Typing != Complexity

Developers of all experience levels commonly share a false belief: more typing means more complexity. The most powerful idioms and tools often require a few extra keystrokes, but dramatically reduce complexity.

The final keyword in Java is a bit of extra typing. The final keyword can be applied to variables, method parameters, instance members, static members, methods, and classes. By making these final, their values will not depend on their context. They will be known constants through their lifetime. Their constancy removes a large cognitive load. The developer no longer needs to worry if the value was not set or if it was set multiple times. Many developers forgo this benefits to avoid typing the extra keyword, to their own detriment. Later, they spend too much time chasing down defects caused by mutable state.

Developers will often shun creating small types and interfaces because of the extra typing involved. Interfaces can abstract away many different implementations behind a simpler facade. Adding new implementations would only require creating a new class. Instead, many developers will create long-winded conditional chains of all the behaviors. These chains are repeated in many places, opening the possibility for defects through inconsistencies. Conditionals are harder to understand and change than focused classes. Small types allow us to use the compiler to find defects and document expectations in the code. A primitive integer can represent a distance, a duration, or any number of other numeric values. A wrong value in the wrong place can be disastrous. A Duration instance cannot be wrongly used in place of a Distance though. This guarantee is enforced by the compiler, and will not be overlooked or side-stepped.

Programming languages, like natural languages, are built for people. And like natural languages, they cannot always be maximally terse and maximally expressive. For people, expressiveness is the more valuable attribute. With programming languages, the expressiveness carries added benefits. We can create stronger assurances against defects, and fail earlier. All for the price of a little extra typing.

Comments

Post a Comment

Popular posts from this blog

The Timeline of Errors

Image
As software developers, we see errors every day. They manifest as exceptions or segfaults or error codes, telling us that our code has gotten into a state we didn't expect. Their appearance often portends bugs. Though we groan at an unexpected stack trace, we should see an error as a form of automated feedback . Feedback can be fast or slow. We can put the discovery of errors onto a timeline. Errors appear at many points over the lifetime of the code, starting at the moment it is compiled. The further to the right that an error appears, the longer it takes for the feedback to appear. Compile time Compile time is the earliest we can receive feedback about an error. The compiler automatically does a number of checks to make sure the code makes some semblance of sense. The most powerful tool for compile-time feedback is the type-checker. The type-checker makes sure that only values of the expected type are passed around to the places that expect them. This guards ...
Read more

Assuming the Bugs

Writing code is all about making assumptions. Sometimes those assumptions are explicit, but more often we make those assumptions implicitly. We make assumptions about what kinds of parameters we will receive. We make assumptions about what kinds of values methods and functions will return. We make assumptions about the global state. The correctness of our code relies on the correctness of these assumptions. Bad assumptions can wreck our applicatons. We assumed that method never returns null, but turns out it does. Now we have an unexpected NullPointerException crashing through our stack. We assume that we will always average at least one element. Turns out someone wants to average zero elements. Boom, division by zero, ArithmeticException . We make so many assumptions through our codebases, at least a few are going to be wrong. Really, there are many, many assumptions that are wrong. These are bugs. These bad assumptions are all of our bugs. Usually, our assumptions are i...
Read more

Assuming Debugging

Bugs are bad assumptions . Debugging is the process of testing our assumptions until we discover the invalid one(s). Once found, we can then correct those bad assumptions. The following code generates blog post author statistics for a popular blog site. The statistics show which days of the week authors are making posts. Most of the authors post every day, and extra on Fridays and Saturdays to capture the weekend audience. It has at least one bug. @GET @Path("/authors/{email}/weekly-stats") public UserWeeklyStats calculateWeeklyStats(@PathParam("email") final String email) { final User user = this.userService.byEmail(email); final Map<LocalDate, List<Post>> postsByDate = this.postService.thisWeekGroupedByDateFor(user.id()); if (postsByDate.isEmpty()) { return null; } final Map<DayOfWeek, List<Post>> postsByDayOfWeek = new HashMap<>(); postsByDate.forEach((date, post) -> post...
Read more