My Mathematical Regression
A programmer unearthed their decade-old Project Euler solution for a grid path problem, revealing an elegant mathematical insight that required no code. This discovery sparked a nostalgic reflection on the stark difference between their past intuitive problem-solving and their current inclination to brute-force or use AI. The story resonates deeply within the HN community by contrasting fundamental theoretical computer science with modern development pragmatism.
The Lowdown
The author recounts a recent dive into their old Project Euler repository, a digital time capsule from their student days. Among the Python scripts, a simple text file for "Problem 15" presented a stark contrast between their past and present problem-solving approaches, leading to a thoughtful contemplation on the evolution of their engineering skills.
- The author revisited their 10-year-old Project Euler solutions repository, discovering
problem15.txt. - Problem 15 requires finding the number of routes through a 20x20 grid, moving only right or down from top-left to bottom-right.
- The author's current self would likely approach this with programming techniques like brute-force, memoization, dynamic programming, or even by offloading it to an AI.
- Their student-era solution, however, was a simple comment within the text file stating the problem follows the pattern of "(2n) choose n," directly calculating the binomial coefficient for n=20.
- This elegant mathematical solution required no actual programming, leading to the result (2*20) choose 20 = 137,846,528,820.
- The author expressed admiration for their past self's intuitive grasp of discrete mathematics and sadness over their current, more pragmatic (or perhaps less fundamental) approach.
- The experience led to reflection on how reliance on modern tools and AI might diminish foundational problem-solving skills.
This personal anecdote serves as a poignant reminder of the enduring power of fundamental mathematical principles in computer science and raises questions about how contemporary development practices might be shaping (or eroding) engineers' core problem-solving acumen.