Part 2: Be Wary of the Dark Side of LLM-Powered Coding

This section addresses critical challenges and risks associated with using Large Language Models in software development. We will examine how biases can affect shape code due to training data limitations and ethical practices for minimizing these effects. We will also explore potential legal risks such as intellectual issues and jurisdictional variances and we will see how to handle them. We will also learn to mitigate various vulnerabilities that may emerge in LLM-generated code. Finally, we discuss the inherent limitations of LLMs in handling coding tasks and the inconsistencies that can arise.

This section covers the following chapters:

• Chapter 4, Demystifying Generated Code for Readability
• Chapter 5, Addressing Bias and Ethical Concerns in LLM-Generated Code
• Chapter 6, Navigating the Legal Landscape of LLM-Generated Code
• Chapter 7, Security Considerations and Measures