Type systems (Due November 3)

Due Thursday, November 3, 2022

Due Thursday, November 3, 2022

(A printable version of this homework, with some loss of formatting, is available in PDF format.)


Even if you spend your whole career using only scripting languages, at some point you’ll be expected to use a language with a type system. (Even languages that have never had type systems, like PHP and JavaScript, are getting them now.) You’re already aware of type systems in C and C++, and you’ll likely encounter them in other languages such as Java, C#, Swift, Go, Rust, and so on. This assignment will help you learn about type systems and polymorphism. You will understand what a type checker does, and you will be able to translate formal type-system rules into code for a type checker.1 You will add typed primitives to an interpreter. And you will write a couple of explicitly typed, polymorphic functions. When you complete the assignment, you’ll be pretty clear about how polymorphism works in languages like Java and Scala, and you might understand why many Go programmers really wish they had it too!

This homework is due on a Thursday


If you have not done so already, clone the book code:

  git clone homework.cs.tufts.edu:/comp/105/build-prove-compare

If you already have a clone, there might be updates, so run git pull.

You will modify two interpreters: build-prove-compare/bare/tuscheme/tuscheme.sml and build-prove-compare/bare/timpcore/timpcore.sml. You will compile your work with, e.g.,

  mosmlc -o timpcore -toplevel -I /comp/105/lib timpcore.sml
  mosmlc -o tuscheme -toplevel -I /comp/105/lib tuscheme.sml

Dire warnings

Your modified timpcore.sml and tuscheme.sml must compile using mosmlc without errors or warnings.

Your modified timpcore.sml and tuscheme.sml must pass sml-lint with no complaints:

  sml-lint timpcore.sml tuscheme.sml

As in the ML homework, you must not use the functions null, hd, and tl. Use pattern matching.

You must not use the ML forms #1 and #2. (These syntactic forms are manifestations of bad design, trying to masquerade as functions.) If you can’t use pattern matching, use the fst and snd functions that are included with the interpreter’s source code. (Heuristic: It’s safe to pass fst or snd to map. Otherwise, avoid them.

Your typed-funs.scm must load into tuscheme without warnings or errors, as in

  tuscheme -q < typed-funs.scm

Reading comprehension

Before starting the programming problems, answer the reading-comprehension questions for this module, which you will find online. It is also OK to alternate between reading-comprehension questions and related homework questions.

All the homework problems

Problems to do by yourself (25 percent)

On your own, please work exercise 4 on page 400 of Build, Prove, and Compare and problem TD described below.

4. Adding lists to the theory of Typed Impcore. Do exercise 4 on page 400 of Build, Prove, and Compare. The exercise requires you to design new syntax and to write type rules for lists.

Your typing rules must be deterministic. This means that in any given typing environment, any given expression has at most one type, and the type must be computable by a function that is given the abstract syntax and the typing environment as inputs.

Related reading:

  • Study the new abstract syntax for arrays in section 6.3.2, which starts on page 352. Be sure you understand that you are seeing new syntactic forms, not functions.

  • Each new form in code chunk 354b comes with a typing rule, which can be found in section 6.3.3, which starts on page 355. As long as you keep in mind the differences between lists and arrays, this section will help you imagine the sorts of rules you will need to write for lists.

  • For another example of new forms and corresponding rules, study the sum-introduction forms left and right in section 6.4 near page 358.

  • Finally, for help classifying rules, see the sidebar on “Formation, introduction, and elimination” on page 356.

Hint: This exercise is more difficult than it first appears. I encourage you to scrutinize the lecture notes for similar cases, and to remember that you have to be able to type check every expression at compile time. I recommend that you do pair exercise 18 first. It will give you a better feel for monomorphic type systems.

Here are some things to watch out for:

  • It’s easy to conflate syntax, types, and values. In this respect, doing theory is significantly harder than doing implementation, because there’s no friendly compiler to tell you that you have a type clash among exp, tyex, and value.

  • It’s especially easy to get confused about cons. You need to create a new syntax for cons. This syntax needs to be different from the PAIR constructor that is what cons evaluates to.

  • Here’s a good mental test case: it should be possible to write a recursive reverse function, and if ns is a list of integers, then (car (reverse ns)) is an expression that should have type int. Even if list ns is empty.

  • The empty list presents a challenge. Typed Impcore is monomorphic, which implies that any given piece of syntax has at most one type. But you want to allow for empty lists of different types. The easy way out is to design your syntax so that you have many different expressions, of different types, that all evaluate to empty lists. The most common mistake is to design a syntax that requires nondeterminism to compute the type of any term involving the empty list. But the problem requires a deterministic type system, because deterministic type systems are much easier to implement.

    You might consider whether similar difficulties arise with other kinds of data structures or whether lists are somehow unique.

    You might consider what happens in C when you try to do something clever with a pointer of type void *, and to think of how C can address this issue using expression syntax only (that is, without resorting to a definition form.)

  • You might want to see what happens to an ML program when you try to type-check operations on empty and nonempty lists. For this exercise to be helpful, you have to understand the phase distinction between a type error and a run-time error. For example, hd 3 results in a type error, but hd [] is well-typed—and results in a run-time error.

TD. Polymorphic functions in Typed uScheme. To hold your solution, create a file typed-funs.scm. Implement, in Typed μScheme, fully typed versions of these two functions:

  • Function drop from the Scheme homework, problem B, which drops a given number of elements from the front of a list

  • Function takewhile, from exercise 31 on page 187, which takes frontal elements that satisfy a given predicate

The problem has four parts:

  1. Write, in a check-type, the polymorphic type you expect drop to have.

  2. Write a definition of drop.

  3. Write, in a check-type, the polymorphic type you expect takewhile to have.

  4. Write a definition of takewhile.

If you are not able to write implementations of drop and takewhile with the proper types, you may get partial credit by commenting out the check-type forms in parts (a) and (c).

Related reading: Read section 6.6.3 on quantified types. Look especially at the definitions of list2, list3, length, and revapp. If you are not yet confident, go to section Q.6 in supplemental chapter Q and study the definitions of append, filter, and map. (Supplemental chapter Q is in the book’s Supplement, which is available from https://www.cs.tufts.edu/comp/105/supplement.pdf.

Problems you can work on with a partner (75 percent)

Complete exercise 18 on page 403, exercise 19 on page 404, and Exercises T and A described below. You may work by yourself or with a partner. Most students prefer to work with a partner.

18. Type-checking arrays in Typed Impcore. Do exercise 18 on page 403 of Build, Prove, and Compare. Remember that your ML code must compile without errors or warnings, and it must be accepted without comment by sml-lint. Our model solution to this problem is 21 lines of ML.

To test your checker, try using some check-function-type in a Typed Impcore test file. I test my own code using this two-stage process:

  • For each array operation to be tested, define two functions in Typed Impcore: one that does the operation on an array of Booleans, and another on an array of integers.

  • Unit test the functions with the check-function-type form.

Related reading:

  • Study Lesson 5 (“Program design with typing rules”) of Seven Lessons in Program Design. Understand the model for implementing each form of judgment as an ML function. Understand the step-by-step procedure for implementing each rule.

  • In Programming Languages: Build, Prove, and Compare, understand Table 6.2 on page 347. Identify what functions are available to you to call and what functions you will have to add code to.

  • Study section 6.2.1, which starts on page 347. Understand the structure of function typeof, which takes three explicit typing environments, and internal function ty, which has access to those environments even though it takes only one parameter. Study the cases for SET, IFX, EQ, and PRINT. Develop an idea how typing rules and code are related.

  • See how the ARRAYTY value constructor is defined in chunk 340c. An ML value constructed with ARRAYTY represents an array type in Typed Impcore. When you need to recognize an array type, you will pattern match using ARRAYTY. When you need to construct an array type, you will apply ARRAYTY to another ML value of type ty.

  • Understand the typing rules in section 6.3.3, which starts on page 355.

  • For a broader view of how Typed Impcore is extended with arrays, study section 6.3, which starts on page 352.

19. Type checking Typed uScheme. Do exercise 19 on page 404 of Build, Prove, and Compare: write a type checker for Typed uScheme. You will submit a modified interpreter and a file containing regression tests. Don’t worry about the quality of your error messages, but do remember that your ML code must compile without errors or warnings, and it must be accepted without comment by sml-lint.

Follow the step-by-step instructions listed below under the heading “How to build a type checker,” which tells you how to build both the type checker and the regression tests.

Avoid this common mistake: Every possible syntactic form (which is every form except the literal-expression form) should be regression tested with at least one check-type-error test. The most common mistake is to forget these tests.

Our model type checker is about 120 lines of ML. It is very similar to the type checker for Typed Impcore that appears in the book. The code could have been a little shorter, but we wanted detailed error messages.

Related reading:

  • Revisit Lesson 5 (“Program design with typing rules”) of Seven Lessons in Program Design. Understand the model for implementing each form of judgment as an ML function. Understand the step-by-step procedure for implementing each rule.

  • In Programming Languages: Build, Prove, and Compare, understand Table 6.5 on page 376.2 Identify what functions are available to you to call and what functions you will write. Functions asType, eqType, and instantiate are written for you, and they are frequently overlooked.

  • Study section 6.6.5, which starts on page 370—it gives the typing rules for expressions and definitions. You will implement each of these rules.

  • Section 6.6.6 contains a long song and dance about type equivalence, starting on page 378. You do not need to understand any of the song and dance—you will get the important aspects later in the term—but you do need to understand functions eqType and eqTypes well enough to know how to use them.

  • In section 6.6.7, which starts on page 380, there is even more song and dance, about substitution and instantiation. To implement your type checker successfully, you need to know only how to use functions freetyvarsGamma and instantiate.

  • In section 6.6.10, which starts on page 387, you need to know how to use function asType, which is defined on page 389.

  • Study the instructions “How to build a type checker” below.

T. Unit tests for type checkers. Create a file type-tests.scm, and in that file, write three unit tests for Typed μScheme type checkers. Each test must use either check-type or check-type-error. If you wish, your file may include val bindings or val-rec bindings of names used in the tests. Your file must load and pass all tests using the reference implementation of Typed μScheme:

  tuscheme -q < type-tests.scm

If you submit more than three tests, we will use only the first three.

Here is a complete example type-tests.scm file, with five tests:

  (check-type cons (forall ('a) ('a (list 'a) -> (list 'a))))
  (check-type (@ car int) ((list int) -> int))
     (type-lambda ['a] (lambda ([x : 'a]) x))
     (forall ('a) ('a -> 'a)))
  (check-type-error (+ 1 #t))                        ; extra example
  (check-type-error (lambda ([x : int]) (cons x x))) ; another extra example

You may, if you wish, submit any of these example tests, provided you attribute them properly (that is, you identify them as coming from this homework). But your tests will be evaluated on how well they find bugs in the type checkers everyone writes—so new tests are more likely to earn high grades.

Related reading: To be able to write check-type and check-type-error tests, you need to know the concrete syntax for unit-test and type-exp, which is shown in Figure 6.3 on page 362. Notice that the check-type-error form can accept any true definition, not just an expression.

A. Polymorphic array primitives for Typed μScheme. The only way to add arrays to Typed Impcore is to modify the type checker. In Type μScheme, we can do better: A great advantage of a polymorphic type system is that a language can be extended without touching its abstract syntax, its values, its type checker, or its evaluator. You will add arrays to Typed μScheme without changing any of these parts.

Extend Typed μScheme with an array type constructor and the polymorphic values Array.make, Array.at, Array.put, and Array.size. The contracts of the functions are as follows:

  • Array.make takes as argument a nonnegative integer n and a value v, and it creates an array of n slots, each initialized with v.

  • Array.size takes an array and returns the number of slots in the array.

  • Array.at is the array-indexing operation; it takes an array and an index, and it returns the value stored at the given index.

  • Array.put is the array-update operation; it takes an array, an index, and a value, and it stores the value at the given index.

If n is negative in Array.make, it causes a checked run-time error, as does indexing out of bounds (including negative indices). These errors are run-time errors, not type errors.

The exercise has three parts:

  1. What is the kind of the type constructor array? Add it to the initial Δ for Typed μScheme.

  2. What are the types of Array.make, Array.at, Array.put, and Array.size? (These types are polymorphic.)

  3. Edit the interpreter’s source code to add the array primitives the initial Γ and ρ of Typed μScheme.

All you are doing is adding new primitives. There is no change to the type checker or to any existing code!

For part (c), the interpreter source code includes some functions that you will find useful:

(* val makeArray : int * value -> value *)
fun makeArray (n, v) = ARRAY (Array.tabulate (n, (fn _ => v)))

(* val arrayLength : value array -> value *)
fun arrayLength a = NUM (Array.length a)

(* val arrayAt : value array * int -> value *)
fun arrayAt (a, i) = 
  Array.sub (a, i) handle Subscript => raise RuntimeError "array subscript out of bounds"

(* val arrayAtPut : value array * int * value -> unit *)
fun arrayAtPut (a, i, v) = 
  Array.update (a, i, v) handle Subscript => raise RuntimeError "array subscript out of bounds"

You will use these ML functions to implement the primitive Typed μScheme functions. Each primitive function has its own type in Typed μScheme, but to implement each Typed μScheme primitive, you must supply an ML function of type value list -> value.

To match an ML value into an array, you’ll use the ARRAY value constructor, which is a secret: it’s in the code but not the book. Consider code like this:

(fn ARRAY a => ... code using a ...
  | _ => raise BugInTypeChecking "should have had an array here")

If you emulate the implementations of existing primitives like cdr or the pattern matches in arithOp, which is used to implement + and *, and cdr, you’ll be fine. Those implementations are found in the online Supplement to the textbook (https://www.cs.tufts.edu/comp/105/supplement.pdf). Look at page S400 in Appendix Q or at the higher-order functions used to implement the Typed Impcore primitives, on page S389.

Parts (a) and (b) ask you to write a kind and a type. The answers will appear in your code, but so we can find them, please also put the answers in your README file. Even if the code isn’t perfect, you’ll get partial credit for a good kind and good types.

Hint: You will modify code in builds the initial basis. The code appears in section 6.6.10, “Other building blocks of a type checker.” On page 391, your definitions of Array.make, Array.size, Array.at, and Array.put can go next to primitives null?, cons, car, and cdr.

My solution to this problem, which takes advantages of the binaryOp and unaryOp functions already in the interpreter, is 12 lines of ML.

Related reading: Read “Primitive type constructors of Typed μScheme” in section 6.6.10, which starts on page 390 of Build, Prove, and Compare. Focus on polymorphic primitives, such as null?, cons, car, and cdr in code chunk 391c.

Function Array.put needs to return unit. You can emulate the implementation of the print primitive, which also returns unit. The print primitive is found in the Supplement on page S400 (chunk S400c).

What to submit and how to submit it

Even if you decide to work without a partner, you’ll submit individual work and pair work separately.

Submitting individual work

Using script submit105-typesys-solo, please submit

Submit early and often!

Submitting pair work

For your joint work with your partner, one of you should use script submit105-typesys-pair to submit these files:

Only one partner submits.

How your work will be evaluated

We will evaluate the functional correctness of your code by extensive testing.

We will evaluate your regression tests by looking at coverage: a syntactic form is well covered if there is a check-type test for the form and if there is also at least one check-type-error test for every way the form can go wrong.

We will evaluate your unit-test cases by using them to look for bugs in other people’s code. The more bugs your tests find, the better they are.

We will evaluate the structure and organization of your Typed μScheme code using the same criteria as used in previous homework assignments. We will evaluate the structure and organization of your ML code using similar criteria for naming and documentation. For indentation and layout, we’ll look for conformance to the Style Guide for Standard ML Programmers, within the constraints imposed by the code from the book.

Techniques and advice

How to run internal Unit tests

Many students prefer to include internal Unit tests for their type checkers. If you include such tests, here’s how you should run them:

  1. Compile your interpreter using something like the following:

      mosmlc -o a.out -toplevel -I /comp/105/lib timpcore.sml
      mosmlc -o a.out -toplevel -I /comp/105/lib tuscheme.sml
  2. Run the unit tests from the Unix command line using

      ./a.out -q < /dev/null

How to print information when debugging

Within each interpreter, you can use ML functions print, println, eprint, and eprintln.3 Each of these functions expects a single string, and they write to standard output and standard error, respectively. To produce strings, you can use internal functions expString, typeString, defString, and intString.

The most common use case is with predefined function app. Here’s an example:

  let ...
      val _ = 
        app eprint [ "In IF, true branch ", expString e2, " has type "
                   , typeString tau2, " and false branch ", expString e3
                   , " has type ", typeString tau3, "\n"
  in  ...

Here’s some generic advice for writing any of the type-checking code, but especially the array primitives you will add to Typed μScheme:

  1. Compile early. You could use this command:

    mosmlc -I /comp/105/lib -o tuscheme tuscheme.sml
  2. Compile insanely often.
  3. Compile from within your editor, and use an editor that can jump straight to the location of the first error. With Vim, use :make, and with Emacs, use M-x compile.
  4. Come up with examples in Typed μScheme.
  5. Figure out how those examples are represented in ML.
  6. Keep in mind the distinction between the term language (values of array type, values of function type, values of list type) and the type language (array types, function types, list types).
  7. If you’re talking about a thing in the term language, you should be able to give its type.
  8. If you’re talking about a thing in the type language, you should be able to give its kind.

How to regression-test a typing rule

Using the checklist below, you’ll build your typechecker one rule at a time. And after you implement each rule, you’ll need to write a small suite of regression tests. Each suite can be written by examining the rule:

  1. To write regression tests, you’ll need to work with the transformed version of the rule. (You’ll have transformed the rule already while implementing it.) The transformation works like this: If the same type appears more than once above the line, rewrite the rule so that each appearance gets its own subscript, and the appearances are required to be equivalent. Do the same if a particular type (say bool) appears in a judgment above the line.

    For example,

    Δ, Γ ⊢ e1 : bool  Δ, Γ ⊢ e2 : τ  Δ, Γ ⊢ e3 : τ

    Δ, Γ ⊢ IF(e1, e2, e3) : τ


    Δ, Γ ⊢ e1 : τ1  τ1 ≡ bool  Δ, Γ ⊢ e2 : τ2  Δ, Γ ⊢ e3 : τ3  τ2 ≡ τ3

    Δ, Γ ⊢ IF(e1, e2, e3) : τ2

  2. In the transformed rule, examine each judgment above the line. Write a test case that invalidates the judgment. The major judgments that can be invalidated are as follows:

    • Δ, Γ ⊢ e : τ is invalidated by providing an expression e that doesn’t typecheck.

    • τ ≡ τ is invalidated by providing expressions of two different types τ and τ.

    • x ∈ domΓ is invalidated by providing a name x that isn’t defined.

    • Γ(x) = τ can’t be invalidated, but it is always accompanied by x ∈ domΓ, so you can invalidate that instead.

    • Δ ⊢ τ : :* is invalidated by providing a type that is either nonsense (like (bool bool)) or does not have kind * (like list). (This judgment shows up in the lambda and @ forms (lambda and tyapply.)

    • α ∉ ftv(Γ) is invalidated by writing nested type-lambda forms that have a formal type parameter in common.

  3. You will also want at least one test case in which everything is well typed, so that you can be sure that the type of the expression below the line is what you expect.

As an example, the if rule might be tested as follows:

  • To invalidate Δ, Γ ⊢ e1 : τ1, supply an ill-typed condition, as in

    (check-type-error (if (+ 1 #t) 1 0))
  • To invalidate τ1 ≡ bool, supply a non-Boolean condition, as in

    (check-type-error (if 1 1 0))
  • To invalidate τ2 ≡ τ3, supply alternatives of different types, as in

    (check-type-error (if #t 1 #t))
  • To invalidate Δ, Γ ⊢ e2 : τ2 and Δ, Γ ⊢ e3 : τ3, supply two more test cases.

  • To validate the type of the if expression itself (the type below the line), supply a well-typed term with a known type, as in

    (check-principal-type (if #t 1 0) int)

How to build a type checker

Building a type checker is the first CS 105 exercise of significant scope. You must approach it systematically. Do not copy and paste the Typed Impcore code into Typed μScheme. Copying and pasting would be a grave strategic error. You will be much better off adding a brand new type checker to the tuscheme.sml interpreter, one step at a time.

Build and run the type checker in small, bite-sized pieces (just like the lectures). If you try to write the whole thing before you run any of it, you will be miserable. Make the types in the interpreter work for you. (Use the technique shown in the lecture given on Monday, October 17; you can refresh your memory from the notes or the slides.) Start small and implement one rule at a time. For each rule, use the techniques explained in Lesson 5 (“Program design with typing rules”) of Seven Lessons in Program Design. To know what rules to implement in what order, follow these steps:

  1. The initial basis contains code for predefined functions that you will not be able to typecheck until your work is complete. Your first step should therefore be to disable those functions. I suggest that you find the line in the source code that corresponds to the binding of value fundefs in code chunk S394a in the book’s Supplement:

    val fundefs   =
    (* predefined {\tuscheme} functions, as strings (generated by a script) *)

    Replace the line val fundefs = with these two lines:

    val predefined_included = false
    val fundefs = if not predefined_included then [] else

    Verify that your modified interpreter compiles with mosmlc.

  2. Start writing function typeof. I recommend defining an internal function ty, just as in the type checker for Typed Impcore. Create the first draft of ty by writing a clausal definition that has one case for each syntactic form of Typed μScheme. On the right-hand side of each clause, raise the LeftAsExercise exception.

    Verify that your modified interpreter compiles with mosmlc.

  3. Write a function literal that computes the type of a literal value. Start with just numbers, Booleans, and symbols—you can add types for list literals later.

    Verify that your modified interpreter compiles with mosmlc.

  4. Write the case for typeof/ty that handles LITERAL expressions—it should call literal.

  5. Create a test file regression.scm containing a comment and three unit tests:

    ;; step 5
    (check-type 3 int)
    (check-type #t bool)
    (check-type 'hello sym)

    Verify that your modified interpreter compiles with mosmlc.

    Verify that your interpreter correctly typechecks the literals used in the tests above. Run

    ./tuscheme -q < regression.scm

    You must remember the ./ in ./tuscheme, or otherwise you will be testing code from the book, not your own code.

    If you are working on a departmental server, you can try the command

  6. Write the case for typeof that handles IF-expressions. Add regression tests for a few IF-expressions that have different types. Also add tests for some IF-expressions that are ill-typed.

    • Add the comment ;; step 6 to your regression.scm file.

    • Add some check-type unit tests for if to your regression.scm file.

    • Add some check-type-error unit tests for if to your regression.scm file.

    • Verify that your interpreter compiles and passes all its unit tests. If something goes wrong with a unit test, make sure the unit test is OK—test it by running /comp/105/bin/tuscheme -q < regression.scm.

  7. Implement the VAR rule. Add regression tests that check the types of some primitive functions. Be sure to include at least one check-type-error test.

    Please don’t catch the NotFound exception. Just let it pass through to its natural handler. If you catch it, the autograder will not be able to grade your code.

    Verify that your interpreter compiles and passes all its regression tests.

  8. Now turn your attention to function typdef. (It can be found in the source code right next to typeof.) Function typdef takes a true definition, a kind environment, and a typing environment, and it returns a new typing environment and a string.

    • The new typing environment contains a binding for whatever name is defined.

    • The string shows the type of whatever name is defined, which you get by applying function typeString to the type.

    Write four clauses for typdef, each to raise LeftAsExercise. There should be one clause each for VAL, VALREC, EXP, and DEFINE.

    Verify that your interpreter compiles and passes all its regression tests.

  9. Continuing work with typdef, implement the VAL rule for definitions. Then the EXP rule.

    Add a “step 9” comment and a couple of val bindings to your regression-test file, along with check-type and check-type-error tests that use those bindings.

    Verify that your interpreter compiles and passes all its regression tests.

  10. Return to typeof. Implement the rule for function application. Add regression tests that apply functions. Include both check-type and check-type-error tests. You should be able to apply some primitive arithmetic and comparison functions.

    Verify that your interpreter compiles and passes all its regression tests.

  11. Implement LET binding. Make sure your implementation matches the corresponding typing rule. Be careful with your contexts. Add both check-type and check-type-error tests.

    Verify that your interpreter compiles and passes all its regression tests.

  12. Once you’ve got LET working, LAMBDA should be quite similar.

    Add suitable regression tests, including both check-type and check-type-error tests, and verify that your interpreter compiles and passes its regression tests.

  13. Knock off SET, WHILE, and BEGIN.

    Add suitable regression tests, including both check-type and check-type-error tests, and verify that your interpreter compiles and passes its regression tests.

  14. There are a couple of different ways to handle LETSTAR. As usual, the simplest way is to treat it as syntactic sugar for nested LETs. Implement type checking for LETSTAR.

    Add suitable regression tests, including both check-type and check-type-error tests, and verify that your interpreter compiles and passes its regression tests.

  15. Implement the LETREC rule. Don’t overlook the side condition: every right-hand side must be a LAMBDA expression.

    Add suitable regression tests, including both check-type and check-type-error tests, and verify that your interpreter compiles and passes its regression tests.

  16. Go back to typdef, and knock off the definition forms VALREC and DEFINE. (Remember that DEFINE is syntactic sugar for VALREC.) As in LETREC, the right-hand side of VALREC must be a LAMBDA expression.

    Add val-rec and define definitions to your regression-test file, and add regression tests for the names you define. Include both check-type and check-type-error tests.

    Verify that your interpreter compiles and passes all its regression tests.

    Your typdef is now complete.

  17. Return to typeof and implement TYAPPLY and TYLAMBDA. Save these cases for after the last class lecture on the topic. (Those are the only parts that have to wait until the last lecture; you can have your entire type checker, except for those two constructs, finished before the last class.)

    Add suitable regression tests, including both check-type and check-type-error tests, and verify that your interpreter compiles and passes its regression tests.

  18. Complete your literal function by making sure it handles list literals formed with PAIR or NIL. The book has three rules for list literals; follow them rigorously, and your code will work with no problems.

    Add suitable regression tests, including both check-type and check-type-error tests, and verify that your interpreter compiles and passes its regression tests.

    Your typeof function is now complete.

    Your entire type checker is now complete.

  19. Return to the code you modified in step 1. Bind

    val predefined_included = true

    Verify that your interpreter compiles and that it can typecheck the predefined functions of Typed μScheme.

Avoid common mistakes

In exercise 4, it’s a common mistake to try to create a type system that prevents programmers from applying car or cdr to the empty list. Don’t do this! Such a type system is too complicated for CS 105. As in ML, taking car or cdr of the empty list should be a well-typed term that causes an error at run time.

In exercise 4, it’s common to write a nondeterministic type system by accident. The rules, typing context, and syntax have to work together to determine the type of every expression. But you’re free to choose whatever rules, context, and syntax you want.

In exercise 4, it’s inexplicably common to forget to write a typing rule for the construct that tests to see if a list is empty.

There are already interpreters on your PATH with the same name as the interpreters you are working on. So remember to get the version from your current working directory, as in

  ledit ./timpcore

Just plain timpcore will get the system version.

In exercise 19, it’s a common mistake to write only check-type tests, forgetting the check-type-error tests. To earn full credit for your regression tests, you must use check-type-error.

ML equality is broken! The = sign gives equality of representation, which may or may not be what you want. For example, in Typed uScheme, you must use the eqType function to see if two types are equal. If you use built-in equality, you will get wrong answers.

It’s a common mistake to call ListPair.foldr and ListPair.foldl when what you really meant was ListPair.foldrEq or ListPair.foldlEq.

It’s not a common mistake, but it can be devastating: when you’re writing the type of a polymorphic primitive function, write the type variable with an ASCII quote mark, as in 'a, not with a Unicode right quote mark, as in ’a.

It’s not a common mistake, but don’t define any new exceptions. And don’t raise any exceptions besides TypeError. (If you don’t finish, you might also raise LeftAsExercise.)

What is and is not hard or time-consuming

To help you plan your work on this assignment, I provide some opinions about where I think the difficulties lie.

  1. You will not necessarily develop a deep understanding for how the rules work—that is, why these particular rules are good ones. That question is related to the so-called “type-soundness theorem,” which is a proof that the type system predicts what happens when we run the code. Unfortunately, proofs of type soundness are relatively deep, and such proofs are beyond the scope of CS 105.

  2. Some students discover this table very late in the game, and when they realize how much of the code they’ve written was already done for them in the book, they are sad.

  3. Function print is predefined; the others are implemented in the interpreter itself.

  4. In the lingo of the field, ML is the “metalanguage” and μScheme is the “object language.” “Metalanguage” is what “ML” stands for.