Cons of using github copilot

Question

I just wanted to know the practical hurdles or cons faced in real time. Your insights would be a great help.

Deepak Tewatia · Answer

My feedback on GitHub Copilot GitHub Copilot suggests code based on existing patterns. It may not always use the best coding practices and standards. The cost for teams and enterprises is very high. Sometimes code suggestions might not fit your project's specific setup and configuration requiring extra time to debug and fixing. Thanks

Mithilesh Tata · Answer

GitHub Copilot like any other tool has its limitations and potential drawbacks. Here are some cons to consider when using GitHub Copilot: Overreliance on the Tool : GitHub Copilot can provide suggestions and generate code snippets but it's important for developers not to rely solely on it. Overreliance on Copilot might lead to a lack of understanding of fundamental programming concepts or cause developers to overlook potential errors or inefficiencies in the generated code. Limited Context Understanding : While GitHub Copilot is impressive in generating code based on the provided context it may not always fully understand the specific requirements or constraints of a given project. This can lead to suggestions that are not entirely appropriate for the task at hand or require significant modification. License and Legal Concerns : GitHub Copilot generates code based on patterns learned from publicly available sources including open-source projects. There may be legal and licensing implications when using code generated by Copilot especially if it closely resembles code from proprietary or copyrighted sources. Quality of Generated Code : While GitHub Copilot aims to generate high-quality code the quality of the suggestions can vary. Generated code may not always follow best practices may be inefficient or may contain bugs. It's essential for developers to review and test the generated code thoroughly. Security Risks : Automatically generated code if not properly reviewed may introduce security vulnerabilities into a project. Developers need to be cautious and ensure that the generated code does not inadvertently expose the application to security threats. Potential Bias and Stereotyping : Since GitHub Copilot learns from existing code repositories it may inadvertently replicate biases or stereotypes present in those repositories. This could lead to the generation of insensitive or inappropriate code comments or suggestions. Learning Hindrance : While GitHub Copilot can aid in completing tasks quickly it may hinder the learning process for developers particularly those who rely heavily on it. Developers should strive to understand the code they write and not use Copilot as a crutch that replaces learning and problem-solving skills. Dependency on Internet Connectivity : GitHub Copilot relies on an internet connection to function properly as it needs to access GitHub's codebase and machine learning models. Working in environments with limited or no internet connectivity may impact the availability and performance of Copilot.