Articles

Foundations

How do you calculate a complexity budget?
Foundations Algorithms & theory
How to start solving a problem?
Foundations Algorithms & theory
Implement: make the code preserve the design
Foundations Algorithms & theory
Trace test: watch the state the program actually creates
Foundations Algorithms & theory
Reduce: translate the problem without losing its meaning
Foundations Algorithms & theory
What is an invariant?
Foundations Algorithms & theory

Algorithms & theory

How do you calculate a complexity budget?
Foundations Algorithms & theory
How to start solving a problem?
Foundations Algorithms & theory
Implement: make the code preserve the design
Foundations Algorithms & theory
Trace test: watch the state the program actually creates
Foundations Algorithms & theory
Reduce: translate the problem without losing its meaning
Foundations Algorithms & theory
What is an invariant?
Foundations Algorithms & theory
The halting problem: why code can only be run, never read
Algorithms & theory
a monad is a monoid in the category of endofunctors
Algorithms & theory
Rate limiting: the window that expires before it floods
Algorithms & theory
Backpressure: the queue that says no before it overflows
Algorithms & theory
P vs NP: when a thousand cores won't help
Algorithms & theory
What O(n) actually promises
Algorithms & theory
Counting the work: from recurrences to big O
Algorithms & theory
Hash tables: the O(1) that has fine print
Algorithms & theory
Amortized: the expensive step you almost never take
Algorithms & theory
Sorting: the wall at n log n
Algorithms & theory
Dynamic programming: recursion with a cache
Algorithms & theory
Graphs: when the answer is a hop away
Algorithms & theory
Tables all the way down: learning algorithms without standard library magic
Algorithms & theory
When an approximate answer is worth an infinite speedup: Bloom filters, Count-Min sketches, and HyperLogLog
Algorithms & theory
Binary tree traversals: pre, in, and post-order as views of recursive state
Algorithms & theory
Binary trees: where the log in O(log n) lives
Algorithms & theory
Stacks, queues, and associative arrays: the data shapes your algorithms run on
Algorithms & theory
The encoding: how complex structures hide in simple ones
Algorithms & theory
Two pointers: the pattern hiding in plain sight
Algorithms & theory
Compilers for the practicing programmer
Algorithms & theory
What a comparison is worth: the log from first principles
Algorithms & theory
Binary search: halving the search space in O(log n)
Algorithms & theory
Backtracking: recursion that can undo a choice
Algorithms & theory
Strings: the array of characters hiding a stack of agreements
Algorithms & theory
Earliest deadline first: the algorithm behind your review schedule
Algorithms & theory
Heaps: the structure behind every scheduler
Algorithms & theory
Dijkstra's algorithm: when every hop costs something
Algorithms & theory
Greedy: when the local choice is the global one
Algorithms & theory
Parsing: turning text into trees
Algorithms & theory
An interpreter is just an evaluator
Algorithms & theory
Algorithms past the interview: what the handshake is actually measuring
Algorithms & theory