechanism in place to allow the application to be graceful and accept future changes.
Test-driven development TDD is an iterative agile development technique that emphasizes test-first development, which implies that you write a test before you write production-ready code to make the test pass.
The TDD technique focuses on writing clean and quality code by ensuring that the code passes the earlier written tests by continuously refactoring the code. TDD, being a test-first development approach, places greater emphasis on building well-tested software applications. This allows developers to write code in relation to solving the tasks defined in the tests after a thorough thought process. It is a common practice in TDD that the development process begins with writing the tests code before the actual application code is written.
TDD introduces an entirely new development paradigm and shifts your mindset to begin thinking about testing your code right before you even start writing the code. This contrasts with the traditional development technique of deferring code testing to the later stage of the development cycle, an approach known as test last development TLD. TDD has been discussed at several conferences and hackathons.
Many technology advocates and bloggers have blogged about TDD, its principles, and its benefits. At the same time, there have been many talks and articles written against TDD. The honest truth is TDD rocks, it works, and it offers great benefits when practiced correctly and consistently. You might probably be wondering, like every developer new to TDD, why write a test first, since you trust your coding instinct to write clean code that always works and usually will test the entire code when you've done coding.
Your coding instinct may be right or it may not. There is no way to validate this assumption until the code is validated against a set of written test cases and passes; trust is good, but control is better. Test cases in TDD are prepared with the aid of user stories or use cases of the software application being developed. The code is then written and refactored iteratively until the tests pass.
For example, a method written to validate the length of a credit card might contain test cases to validate the correct length, incorrect length, and even when the null or empty credit card is passed as a parameter to the method. Many variants of TDD have been proposed ever since it was originally popularized. A variant is behavior-driven development BDD or acceptance test—driven development ATDD , which follows all the principles of TDD while the tests are based on expected user-specified behavior.
There is literally no written evidence as to when the practice of TDD was introduced into computer programming or by which company it was first used. Nevertheless, there is an excerpt from Digital Computer Programming , by D. TDD forces us into the habit of writing unit tests for production code - no excuses. Applying TDD requires a fundamental change in how we think about writing code.
So if you're planning to try it out on your next project or within an existing one be patient and approach it in baby steps. To get a feel for it, try and isolate a single class or component and apply the process of thinking through the design from a testing perspective. If you find yourself simultaneously changing the code and tests it's usually a sign of a misstep in your design - no big deal. Keep iterating and you'll get it.
Home Login. Beginning Test-Driven Development in. What is test-driven development? You repeat this cycle many times. Typically, the initial cycles are very quick but gradually slow down as more time is spent refactoring. Get notified on new posts Straight from me, no spam, no bullshit.
Frequent, helpful, email-only content. Recent Clean Architecture with X Build an Authenticated Gr User Authentication and I To find the point of failure, select the failing test, and then look at the details in the Test Detail Summary pane. Inspect the method under test to see what might be wrong. Alter the SquareRoot code as follows:. Fix the SquareRoot code by adding the following if statement at the beginning of the method:. A refactoring is a change that is intended to make the code perform better or easier to understand.
It is not intended to alter the behavior of the code, and therefore the tests are not changed. We recommend that you perform refactoring steps separately from steps that extend functionality. Keeping the tests unchanged gives you confidence that you have not accidentally introduced bugs while refactoring.
Change the line that calculates result in the SquareRoot method as follows:. Feedback will be sent to Microsoft: By pressing the submit button, your feedback will be used to improve Microsoft products and services. Privacy policy. It forces you to think about smaller chunks of functionality at a time rather than the application as a whole.
Then you can incrementally build on a passing test, rather than trying to tackle the bigger picture from the get-go, which will probably result in more bugs.
To be honest, there are more articles in which you can read even more deeply on TDD. Therefore, I avoided writing the whole theory of TDD here because it would take a very long time to read everything. So our requirements are pretty simple: we want to implement a Stack class, so the requirements are:. After we know what the requirements of the system are, we can start to define how we will solve this.
I use visual studio NET Framework. Open the solution explorer. Add a new class to the StackTests project and call it StackTest. Now the solution should look like this:. Before we can start writing the code we need to learn 3 important things: TestFixture, Test, and Assert. TestFixture is the attribute that marks a class that contains tests and, optionally, setup or teardown methods. The Test attribute is one way of marking a method inside a TestFixture class as a test.
The Assert class is a collection of helper classes to test various conditions within unit tests. If the condition being tested is not met, an exception is thrown. We will write a creation test, which will create a new object of our Stack, and it will check that the size of the Stack is 0 at the beginning.
At this point we will check that the last element is the exact one we expect to get and that the stack size decreased. As you can see, push and pop functions do not even exist, so when we run tests we get a failure in our test results.
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