Little-o (o) and Little-omega (ω) Notations provide more precise ways to describe the growth rate of functions. While Big-O and Big-Omega set upper and lower bounds that an algorithm’s complexity can approach, little-o and little-omega are stricter. They define cases where a function grows strictly slower (little-o) or strictly faster (little-omega) than another.

Little-o Notation (o-notation)

Little-o notation, represented as o(g(n)), describes a function f(n) that grows strictly slower than g(n). In other words, f(n) approaches zero relative to g(n) as n grows larger.