About

My name is Christopher Bojarski. I'm a web developer, programmer and blogger. Fan of all things technology related. Avid reader and traveler. Married and living in Philadelphia. Connect with me at cbojar.net.

Popular posts from this blog

The Timeline of Errors

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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 ...
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The Cone of Code Uncertainty

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As hurricanes approach the shores of North America, we are barraged with maps of possible tracks those storms can take. Those tracks start pretty close together, but diverge widely the further into the future they predict. Simplified, those storm tracks form a cone of uncertainty . A storm in the Atlantic could slide into the Gulf of Mexico and land anywhere from the Texas-Mexico border to Panama City Beach, FL. It all depends on a myriad of tiny factors to turn the storm this way or that. As time progresses, the storm moves along, and the cone of uncertainty shrinks. Its eventual location becomes clearer to predict, and we can more effectively target resources. Cone of Uncertainty for Hurricane Ike, source Much like hurricanes, running code lives in a cone of uncertainty. A function or method call is a mysterious black box until we have a result. If something goes wrong, we must delve into this cone of code uncertainty to find the problem. We use log statements and de...
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Assuming Maintainability

Bugs are bad assumptions. Making assumptions explicit leads to more direct, easier to maintain code. Bugs are bad assumptions. Therefore, to reduce bugs and make code more maintainable, we need to make our assumptions as explicit as we can. We make our assumptions explicit in five ways: comments, tests, conditionals, assertions, and encapsulation with the type system. Each of these ways gives us progressively more assurance that our explicit assumptions are enforced in the code base. They also give us progressively earlier feedback when our code fails to live up to our assumptions. Comments Comments are the simplest way to express an assumption in the code. We write out, in plain language, what our assumption is. We can then read those assumptions quickly when need to use that piece of code. For example, we can state assumptions in method-level comments that describe our parameters. /** * Divide the dividend by the divisor. * @param dividend the number to d...
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