Advanced -> Meet-In-The-Middle

Split a subset-like exact search into two halves, enumerate exact half summaries, and merge them faster than full 2^n brute force.

• Topic slug: advanced/meet-in-the-middle
• Tutorial page: Open tutorial
• Ladder page: Open ladder
• Repo problems currently tagged here: 1
• Repo companion pages: 3
• Curated external problems: 3

Microtopics

• half-enumeration
• subset-sums
• sort-and-merge
• hash-merge
• n-around-40
• sqrt-state-space

Learning Sources

Source	Type
USACO Guide meet in the middle	Reference
Competitive Programmer's Handbook	Reference
Jeff Erickson - Algorithms	Course

Practice Sources

Source	Type
CSES Meet in the Middle	Practice
SPOJ SUBSUMS	Practice
AtCoder ABC184 F	Practice

Repo Companion Material

Material	Type
Meet-In-The-Middle hot sheet	quick reference
Meet in the Middle note	anchor note
Discrete Log note	algebraic compare point

Curated External Problems

Core

Problem	Source	Difficulty	Context	Style	Prerequisites	Tags	Why it fits
Meet in the Middle	CSES	Medium-Hard	Mitm	Exact Search; Sort-And-Merge	Subset Enumeration; Binary Search	Subset-Sum; Counting	The cleanest internal anchor for the classic half-sum enumeration route.
Programming Contest	AtCoder	Medium-Hard	Mitm	Exact Search; Optimization	Subset Enumeration; Binary Search	Best-Feasible-Sum; Binary Search	A standard best-sum-no-more-than-S route where the merge is about best feasible complement rather than multiplicity.

Classics

Problem	Source	Difficulty	Context	Style	Prerequisites	Tags	Why it fits
SUBSUMS	SPOJ	Medium-Hard	Mitm	Exact Search; Counting	Subset Enumeration; Sorting	Subset-Sum; Range Counting	A classic SPOJ benchmark for half-sum generation with a counting-flavored merge.

Repo Problems

Code	Title	Fit	Difficulty	Pattern	Note	Solution
MEETINTHEMIDDLE	Meet in the Middle	primary	medium-hard	-	Note	Code

Regeneration

python3 scripts/generate_problem_catalog.py