How do you organize your algorithm sources?

1 Why organize your algorithm sources?

Organizing your algorithm sources can help you save time and effort, avoid duplication and errors, and enhance your learning and creativity. By having a clear and consistent system for storing, naming, and documenting your algorithm sources, you can quickly locate the algorithm you need for a specific task or project, compare different algorithms for the same problem, modify existing algorithms to suit your needs and preferences, share with others who use or develop algorithms as well as learn from the experts and discover new ideas and techniques.

2 How to choose your algorithm sources?

Before you start organizing your algorithm sources, you need to decide which ones are worth keeping and using. To help you make an informed decision, consider factors such as the relevance, quality, complexity, availability, and credibility of the algorithm. You can evaluate your algorithm sources by reading reviews, checking references, testing examples, or consulting experts. Doing so will help ensure that you are selecting the best algorithm for your problem or goal.

3 How to store your algorithm sources?

Once you have selected your algorithm sources, you need to store them in a way that is convenient, secure, and scalable. You can utilize physical media such as books, papers, notebooks, or flash drives; digital media like files, folders, databases, or cloud services; or a hybrid of both. Additionally, you can store your algorithm sources in various formats like plain text, markdown, LaTeX, Python, C++, Java, pseudocode (a simplified and standardized way of describing algorithms), flowcharts, graphs, or trees. Ultimately, the choice of storage media and format depends on your personal preference, budget, and availability; however you should strive for consistency, compatibility, and backup.

4 How to name your algorithm sources?

Naming your algorithm sources is a key step to organize them and make them easy to locate. You can use various naming conventions, such as descriptive keywords or phrases, the name of the author or publisher, acronyms or initials, and numbers or codes. Additionally, you can choose from hierarchical subfolders or prefixes, a single folder or level, or a combination of the two. Ultimately, the choice of naming convention and structure depends on your personal preference, clarity, and uniqueness. However, you should avoid ambiguous, misleading, or conflicting names.

5 How to document your algorithm sources?

Documenting your algorithm sources is a necessary step to organize them and make them easy to comprehend and utilize. You can employ various types of documentation, such as inline or block comments to explain the code or pseudocode of the algorithm, symbols or labels to highlight the key features or steps of the algorithm, tags or attributes to provide additional information about the algorithm, and separate files or documents to provide detailed instructions or examples on how to use the algorithm. The selection of documentation type depends on your personal preference, audience, and purpose; however, accuracy, completeness, and readability should be your objectives.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?