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Version: 1.4.0

Michelson and LIGO

Currently LIGO compiles to Michelson, the native smart contract language supported by Tezos. This page explains the relationship between LIGO and the underlying Michelson it compiles to. Understanding Michelson is not a requirement to use LIGO, but it does become important if you want to formally verify contracts using Mi-Cho-Coq or tune the performance of contracts outputted by the LIGO compiler.

The rationale and design of Michelson

Michelson is a Domain-Specific Language (DSL) for writing Tezos smart contracts inspired by Lisp and Forth. This unusual lineage aims at satisfying unusual constraints, but entails some tensions in the design.

First, to measure step-wise gas consumption, Michelson is interpreted.

On the one hand, to assess gas usage per instruction, instructions should be simple, which points to low-level features (a RISC-like language). On the other hand, it was originally thought that users will want to write in Michelson instead of lowering a language to Michelson, because the gas cost would otherwise be harder to predict. This means that high-level features were deemed necessary (like a restricted variant of Lisp lambdas, a way to encode algebraic data types, as well as built-in sets, maps and lists).

To avoid ambiguous and otherwise misleading contracts, the layout of Michelson contracts has been constrained (e.g., indentation, no UTF-8), and a canonical form was designed and enforced when storing contracts on the chain.

To reduce the size of the code, Michelson was designed as a stack-based language, whence the lineage from Forth and other concatenative languages like PostScript, Joy, Cat, Factor etc. (Java byte-code would count too.)

Programs in those languages are compact because they assume an implicit stack in which some input values are popped, and output values are pushed, according to the current instruction being executed.

Each Michelson instruction modifies a prefix of the stack, that is, a segment starting at the top.

Whilst the types of Michelson instructions can be polymorphic, their instantiations must be monomorphic, hence Michelson instructions are not first-class values and cannot be partially interpreted.

This enables a simple static type checking, as opposed to a complex type inference. It can be performed efficiently: contract type checking consumes gas. Basically, type checking aims at validating the composition of instructions, therefore is key to safely composing contracts (concatenation, activations). Once a contract passes type checking, it cannot fail due to inconsistent assumptions on the storage and other values (there are no null values, no casts), but it can still fail for other reasons: division by zero, token exhaustion, gas exhaustion, or an explicit FAILWITH instruction. This property is called type safety. Also, such a contract cannot remain stuck: this is the progress property.

The existence of a formal type system for Michelson, of a formal specification of its dynamic semantics (evaluation), of a Michelson interpreter in Coq, of proofs in Coq of properties of some typical contracts, all those achievements are instances of formal methods in Tezos.

Here is an example of a Michelson contract.

counter.tz

{ parameter (or (or (nat %add) (nat %sub)) (unit %default)) ;
storage int ;
code { AMOUNT ; PUSH mutez 0 ; ASSERT_CMPEQ ; UNPAIR ;
IF_LEFT
{ IF_LEFT { ADD } { SWAP ; SUB } }
{ DROP ; DROP ; PUSH int 0 } ;
NIL operation ; PAIR } }

The contract above maintains an int as its storage. It has two entrypoints, add and sub, to modify it, and the default entrypoint of type unit will reset it to 0.

The contract itself contains three sections:

  • parameter - The argument provided by a transaction invoking the contract.
  • storage - The type definition for the contract's data storage.
  • code - Actual Michelson code that has the provided parameter and the current storage value in its initial stack. It outputs in the resulting stack a pair made of a list of operations and a new storage value.

Michelson code consists of instructions like IF_LEFT, PUSH ..., UNPAIR etc. that are composed sequentially in what is called a sequence. The implicit stack contains at all times the state of the evaluation of the program, whilst the storage represents the persistent state. If the contract execution is successful, the new storage state will be committed to the chain and become visible to all the nodes. Instructions are used to transform a prefix of the stack, that is, the topmost part of it, for example, by duplicating its top element, dropping it, subtracting the first two etc.

💡 A Michelson program running on the Tezos blockchain is meant to output a pair of values including a list of operations to include in a transaction, and a new storage value to persist on the chain.

Stack versus variables​

Perhaps the biggest challenge when programming in Michelson is the lack of variables to denote the data: the stack layout has to be kept in mind when retrieving and storing data. For example, let us implement a program in JavaScript that is similar to the Michelson above:

counter.js

var storage = 0;
function add (a) { storage += a; }
function sub (a) { storage -= a; }
// We are calling this function "reset" instead of "default"
// because `default` is a Javascript keyword
function reset () { storage = 0; }

In our JavaScript program the initial storage value is 0 and it can be modified by calling add (a), sub (a) and reset ().

We cannot run JavaScript on the Tezos blockchain, but we can choose LIGO, which will abstract the stack management and allow us to create readable, type-safe, and efficient smart contracts.

The JsLIGO program is very similar to the above naive JavaScript example. The notable differences are:

  • the main functions return the new storage, instead of updating it
  • the main functions also return a list of operations, this is used to transfer tokens out of the contract to other addresses
  • As in TypeScript, we need to specify the input / output type of some functions, where the compiler cannot guess them. This helps the compiler perform extra checks and weed off some bugs before they ever happen.
type t_storage = int
type result = [list<operation>, t_storage]
@entry
function add (a, storage) : result { return [list([]), storage + a]; }
@entry
function sub (a, storage) : result { return [list([]), storage - a]; }
@entry
function reset (_ : unit, _storage : t_storage) : result { return [list([]), 0]; }