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Code Debugging with LLMs
A Large Language Model that has been trained on extensive datasets of both source code and natural language can be effectively utilized for the task of code debugging.
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Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Code Debugging with LLMs
Analyzing Types of Textual Correction
A language model is tasked with correcting the following sentence: "To improve the car's aerodynamics, the engineers decided to increase its weight and add a large, flat spoiler." Which of the following options best analyzes the error and proposes a logical correction?
Evaluating an LLM's Text Correction
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A developer has written the Python function below to find the smallest number in a list of positive integers. When they test it with the list
[10, 3, 8, 5], the function incorrectly returns0instead of the expected3.def find_smallest_number(numbers): smallest_so_far = 0 for num in numbers: if num < smallest_so_far: smallest_so_far = num return smallest_so_farThey ask a large language model for help debugging it. Analyze the four potential responses from
Crafting an Effective Debugging Prompt
A developer is working on four different code snippets, each containing a bug. In which of the following scenarios would a large language model, trained on a vast corpus of code, be most effective at identifying and suggesting a fix for the error?