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Everything about Implicit computational complexity

Implicit computational complexity (ICC) is a subfield of computational complexity theory that characterizes programs by constraints on the way in which they are constructed, without reference to a specific underlying machine model or to explicit bounds on computational resources unlike conventional complexity theory. The central goal of ICC is to identify programming formalisms — such as restricted formal languages, type systems, or recursion schemes — whose expressive power coincides exactly with a given complexity class, so that membership in the class becomes a consequence of syntactic well-formedness rather than a separate computational argument. ICC was developed in the 1990s and employs the techniques of proof theory, substructural logic, linear logic, model theory and recursion theory to prove bounds on the expressive power of high-level formal languages. Among its founding contributions are Girard, Scedrov, and Scott’s bounded linear logic (1992), Bellantoni and Cook’s function algebra based on predicative recursion (1992), and Jones’s cons-free programming language characterisation of polynomial time (1999). ICC is also concerned with the practical realization of functional programming languages, language tools and type theory that can control the resource usage of programs in a formally verifiable sense. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Implicit computational complexityA 5-minute orientation
  2. Skim a recent paper: Implicit computation complexity in higher-order programming languagesInfluential work since 2022
  3. Pick up a classic book: Recent advances in real complexity and computationThe most-reprinted book on the subject
  4. Read the landmark paper: Quantum implicit computational complexityCited 24 times
  5. Go sideways: Primitive recursive functionA closely related topic
  6. Go sideways: Recursion (computer science)A closely related topic

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