* This blog post is a summary of this video.
Testing ChatGPT's Code Problem-Solving Abilities on LeetCode
Table of Contents
- Examining ChatGPT's Performance on Easy LeetCode Problems
- ChatGPT's Handling of Medium-Level LeetCode Challenges
- Solving Complex LeetCode Problems with ChatGPT
- ChatGPT Beats Most Human Coders on LeetCode Leaderboards
- The Future of AI and Its Impact on Software Engineering
- Conclusion and Final Thoughts
Examining ChatGPT's Performance on Easy LeetCode Problems
In this blog post, we will be examining ChatGPT's capabilities in solving coding problems on LeetCode. We will start with an easy problem, then look at a medium one before testing ChatGPT on 5 hard LeetCode challenges.
Our goal is to incrementally push ChatGPT to its limits to see how it performs. Can an AI really create solutions for tough algorithmic problems that only highly skilled software engineers can typically solve?
The Two Sum Coding Question
We began with the famously easy Two Sum problem on LeetCode. After providing the problem statement and inputs to ChatGPT, it generated a clean Java solution utilizing a HashMap in just a few seconds. Upon testing, the code worked flawlessly. When submitted on LeetCode, ChatGPT's Two Sum solution actually ranked among the top fastest out of all submissions. Pretty impressive for an AI just getting started!
ChatGPT's Handling of Medium-Level LeetCode Challenges
Next, we tested ChatGPT on a medium difficulty LeetCode question. Once again, after providing the necessary problem statement and inputs, ChatGPT produced valid Java code that passed all test cases.
Its solution for the medium problem ranked as one of the fastest on LeetCode as well. At this point, it was clear ChatGPT could breeze through simple and medium challenges - but how would it fare on truly hard algorithm problems?
Solving Complex LeetCode Problems with ChatGPT
We provided ChatGPT with 5 notoriously tricky LeetCode problems that often stump even experienced software engineers in interviews. These are the kinds of questions that can take 30-40 minutes to work out an optimal algorithm during a coding test.
Amazingly, ChatGPT generated solutions for all 5 hard problems! For most, its initial code submissions passed all test cases. When optimizations were needed for performance, ChatGPT gracefully updated its solutions when prompted to improve runtime.
For 3 out of the 5 extremely hard LeetCode challenges, ChatGPT produced solutions that outperformed over 80% of all other submissions. For 1 problem, it ranked better than 44% of submissions, and for 1, my own solution was slightly faster.
ChatGPT Beats Most Human Coders on LeetCode Leaderboards
Examining the LeetCode leaderboards shows just how capable ChatGPT is compared to human coders. Its solutions for easy and medium problems blow away most other submissions in terms of runtime efficiency.
Even for notoriously hard algorithm challenges, ChatGPT can crank out solutions that outperform what the majority of engineers are able to code in interviews or exams when under time pressure.
This astonishing coding capability from an AI has enormous implications. Software engineering interviews and coding assessments may need an overhaul in light of ChatGPT's launch. With further improvement, could we reach a point where AI assistants surpass nearly all human programmers?
The Future of AI and Its Impact on Software Engineering
ChatGPT today is like the original iPhone back in 2007. Revolutionary when first launched, but still primitive compared to how the technology will progress.
As AI assistants become far more advanced over the next decade, they threaten to automate a significant portion of programming work currently done by software engineers.
Companies will need to validate engineering talent in new ways going forward. Coding interviews and online algorithm tests may fade into obsolescence as AI tools create solutions as fast as the smartest programmers.
Conclusion and Final Thoughts
In testing ChatGPT on programming problems across the easy, medium and hard difficulty spectrums on LeetCode, the AI assistant blew away expectations with its coding capabilities.
While ChatGPT still requires oversight and occasional performance tuning from engineers, it can generate clean, efficient code for even extremely complex algorithm challenges - the types of problems that trip up many developers in high-stakes interviews.
As conversational AI continues its rapid pace of advancement, the technology will trigger a revolution in software engineering. Programmers may increasingly morph into trainers and overseers of AI systems like ChatGPT that themselves crank out lines of code. Exciting times are ahead!
FAQ
Q: What coding problems did ChatGPT solve in this test?
A: ChatGPT was tasked with solving easy, medium and hard problems from LeetCode, including Two Sum, Merge K Sorted Lists, Reverse Nodes in K Groups and Sudoku Solver.
Q: How efficiently did ChatGPT solve the problems?
A: ChatGPT solved most problems very efficiently, beating over 80-100% of other human written solutions on LeetCode in terms of runtime and memory usage.
Q: What was the hardest problem ChatGPT solved?
A: The hardest problem solved was the Sudoku Solver question, which ChatGPT initially solved suboptimally but then improved to beat 91% of other solutions.
Q: What does this mean for the future of coding interviews?
A: With ChatGPT's strong coding abilities, companies may need to rethink coding interviews and assessments to evaluate candidates in new ways.
Q: How could AI like ChatGPT impact software engineering?
A: AI assistants like ChatGPT have the potential to drastically augment and enhance software engineers' productivity in writing, testing and debugging code.
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