Parsing Expressions

Grammar, which knows how to control even kings. Molière

This chapter marks the first major milestone of the book. Many of us have cobbled together a mishmash of regular expressions and substring operations to extract some sense out of a pile of text. The code was probably riddled with bugs and a beast to maintain. Writing a real parser — one with decent error-handling, a coherent internal structure, and the ability to robustly chew through a sophisticated syntax — is considered a rare, impressive skill. In this chapter, you will attain it.

It’s easier than you think, partially because we front-loaded a lot of the hard work in the last chapter. You already know your way around a formal grammar. You’re familiar with syntax trees, and we have some Java classes to represent them. The only remaining piece is parsing — transmogrifying a sequence of tokens into one of those syntax trees.

Some CS textbooks make a big deal out of parsers. In the 60s, computer scientists — reasonably fed up with programming in assembly language — started designing more sophisticated, human-friendly languages like FORTRAN and ALGOL. Alas, they weren’t very machine-friendly, for the primitive machines at the time.

They designed languages that they honestly weren’t even sure how to write compilers for, and then did ground-breaking work inventing parsing and compiling techniques that could handle these new big languages on those old tiny machines.

Classic compiler books read like fawning hagiographies of these pioneers and their tools. The cover of “Compilers: Principles, Techniques, and Tools” literally has a dragon labeled “complexity of compiler design” being slain by a knight bearing a sword and shield branded “LALR parser generator” and “syntax directed translation”. They laid it on thick.

A little self-congratulation is well-deserved, but the truth is you don’t need to know most of that stuff to bang out a high quality parser for a modern machine. As always, I encourage you to broaden your education and take it in later, but this book omits the trophy case.

6 . 1 Ambiguity and the Parsing Game

In the last chapter, I said you can “play” a context free grammar like a game in order to generate strings. Now, we play that game in reverse. Given a string — a series of tokens — we map those tokens to terminals in the grammar to figure out which rules could have generated that string.

The “could have” part is interesting. It’s entirely possible to create a grammar that is ambiguous, where different choices of productions can lead to the same string. When you’re using the grammar to generate strings, that doesn’t matter much. Once you have the string, who cares how you got to it?

When parsing, ambiguity means the parser may misunderstand the user’s code. Here’s the Lox expression grammar we put together in the last chapter:

expression  literal
           | unary
           | binary
           | grouping ;

literal     NUMBER | STRING | "false" | "true" | "nil" ;
grouping    "(" expression ")" ;
unary       ( "-" | "!" ) expression ;
binary      expression operator expression ;
operator    "==" | "!=" | "<" | "<=" | ">" | ">="
           | "+"  | "-"  | "*" | "/" ;

This is a valid string in that grammar:

6 / 3 - 1

But there are two ways we could have generated it. One way is:

  1. Starting at expression, pick binary.
  2. For the left-hand expression, pick NUMBER, and use 6.
  3. For the operator, pick "/".
  4. For the right-hand expression, pick binary again.
  5. In that nested binary expression, pick 3 - 1.

Another is:

  1. Starting at expression, pick binary.
  2. For the left-hand expression, pick binary again.
  3. In that nested binary expression, pick 6 / 3.
  4. Back at the outer binary, for the operator, pick "-".
  5. For the right-hand expression, pick NUMBER, and use 1.

Those produce the same strings, but not the same syntax trees:

Two valid syntax trees: (6 / 3) - 1 and 6 / (3 - 1)

In other words, the grammar allows seeing the expression as (6 / 3) - 1 or 6 / (3 - 1). That in turn affects the result of evaluating it. The way mathematicians have solved this ambiguity since blackboards were first invented is by defining rules for precedence and associativity.

Without well-defined precedence and associativity, an expression that uses multiple operators is ambiguous — it can be parsed into different syntax trees, which could in turn evaluate to different results. For Lox, we follow the same precedence rules as C, going from highest to lowest:

Name Operators Associates
Unary ! - Right
Multiplication / * Left
Addition - + Left
Comparison > >= < <= Left
Equality == != Left

How do we stuff these restrictions into our context-free grammar? Right now, when we have an expression that contains subexpressions, like a binary operator, we allow any expression in there:

binary  expression operator expression ;

The expression nonterminal allows us to pick any kind of expression as an operand, regardless of the operator we picked. The rules of precedence limit that. For example, an operand of a * expression cannot be a + expression, since the latter has lower precedence.

For the multiplication operands, we need a nonterminal that means “any kind of expression of higher precedence than *”. Something like:

multiplication  higherThanMultiply "*" higherThanMultiply ;

Since * and / have the same precedence and the level above them is unary operators, a better approximation is:

multiplication  unary ( "*" | "/" ) unary ;

Except that’s not quite right. We broke associativity. This multiplication rule doesn’t allow 1 * 2 * 3. To support associativity, we make one side permit expressions at the same level. Which side we choose determines if the operator is left- or right-associative. Since multiplication and division are left-associative, it’s:

multiplication  multiplication ( "*" | "/" ) unary ;

This is correct, but the fact that the first nonterminal in the body of the rule is the same as the head of the rule means this production is left-recursive. Some parsing techniques, including the one we’re going to use, have trouble with left recursion. Instead, we’ll use this other style:

multiplication  unary ( ( "/" | "*" ) unary )* ;

At the grammar level, this sidesteps left recursion by saying a multiplication expression is a flat sequence of multiplications and divisions. This mirrors the code we’ll use to parse a sequence of multiplications.

If we rejigger all of the binary operator rules in the same way, we get:

expression      equality ;
equality        comparison ( ( "!=" | "==" ) comparison )* ;
comparison      addition ( ( ">" | ">=" | "<" | "<=" ) addition )* ;
addition        multiplication ( ( "-" | "+" ) multiplication )* ;
multiplication  unary ( ( "/" | "*" ) unary )* ;
unary           ( "!" | "-" ) unary ;
               | primary ;
primary         NUMBER | STRING | "false" | "true" | "nil"
               | "(" expression ")" ;

Instead of a single binary rule, there are now four separate rules for each binary operator precedence level. The main expression rule is no longer a flat series of | branches for each kind of expression. Instead, it is simply an alias for the lowest-precedence expression form, equality, because that includes all higher-precedence expressions too.

Each binary operator’s operands use the next-higher precedence level. After the binary operators, we go to unary, the rule for unary operator expressions, since those bind tighter than binary ones. For unary, we do use a recursive rule because unary operators are right-associative, which means instead of left recursion, we have right recursion. The unary nonterminal is at the end of the body for unary, not the beginning, and our parser won’t have any trouble with that.

Finally, the unary rule alternately bubbles up to primary in cases where it doesn’t match a unary operator. “Primary” is the time-honored name for the highest level of precedence including the atomic expressions like literals.

Our grammar grew a bit, but it’s unambiguous now. We’re ready to make a parser for it.

6 . 2 Recursive Descent Parsing

There are a whole pack of parsing techniques whose names mostly seem to be combinations of “L” and “R” — LL(k), LR(1), LALR — along with more exotic beasts like parser combinators, Earley parsers, the shunting yard algorithm, and packrat parsing. For our first interpreter, one technique is more than sufficient: recursive descent.

Recursive descent is the simplest way to build a parser, and doesn’t require using complex parser generator tools like Yacc, Bison or ANTLR. All you need is straightforward hand-written code. Don’t be fooled by its simplicity, though. Recursive descent parsers are fast, robust, and can support sophisticated error-handling. In fact, GCC, V8 (the JavaScript VM in Chrome), Roslyn (the C# compiler written in C#) and many other heavyweight production language implementations use recursive descent. It kicks ass.

It is considered a top-down parser because it starts from the top or outermost grammar rule (here expression) and works its way down into the nested subexpressions before finally reaching the leaves of the syntax tree. This is in contrast with bottom-up parsers like LR that start with primary expressions and compose them into larger and larger chunks of syntax.

A recursive descent parser is a literal translation of the grammar’s rules straight into imperative code. Each rule becomes a function. The body of the rule translates to code roughly like:

Grammar notation Code representation
TerminalCode to match and consume a token
NonterminalCall to that rule’s function
|If or switch statement
* or +While or for loop
?If statement

It’s called “recursive descent” because when a grammar rules refers to itself – directly or indirectly — that translates to recursive method calls.

6 . 2 . 1 The parser class

Each grammar rule becomes a method inside this new class:

create new file
package com.craftinginterpreters.lox;

import java.util.List;

import static com.craftinginterpreters.lox.TokenType.*;

class Parser {
  private final List<Token> tokens;
  private int current = 0;

  Parser(List<Token> tokens) {
    this.tokens = tokens;

Like the scanner, it consumes a sequence, only now we’re working at the level of entire tokens. It takes in a list of tokens and uses current to point to the next token eagerly waiting to be used.

We’re going to run straight through the expression grammar now and translate each rule to Java code. The first rule, expression, simply expands to the equality rule, so that’s straightforward:

add after Parser()
  private Expr expression() {
    return equality();

Each method for parsing a grammar rule produces a syntax tree for that rule and returns it to the caller. When the body of the rule contains a nonterminal — a reference to another rule — we call that rule’s method.

The rule for equality is a little more complex:

equality  comparison ( ( "!=" | "==" ) comparison )* ;

In Java, that becomes:

add after expression()
  private Expr equality() {
    Expr expr = comparison();

    while (match(BANG_EQUAL, EQUAL_EQUAL)) {
      Token operator = previous();
      Expr right = comparison();
      expr = new Expr.Binary(expr, operator, right);

    return expr;

Let’s step through it. The left comparison nonterminal in the body is translated to the first call to comparison() and we store that in a local variable.

Then, the ( ... )* loop in the rule is mapped to a while loop. We need to know when to exit that loop. We can see that inside the rule, we must first find either a != or == token. So, if we don’t see one of those, we must be done with the sequence of equality operators. We express that check using a handy match() method:

add after equality()
  private boolean match(TokenType... types) {
    for (TokenType type : types) {
      if (check(type)) {
        return true;

    return false;

It checks to see if the current token is any of the given types. If so, it consumes it and returns true. Otherwise, it returns false and leaves the token where it is.

The match() method is defined in terms of two more fundamental operations:

add after match()
  private boolean check(TokenType tokenType) {
    if (isAtEnd()) return false;
    return peek().type == tokenType;

This returns true if the current token is of the given type. Unlike match(), it doesn’t consume the token, it only looks at it.

add after check()
  private Token advance() {
    if (!isAtEnd()) current++;
    return previous();

This consumes the current token and returns it, similar to how our scanner’s advance() method did with characters.

These methods bottom out on the last handful of primitive operations:

add after advance()
  private boolean isAtEnd() {
    return peek().type == EOF;

  private Token peek() {
    return tokens.get(current);

  private Token previous() {
    return tokens.get(current - 1);

isAtEnd() checks if we’ve run out of tokens to parse. peek() returns the current token we have yet to consume and previous() returns the most recently consumed token. The latter makes it easier to use match() and then access the just-matched token.

That’s most of the parsing infrastructure we need. Where were we? Right, so if we are inside the while loop in equality(), then the parser knows it found a != or == operator and must be parsing an equality expression.

It grabs the token that was matched for the operator so we can track which kind of binary expression this is. Then it calls comparison() again to parse the right-hand operand. It combines the operator and the two operands into a new Expr.Binary syntax tree node, and then loops around. Each time, it stores the expression back in the same expr local variable. As it zips through a sequence of equality expressions, that creates a left-associative nested tree of binary operator nodes.

The syntax tree created by parsing 'a == b == c == d == e'

The parser falls out of the loop once it hits a token that’s not an equality operator. Finally, it returns the expression. Note that if it doesn’t encounter a single equality operator, then it never enters the loop. In that case, the equality() method effectively calls and returns comparison(). In that way, this method matches an equality operator or anything of higher precedence.

Moving on to the next rule…

comparison  addition ( ( ">" | ">=" | "<" | "<=" ) addition )* ;

Translated to Java:

add after equality()
  private Expr comparison() {
    Expr expr = addition();

      Token operator = previous();
      Expr right = addition();
      expr = new Expr.Binary(expr, operator, right);

    return expr;

The grammar rule is virtually identical to equality and so is the corresponding code. The only differences are the token types for the operators we match, and the method we call for the operands, now addition() instead of comparison(). The remaining two binary operator rules follow the same pattern:

add after comparison()
  private Expr addition() {
    Expr expr = multiplication();

    while (match(MINUS, PLUS)) {
      Token operator = previous();
      Expr right = multiplication();
      expr = new Expr.Binary(expr, operator, right);

    return expr;

  private Expr multiplication() {
    Expr expr = unary();

    while (match(SLASH, STAR)) {
      Token operator = previous();
      Expr right = unary();
      expr = new Expr.Binary(expr, operator, right);

    return expr;

That’s all of the binary operators, parsed with the correct precedence and associativity. We’re crawling up the precedence hierarchy and now we’ve reached the unary operators:

unary  ( "!" | "-" ) unary
      | primary ;

The code for this is a little different:

add after multiplication()
  private Expr unary() {
    if (match(BANG, MINUS)) {
      Token operator = previous();
      Expr right = unary();
      return new Expr.Unary(operator, right);

    return primary();

Again, we look at the current token to see how to parse. If it’s a ! or -, we must have a unary expression. In that case, we grab the token, and then recursively call unary() again to the parse the operand. Wrap that all up in a unary expression syntax tree and we’re done.

Otherwise, we must have reached the highest level of precedence, primary expressions.

primary  NUMBER | STRING | "false" | "true" | "nil"
        | "(" expression ")" ;

Most of the cases for the rule are single terminals, so it’s pretty straightforward:

add after unary()

private Expr primary() { if (match(FALSE)) return new Expr.Literal(false); if (match(TRUE)) return new Expr.Literal(true); if (match(NIL)) return new Expr.Literal(null); if (match(NUMBER, STRING)) { return new Expr.Literal(previous().literal); } if (match(LEFT_PAREN)) { Expr expr = expression(); consume(RIGHT_PAREN, "Expect ')' after expression."); return new Expr.Grouping(expr); } }

The interesting branch is the one for handling parentheses. After we match an opening ( and parse the expression inside it, we must find a ) token. If we don’t, that’s an error.

6 . 3 Syntax Errors

A parser really has two jobs:

  1. Given a valid sequence of tokens, produce a corresponding syntax tree.

  2. Given an invalid sequence of tokens, detect any errors and tell the user about their mistakes.

Don’t underestimate how important the second job is! In modern IDEs and editors, the parser is constantly reparsing code — often while the user is still editing it — in order to syntax highlight and support things like auto-complete. That means it will encounter code in incomplete, half-wrong states all the time.

When the user doesn’t realize the syntax is wrong, it is up to the parser to help guide them back onto the right path. The way it reports errors is a large part of your language’s user interface. Good syntax error handling is hard. By definition, the code isn’t in a well-defined state, so there’s no infallible way to know what the user meant to write. The parser can’t read your mind.

There are a couple of hard requirements for when the parser runs into a syntax error:

Those are the table stakes if you want to get in the parser game at all, but you really want to raise the ante beyond that. A decent parser should:

The last two points are in tension. We want to report as many separate errors as we can, but we don’t want to report ones that are merely side effects of an earlier one.

The way a parser responds to an error and keeps going to look for later errors is called “error recovery”. It was a hot research topic in the 60s. Back then, you’d hand a stack of punch cards to the secretary and come back the next day to see if the compiler succeeded. With an iteration loop that slow, you really wanted to find every single error in your code in one pass.

Today, when parsers complete before you’ve even finished typing, it’s less of an issue. Simple, fast error recovery is fine.

6 . 3 . 1 Panic mode error recovery

Of all the recovery techniques devised in yesteryear, the one that best stood the test of time is called — somewhat alarmingly — “panic mode”. As soon as the parser detects an error, it enters panic mode. It knows at least one token doesn’t make sense given its current state in the middle of some stack of grammar productions.

Before it can get back to parsing, it needs to get its state and the sequence of forthcoming tokens aligned such that the next token does match the rule being parsed. This process is called synchronization.

To do that, we select some rule in the grammar that will mark the synchronization point. The parser fixes its parsing state by jumping out of any nested productions until it gets back to that rule. Then it synchronizes the token stream by discarding tokens until it reaches one that can appear at that point in the rule.

Any additional real syntax errors hiding in those discarded tokens aren’t reported, but it also means that any mistaken cascaded errors that are side effects of the initial error aren’t falsely reported either, which is a decent trade-off.

The traditional place in the grammar to synchronize is between statements. We don’t have those yet, so we won’t actually synchronize in this chapter, but we’ll get the machinery in place for later.

6 . 3 . 2 Entering panic mode

Back before we went on this side trek about error recovery, we were writing the the code to parse a parenthesized expression. After parsing the expression, it looks for the closing ) by calling consume(). Here, finally, is that method:

add after match()
  private Token consume(TokenType type, String message) {
    if (check(type)) return advance();

    throw error(peek(), message);

It’s similar to match() in that it checks to see if the next token is of the expected type. If so, it consumes it and everything is groovy. If some other token is there, then we’ve hit an error. We report it by calling this:

add after previous()
  private ParseError error(Token token, String message) {
    Lox.error(token, message);
    return new ParseError();

First, that shows the error to the user by calling:

add after report()
  static void error(Token token, String message) {
    if (token.type == TokenType.EOF) {
      report(token.line, " at end", message);
    } else {
      report(token.line, " at '" + token.lexeme + "'", message);

This reports an error at a given token. It shows the token’s location and the token itself. This will come in handy later since we use tokens throughout the interpreter to track locations in code.

After this is called, the user knows about the syntax error, but what does the parser do next? Back in error(), it creates and returns a ParseError, an instance of:

class Parser {
in class Parser
  private static class ParseError extends RuntimeException {}

  private final List<Token> tokens;

This is a simple sentinel class we use to unwind the parser. The error() method returns it instead of throwing because we want to let the caller decide whether to unwind or not.

Some parse errors occur in places where the parser isn’t likely to get into a weird state and we don’t need to synchronize. In those places, we simply report the error and keep on truckin’. For example, Lox limits the number of arguments you can pass to a function. If you pass too many, the parser needs to report that error, but it can and should simply keep on parsing the extra arguments instead of freaking out and going into panic mode.

In our case, though, the syntax error is nasty enough that we want to panic and synchronize. Discarding tokens is pretty easy, but how do we synchronize the parser’s own state?

6 . 3 . 3 Synchronizing a recursive descent parser

With recursive descent, the parser’s state — which rules it is in the middle of recognizing — is not stored explicitly in fields. Instead, we use Java’s own callstack to track what the parser is doing. Each rule in the process of being parsed is a callframe on the stack. In order to reset that state, we need to clear out those callframes.

The natural way to do that in Java is exceptions. When we want to synchronize, we throw that ParseError object. Higher up in the method for the grammar rule we are synchronizing to, we’ll catch it. Since we are synchronizing on statement boundaries, we’ll catch the exception there. After the exception is caught, the parser is in the right state. All that’s left is to synchronize the tokens.

We want to discard tokens until we’re right at the beginning of the next statement. That boundary is pretty easy to spot — it’s one of the main reasons we picked it. After a semicolon, we’re probably finished with a statement. Most statements start with a keyword — for, if, return, var, etc. When the next token is any of those, we’re probably about to start a statement.

This method encapsulates that logic:

add after error()
  private void synchronize() {

    while (!isAtEnd()) {
      if (previous().type == SEMICOLON) return;

      switch (peek().type) {
        case CLASS:
        case FUN:
        case VAR:
        case FOR:
        case IF:
        case WHILE:
        case PRINT:
        case RETURN:


It discards tokens until it thinks it found a statement boundary. After catching a ParseError, we’ll call this and then we are hopefully back in sync. When it works well, we have discarded tokens that would have likely caused cascaded errors anyway and now we can parse the rest of the file starting at the next statement.

Alas, we don’t get to see this method in action, since we don’t have statements yet. We’ll get to that in a couple of chapters. For now, if an error occurs, we’ll panic and unwind all the way to the top and stop parsing. Since we can only parse a single expression anyway, that’s no big loss.

6 . 4 Wiring up the Parser

We are mostly done parsing expressions now. There is one other place where we need to add a little error handling. As the parser descends through the parsing methods for each grammar rule, it eventually hits primary(). If none of the cases in there match, it means we are sitting on a token that can’t start an expression. We need to handle that error too:

    if (match(LEFT_PAREN)) {
      Expr expr = expression();
      consume(RIGHT_PAREN, "Expect ')' after expression.");
      return new Expr.Grouping(expr);
in primary()

throw error(peek(), "Expect expression.");

With that, all that remains in the parser is to define an initial method to kick it off. It’s called, naturally enough, parse():

add after Parser()
  Expr parse() {
    try {
      return expression();
    } catch (ParseError error) {
      return null;

We’ll revisit this method later when we add statements to the language. For now, it parses a single expression and returns it. We also have some temporary code to exit out of panic mode. Syntax error recovery is the parser’s job, so we don’t want the ParseError exception to escape into the rest of the interpreter.

When a syntax error does occur, this method returns null. That’s OK. The parser promises not to crash or hang on invalid syntax, but it doesn’t promise to return a usable syntax tree if an error is found. As soon as the parser reports an error, hadError gets set, and subsequent phases are skipped.

Finally, we can hook up our brand new parser to the main Lox class and try it out. We still don’t have an interpreter so, for now, we’ll parse to a syntax tree and then use the AstPrinter class from the last chapter to display it.

Delete the old code to print the scanned tokens and replace it with this:

    List<Token> tokens = scanner.scanTokens();
in run()
replace 5 lines
    Parser parser = new Parser(tokens);
    Expr expression = parser.parse();

    // Stop if there was a syntax error.
    if (hadError) return;

    System.out.println(new AstPrinter().print(expression));

Congratulations, you have crossed the threshold! That really is all there is to hand-writing a parser. We’ll extend the grammar in later chapters with assignment, statements, and other stuff, but none of that is any more complex than the binary operators we tackled here.

Fire up the interpreter and type in some expressions. See how it handles precedence and associativity correctly? Not bad for less than 200 lines of code.


  1. In C, a block is a statement form that allows you to pack a series of statements where a single one is expected. The comma operator is an analogous syntax for expressions. A comma-separated series of expressions can be given where a single expression is expected (except inside a function call’s argument list). At runtime, the comma operator evaluates the left operand and discards the result. Then it evaluates and returns the right operand.

    Add support for comma expressions. Give them the same precedence and associativity as in C. Write the grammar, and then implement the necessary parsing code.

  2. Likewise, add support for the C-style conditional or “ternary” operator ?:. What precedence level is allowed between the ? and :? Is the whole operator left-associative or right-associative?

  3. Add error productions to handle each binary operator appearing without a left-hand operand. In other words, detect a binary operator appearing at the beginning of an expression. Report that as an error, but also parse and discard a right-hand operand with the appropriate precedence.

Design Note: Logic Versus History

Let’s say we decide to add bitwise & and | operators to Lox. Where should we put them in the precedence hierarchy? C — and most languages that follow in C’s footsteps — place them below ==. This is widely considered a mistake because it means common operations like testing a flag require parentheses:

if (flags & FLAG_MASK == SOME_FLAG) { ... } // Wrong.
if ((flags & FLAG_MASK) == SOME_FLAG) { ... } // Right.

Should we fix this for Lox and put bitwise operators higher up the precedence table than C does? There are two strategies we can take.

You almost never want to use the result of an == expression as the operand to a bitwise operator. By making bitwise bind tighter, users don’t need to parenthesize as often. So if we do that, and users assume the precedence is chose logically to minimize parentheses, they’re likely to infer it correctly.

This kind of internal consistency makes the language easier to learn because there are fewer edge cases and exceptions users have to stumble into and then correct. That’s good, because before users can use our language, they have to load all of that syntax and semantics into their heads. A simpler, more rational language makes sense.

But, for many users there is an even faster shortcut to getting our language’s ideas into their wetware — use concepts they already know. Many newcomers to our language will be coming from some other language or languages. If our language uses some of the same syntax or semantics as those, there is much less for the user to learn (and unlearn).

This is particularly helpful with syntax. You may not remember it well today, but way back when you learned your very first programming language, code probably looked alien and unapproachable. Only through painstaking effort did you learn to read and accept it. If you design a novel syntax for your new language, you force users to start that process all over again.

Taking advantage of what users already know is one of the most powerful tools you can use to ease adoption of your language. It’s almost impossible to underestimate how useful this is. But it faces you with a nasty problem: What happens when the thing the users all know kind of sucks? C’s bitwise operator precedence is a mistake that doesn’t make sense. But it’s a familiar mistake that millions have already gotten used to and learned to live with.

Do you stay true to your language’s own internal logic and ignore history? Do you start from a blank slate and first principles? Or do you weave your language into the rich tapestry of programming history and give your users a leg up by starting from something they already know?

There is no perfect answer here, only trade-offs. You and I are obviously biased towards liking novel languages, so our natural inclination is to burn the history books and start our own story.

In practice, it’s often better to make the most of what users already know. Getting them to come to your language requires a big leap. The smaller you can make that chasm, the more people will be willing to cross it. But you can’t always stick to history, or your language won’t have anything new and compelling to get people to want to jump over.