{"id":434,"date":"2020-02-04T15:51:17","date_gmt":"2020-02-04T15:51:17","guid":{"rendered":"https:\/\/kalkus.dev\/?p=434"},"modified":"2023-08-24T23:31:38","modified_gmt":"2023-08-24T23:31:38","slug":"the-naming-problem-in-programming","status":"publish","type":"post","link":"https:\/\/kalkus.dev\/blog\/2020\/02\/04\/the-naming-problem-in-programming\/","title":{"rendered":"The naming problem in programming"},"content":{"rendered":"\n

Reading source code is more difficult than writing it.<\/strong> Inherently. Everybody who worked with a legacy system and needed to understand the authors\u2019 intent knows what I mean. Browsing through thousands of lines of function definitions, variables and figuring out what\u2019s the point is a daunting task.<\/p>\n\n\n\n

But why, actually?<\/p>\n\n\n\n

Is reading a recipe difficult?<\/strong><\/p>\n\n\n\n

Is it more difficult than writing it?<\/strong><\/p>\n\n\n\n

Is reading a hundred years old recipe more difficult than understanding thirty days old recipe?<\/strong><\/p>\n\n\n\n

I don\u2019t think so.<\/p>\n\n\n\n

Why then reading source code gets more difficult as the code matures? What can be the reason for software decay<\/a> and common hatred towards legacy systems?<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Let us think of the action of reading source code. What do we do when we try to understand the flow of the computer program?<\/p>\n\n\n\n

We are a bit like computers, but less effective. We go through the code and read the variables and functions. Because we are not as fast as machines we can\u2019t remember the value of each variable and we are unable to memorize the body of each function or subroutine. Our \u201cunderstanding\u201d is based on approximation. We read the name of the variable and try to guess its usage, its meaning. We read the name of a function and without reading its body we try to figure out what the function can do.<\/p>\n\n\n\n

It\u2019s exactly the same as in the real world. When we read about \u201ca carrot\u201d in the recipe we imagine a carrot. We can understand the concept of carrot without receiving a lengthy list of details about the carrot, such as its genetic code, mass, temperature, color and so on. <\/p>\n\n\n\n

But source code \u2013 even with the entire effort of object-oriented paradigm \u2013 is not like the real world.<\/p>\n\n\n\n

In the real world we have a huge, but a limited amount of words in our vocabularies. Natural language is processed by human brains in a completely different manner than source code by the compiler. For example \u201ca chair\u201d to a human being is not a particular chair but an idea of a chair.<\/strong> In most cases, we don\u2019t need detailed definitions to process natural language. On the contrary – in rare cases like the law we have big problems with the definitions.<\/p>\n\n\n\n

A very good example illustrating what would happen to the natural language if we process it as literally as computers process the source code is this video:<\/p>\n\n\n\n