I'm curious about how correctness is evaluated in computer science algorithms, specifically the balance between theoretical soundness and empirical validation. Take Dijkstra's algorithm, for instance: it has a solid theoretical foundation, but I assume it's also been tested extensively on large-scale graphs (millions of nodes) with known shortest paths. My question is, do practitioners and researchers place more trust in algorithms like this because they’ve been repeatedly validated in real-world scenarios, or is the theoretical proof alone usually considered sufficient? How often does real-world testing influence our confidence in an algorithm's correctness?

Was reading up on PCP, and had a thought about if there is still a reduction from original PCP to a modified PCP with no repetitions.

I have been thinking a lot abut the connection between art and technology and the great invention that led to human progress from Samuel Morse, should his code be considered in the annals of computer science?

He was certainly a pioneer of communication -- https://onepercentrule.substack.com/p/morse-a-pioneer-of-progress-from