I recently read an article that discussed how to increase code sizes. There are many different ways of doing this, and much of it depends on the programming language and development environment you are using. Here is a list of things to avoid when growing your code base:
A. Not using functions.
B. Not commenting your code.
C. Not refactoring techniques.
D. Using too many lines of code for a single function or block of code.
In order to explain the pitfalls to avoid in the above examples, let’s take a look at each point separately and see what we can learn from them.
So you’ve decided to develop code. Congratulations! But how do you actually increase your code’s size?
There are three main pitfalls to avoid when creating new code:
1. Modularization: Do not modularize your code into functions and classes, or wrap it in a namespace. A single monolithic file is the way to go.
2. Testing: Do not create test cases for any of your code. Testing your code will only introduce unnecessary complexity into the development process.
3. Documentation: This is a no-brainer: comment, comment, and then comment some more! Writing comments is far easier than writing actual code, so make sure every line of code is accompanied by a comment of at least 10 lines in length.
If you follow these three simple rules, you should have no problem increasing the size of your code, and ensuring it remains large for many years to come.
One of the most common questions we hear from developers all over the world is: “How can I keep my code maintainable?”. The answer is usually that you need a good understanding of what you’re doing and how to do it right. As with most things in life, you can’t just get better at something by reading about it or watching videos on YouTube.
But there are some techniques you can use to make your code easier to understand, and we will explain one of them here: Code Size.
A lot of people have trouble understanding what’s going on in their code because they don’t know how much code they’re writing. If you don’t know how much code you’re writing, then you don’t really know what’s going on in your code. But if you do know how much code you’re writing, then you will be able to understand the problems more easily.
And one way to get a better understanding of how much code you’re writing is by looking at the size of your functions and methods. This will give you an idea of how many lines of code there are between two points in your program – and if there are too many lines of code between two points, then that is an indication that something is wrong. In
We live in an age where computers are everywhere. And with the increasing prevalence of computers, more and more people want to create software for them. However, it is not as easy as it looks. There are many factors to creating great software, and one of the most important factors is code size. A large code-base allows a program to do more things, and thus is generally a good thing.
So how can we increase program size? Here are a few tips:
1. Don’t follow best practices.
2. Repeating yourself over and over again is always a good idea.
3. Use lots of nesting in your loops (but don’t use functions – that would be too clean).
4. Make sure to add plenty of comments to your code (but don’t comment on what the code actually does – that would be too informative).
5. Make sure to continually change variable names throughout the program (this keeps the code fresh and interesting).
Programming languages are not at all dead. It’s a very exciting time to be working on programming languages and compilers. First, there is still plenty of low-hanging fruit that we can exploit. For example, a lot can still be done within the imperative paradigm to make code smaller and faster.
Second, the functional paradigm is making a comeback; it never went away entirely but it had been dormant for a while. The functional language Scheme came out in 1975, and has gone through many incarnations (Racket, ClojureScript, Elixir), each time becoming more popular and more useful. A functional language is one where you don’t have variables; you just pass around functions and data structures. In such a language, your code becomes much simpler because you don’t have to deal with the state of your variables which are often the source of bugs in an imperative language like C++ or Java.
Third, new paradigms are coming into view that promise even further reductions in code size and increases in speed: logic programming (Prolog), constraint programming (MiniZinc), and quantum computing (Quipper). This promises not only to make our lives easier as programmers but also to give us much greater insight into problems that we couldn
Why is it that some software projects are delayed and over budget while others seem to sail through without trouble?
Two of the most common reasons for project failure are not technical. Instead, they involve poor project management or a toxic corporate culture. Bad estimates and poor time management result in an inability to predict whether a project will be done on time and on budget. A lack of communication can lead to missed requirements, misunderstandings, and more work than necessary. If a company’s culture doesn’t value cooperation, teamwork, and collaboration, then it makes it that much harder for everyone to work together towards a common goal.
Another reason for project failure is the difficulty of understanding what you’re working on at any given moment. Often it has to do with how familiar you are with the codebase and how well it is documented. In an ideal world, code would be self-documenting and easy to understand. But unfortunately there are many ways to make code difficult to read, understand, and maintain.
In this post I’ll cover some of these pitfalls by looking at specific examples in Python. The examples I’ll use are contrived and don’t represent good coding practices, but they illustrate some of the points I want to make.