calculi

If one does a deep embedding then powerful calculi can be embedded in much weaker calculi.

The problem is bad enough when dealing with core calculi---as this post demonstrates, being precise is doubly important when dealing with feature-rich languages, like C#.

Graphical calculi for monoidal categories date back to Kelly and Laplaza (1980), with later refinements by Joyal-Street and Yetter.

Any suggestions for resources that could help get me more comfortable with reading and understanding type calculi?

Strong normalization theorems are used for typed lambda calculi like the Calculus of Inductive Constructions to show consistency, as well.

Functional programming languages, at their core, are just lambda calculi with some syntactic sugar.

In particular, linguists use typed λ-calculi to construct formal semantics for sentences.

It's good to learn about applying types to process calculi.

Summary for the layperson: The Curry-Howard Isomorphism is an exact syntactic correspondence between types for lambda calculi, propositions in intuitionistic logics, and objects in closed Cartesian categories.

Point-free reasoning is a good way to avoid some of these complications, which contributes to the popularity of combinator calculi like SKI when teaching untyped lambda calculus.

Linear-session-typed process calculi are guaranteed deadlock-free and race-free.

How many process calculi are you familiar with?

A slow-paced textbook like Hankin's "An Introduction to Lambda Calculi for Computer Scientists", and doing the exercises in the first few chapters should do the job.

The problem then becomes a matter of learning various types of "lambda calculi", or similar formalism, usually in 10 minutes, and you don't have to waste a life-time learning the indentation and semi-colon termination rules of yet another procedural language thrown out at you from the blogosphere.

Communicating Sequential Processes (CSP) also came out of the Process Calculi.