Syntax and Semantics

Type theory takes syntax more seriously than I ever realize. It’s like drawing a house. Do you draw a box with a triangle over it, or do you really look.


These are something you can write on paper that represents “I know this”. This is where your mind meets the paper in some sense.


  • Has type $\Gamma \turnstile t : T$
  • Is well formed
  • Is Type $\Gamma \turnstile
  • evaluates to (big step/small step) $(1 + 3) \downarrow 4$ or $(1+3) \rightarrow 4$
  • Hoare logic step {true}x := 3{x > 0}
  • Sequent. Under the assumption A,B hold, A holds. $A,B - A$
  • Focused Sequent. Kind of fishy that this has intuitive meaning
  • Type synthesizes, Type Checks - In bidirictional typing discipline, a type being synthesizable/inferrable from the term vs a type being checkable given both type and term are distinct judgements.

Inference Rules

These are the things drawn with horizontal lines. They take you from


Concrete computer encodings of judgements and inference rules

  • Coq inductive types
  • Prolog programs (Twelf is related I think)
  • Ocaml/Haskell/python functions. There are many different modes you might pick. You can choose
  • Tactics

Computation Rules

I don’t know what this means really. Whatever it means, probably beta reduction (applying lambda functions) is included.

The central idea I think is that if you’re building a theorem prover, it needs to understand how to do something. The hypothesis is that it is useful and flexible for the theorem prover to understand well behaved operations of lambda calculus. Lambda calculus has it’s origin as a study of pure logic. It hopefully is capable of expressing anything that belongs to our intuitive notion of “algorithm” (again this was what it was invented for).

So we might want to build in knowing how to add numbers or do sines or cosines or something into our theorem prover, but we can usefully encode these concepts into the master concepts of lambda calculus.

I am ultimately not convinced or unconvinced this hypothesis holds and wonder if the mainstream of interactive theorem proving isn’t a little too attached to the idea.

Conversion vs Reduction vs Expansion

Coq may have it’s own idiosyncratic naming for different kinds of reduction rules.

  • (fun x => x ) q ~> q beta conversion
  • (fun x => x) ~> (fun z => z) alpha conversion, aka dummy index rewriting
  • match () with () => z ~> z match conversion
  • let x := 3 in x ~> 3 zeta reduction
  • if Definition foo := 3. then foo ~> 3 delta reduction/unfolding of definitions
  • f ~> (fun x => f x), eta conversion. expanding ou
  • x ~> match x with tt => x end Is this right? This is eta for unit

I think eta conversion is the most confusing and puzzling out of all of them. Sometimes eta may refer to only eta expanding functions, but other times it may be referring to the relationship of a data type with it’s match statement.

In some sense functions are very special datatypes. They are not defined via an Inductive definition. But they are also can be thought of as being kind of similar to these data types. The “constructor” of a function is a lambda binder, and the “eliminator” is an application. We can encode data types into functions using church like encodings. match can be encoded by positing a special function that has a computation rule like match.

Decidability of type checking

type checking is the question of whether given all the pieces going into the judgement under line of the inference rule, is it decidable to construct a typing tree that produces such a thing. Even this seemingly simple question can be undecidable in some type systems, because higher up in the typing tree you may ask questions that are very difficult. In the presence of nontermination, you probably are encountering a variant of the halting problem. Undecidability of type checking is typically considered to be an undesriable property, but people are willing to entertain the notion.

Type inference supposes I give the context and term, but leave out the type, can I construct both the typing tree and the type. Principle types are asking whether there is a unique most general type that can be inferred.



Preservation, Subject Reduction

Evaluation does not cause types to change.




Head Normal Form




Reducible Expression

Curry vs Church style


Extensional vs Intensional

Extensional equality collapses definitional and propositional equality.

Adding a rule

Gamma |- t : Id_Type A B
Gamma |- A = B

Notice that this is a transition from a typing judgement to a definitional equality judgement. Very different fellas.

Judgemental/Definitional / Propositional

Another way of talking about judgementally equal is if the proof of Prop equality is just eq_refl. Why is this? Well, type checkeing more or less must look for an inferrance rule with eq_refl : a = b below the horizontal line. This rule breaks apart this problem into a definitional. Definitional equality is so in the air we breath, it may not even be noted explicitly. Any nonlinear occurence of pattern variables in the inferrence rule must imply it.

Tests. Example Definition mytest : tt = tt := eq_refl. See if coq accepts it

  • tt = tt
  • unit = unit
  • 1 + 1 = 2
  • x : nat |- x + 0 = x
  • x : nat |- 0 + x = x
  • (fun x => x) = (fun x => x)
  • (fun x => x) = (fun x => tt)
  • (match tt with tt => tt end) = tt
  • x : unit |- tt = x
  • x : unit |- match x with () => () end = ()
  • x : unit |- match x with () => () end = x
  • x : unit |- match x with () => () end = match x with _ => () end
  • f |- f = (fun x => f x) eta
  • (fun x => x) tt = tt beta


  • Prop vs Type vs Set - Prop is impredicative. Prop and Set are deleted during extraction? Which make them interestingly different from a metaprogramming perspective.

Prop SProp Set SProp is Prop with proof irrelevance

Impredicative vs Predicative

This is describing allowing some kind of form of self reference I think.

Proof Irrelevance

Propositional extensionality implies proof irrelevance Axiom proof_irrelevance : forall (P:Prop) (p1 p2:P), p1 = p2. RFC: Disentangling erasure and proof irrelevance

It feels like proof irrelevance and erasure are related concepts, but like almost everything in type theory there is probably a time and place and level of sophistication to consider them as distinct

Irrelevance, Polymorphism, and Erasure in Type Theory

Universes Universes are

Algerbaic universes - If the levels of type are a DAG, they can be ordered. So one doesn’t eagerly pick integer levels for Type. Instead you maintain contraints like max{l1,l2} etc.


Extensionality is a notion that applies to more than just function and equality types.

forall x, f x = g x -> f = g forall A B : Prop, A <-> B -> A = B forall x, x = match x with () -> ()

Consider fun x -> x = fun x -> tt Is this provable?

Some of these are provable

alpha beta eta iota

Computational Content

Heterogenous vs Homogenous equality

Eta equivalence - The dumb expansion? Observational Equivalence

Reduction vs Equivalence


Implies extensionality Example unit' = unit Isomorphisms future of impredicative set

Amusingly, by mixing the type level and value level, do we end up with a situation akin to dynamic types where we often need to carry types a runtime? Or is that mistaken?


  • TAPL
  • Programming Language Foundations - Harper
  • Programming in Martin Lof Type Theory
  • Software Foundations
  • PLFA

System T

“Quantifier free theory of functionals of finite type”

Logical Relations

Tait proved strong normalization using them 1967.

Parametricity is supposedly an example also


Cody’s suggested book TOC Extensional vs Intensional models? Chapter 1: The type theory and its variants:

  1. The CIC with universes
  2. Recursors vs guarded fixpoints
  3. Predicative variant
  4. Untyped conversion
  5. Some additional conversion rules
  6. Extensionality principles
  7. Anti-extensionality principles
  8. Coinduction Chapter 2: Theorems about syntax
  9. Substitution, weakening
  10. Well-sortedness
  11. Progress and preservation
  12. Uniqueness of types(?)
  13. Properties of normal forms Chapter 3: Extensional models
  14. The not-so-simple set theoretic interpretation
  15. Models of sets in types
  16. The effective topos interpretation
  17. The groupoid interpretation
  18. Consistency implications Chapter 4: Intensional models
  19. Realizability interpretations
  20. The Lambda-set model
  21. The normalization proof
  22. Consistency implications Chapter 5: Inconsistent combinations of rules
  23. Failures of subject reduction
  24. Failures of termination alone
  25. Impredicative inconsistencies
  26. Guard condition and inductive type issues
  27. Other universe issues

smalltt a demo for high performance type theory elaboration. Really good readme too elboration seminar learn type theory

regular propositions are basically the “constructive-content-free” parts of propositions