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How can you ensure that your code documentation and testing are scalable?

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Code documentation and testing are essential for any operations research project, but they can become challenging and time-consuming as the codebase grows and changes. How can you ensure that your code documentation and testing are scalable, meaning that they can adapt to the evolving needs and complexity of your project, without compromising on quality and efficiency? Here are some best practices to follow.

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1 Use a documentation generator

A documentation generator is a tool that automatically creates documentation from your code comments and annotations. This way, you can avoid writing redundant and outdated documentation, and focus on writing clear and concise code comments that explain the logic and functionality of your code. Some popular documentation generators for operations research are Sphinx for Python, Doxygen for C++ and R, and Roxygen2 for R.

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Sanjay Kumar

Digital Transformation| Cyber Security Analysis | C++| C#|.net | Restful API |SQL| AWS |Azure Cloud | Devops| Healthcare| Technical Architect | Solution Architect| Microservices| Process Optimisation| AI | ML
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Documentation is a type of evidence (digitally signed) that tells us what the requirements are, and what the processes are to meet and achieve them. it is the general meaning of documentation. When talking about the code, the important is how can understand the code functionality by reading the comments and annotation.

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2 Follow a coding style guide

A coding style guide is a set of rules and conventions that define how to write and format your code. Following a coding style guide can improve the readability, consistency, and maintainability of your code, as well as make it easier for others to understand and collaborate on your project. You can use an existing coding style guide, such as PEP 8 for Python, Google C++ Style Guide, or R Style Guide, or create your own based on your preferences and needs.

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Sanjay Kumar

Digital Transformation| Cyber Security Analysis | C++| C#|.net | Restful API |SQL| AWS |Azure Cloud | Devops| Healthcare| Technical Architect | Solution Architect| Microservices| Process Optimisation| AI | ML
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When writing code, several style guides can be used for writing your code based on the programming language. Considerations need to be made when selecting the style guide that works best for you. you have look style guide for language, as well as Google's and Twitter's. These are all publicly available. Creating consistent code is crucial when working in large teams or external teams. If you stray too far from the language norms built up over the past quarter of a century, it just makes onboarding harder. Because you're not only teaching new developers the details of a code base, but you're also wrangling a non-standard style at the same time. many languages have plugins to auto-format code as you write formatting changes automatically.

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Vusal Babashov

Data Scientist at Canadian Tire Corporation | Machine Learning | Ph.D. in Applied Operations Research
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Make sure your code follows best practices in Python such as Pep8. Editors such as VS Code allow for using different code linters such as black, pylint, flake8, etc. Using these tools will help you write Pythonic code.

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3 Use a testing framework

A testing framework is a tool that helps you write, organize, and run tests for your code. Testing your code can help you detect and fix errors, ensure that your code meets the specifications and requirements, and verify that your code behaves as expected under different scenarios and inputs. Some common testing frameworks for operations research are PyTest for Python, Google Test for C++, and Testthat for R.

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Sanjay Kumar

Digital Transformation| Cyber Security Analysis | C++| C#|.net | Restful API |SQL| AWS |Azure Cloud | Devops| Healthcare| Technical Architect | Solution Architect| Microservices| Process Optimisation| AI | ML
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The selection of the right testing framework for your written code, there are many testing frameworks, Cucumber, Cypress, Modularity driven testing, google test, etc, all depend on what is the scope you are looking to cover through your testing framework

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4 Automate your documentation and testing

Automating your documentation and testing can save you time and effort, as well as ensure that your documentation and testing are always up to date and consistent with your code. You can use a tool such as Makefile, which is a file that specifies the commands and dependencies for building and running your project, to automate the generation and deployment of your documentation, as well as the execution and reporting of your tests.

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Vusal Babashov

Data Scientist at Canadian Tire Corporation | Machine Learning | Ph.D. in Applied Operations Research
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I like automated docstring generation tools that are nowadays available for editors. For example, VS code has an auto Docstring generator extension for Python.

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5 Review and update your documentation and testing

Even with automation, you still need to review and update your documentation and testing regularly, especially when you make significant changes to your code or add new features or functionalities. You can use a tool such as Git, which is a version control system that tracks and manages the changes to your code, to review the differences between the versions of your code, as well as the corresponding documentation and testing. You can also use a tool such as GitHub, which is a platform that hosts and facilitates the collaboration on Git repositories, to solicit feedback and suggestions from other developers or stakeholders on your documentation and testing.

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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?

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How can you ensure that your code documentation and testing are scalable?

1

2

3

4

5

6

1 Use a documentation generator

2 Follow a coding style guide

3 Use a testing framework

4 Automate your documentation and testing

5 Review and update your documentation and testing

6 Here’s what else to consider

Operations Research

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How can you ensure that your code documentation and testing are scalable?

1

2

3

4

5

6

1 Use a documentation generator

2 Follow a coding style guide

3 Use a testing framework

4 Automate your documentation and testing

5 Review and update your documentation and testing

6 Here’s what else to consider

Operations Research

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