The purpose of this assignment is to help you get acquainted with pure object-oriented programming. Even simple algorithms tend to be implemented by sending lots of messages back and forth among a cluster of cooperating, communicating objects. The assignment is divided into two parts.

This assignment is unusually time-consuming. Many students have experience in languages called object-oriented, but very few students have experience with the extensive, pervasive inheritance that characterizes idiomatic Smalltalk programs.


The μSmalltalk interpreter is in /comp/105/bin/usmalltalk. Many useful μSmalltalk sources are included the book’s git repository, which you can clone by

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

Sources that can be found in the examples directory includes copies of predefined classes, collection classes, financial history, and other examples from the textbook.

Interactive debugging with μSmalltalk

Smalltalk is a small language with a big initial basis. There are lots of predefined classes and methods. Here are two tools that can help you get oriented and debug your code:

Reading comprehension (10 percent)

These problems will help guide you through the reading. We recommend that you complete them before starting the other problems below. You can download the questions.

  1. Read the first ten pages of chapter 11.

    1. What is a “receiver”? What is an “argument”? What is the difference?

    2. What is the relationship between a message and a protocol?

    3. What is the difference between instance protocol and class protocol?

    4. In the name of a message, what is the significance of a colon or colons?

    You are ready for exercise 9 (collection protocols).

  2. Read Section 11.3.4 on message send and dynamic dispatch. Using the class definitions in that section, message m1 is sent to an object of class C: What method definitions are evaluated in what order? An answer looks something like “method m5 on class H, then method m12 on class E, …”.

  3. Continuing with method dispatch, now study the class method new defined on class List in code chunk 927a. The definition sends message new to super. (Keep in mind: because new is a class method, both super and self stand for the class, not for any instance.)

    1. When class method new is evaluated, what three messages are sent by the method body, in what order?

    2. What does each message send accomplish?

    3. If we changed the body so instead of (new super) it said (new self), what would happen?

  4. Find the implementation of class Number on pages 933 and 934. Now study the implementation of class Fraction pages 936 to 938.

    Message - (minus) is sent to Fraction (/ 1 2) with argument Fraction (/ 1 3). What methods are evaluated in what order? Which class implements -?

    You are getting ready for exercise 30(a).

  5. Read about the Magnitude protocol on pages 894 and 895. Study the implementation of class Magnitude on page 932. Then study the implementations of classes Integer and SmallInteger on pages 934 and 935.

    Message <= is sent to small integer 3 with argument 9. What methods are evaluated in what order? Which class implements <=?

    You are ready for exercise 30(a), and you are ready to implement class Natural (exercise 32).

  6. In section 11.10.1 on page 978, you will find a short definition of an “abstract class.” What do you think is the purpose of an abstract class?

  7. One example of an abstract class is class Number. Look up its definition on page 933. List all the methods that are “subclass responsibility.” These are the methods you must implement in class LargeInteger.

    You are getting ready to implement large integers.

  8. Study the implementation of common methods on classes Magnitude and Number. This question asks you to apply the ideas to LargeInteger: Of the methods listed in the previous comprehension question (subclass responsibilities of Number), which ones can be implemented on class LargeInteger itself, as opposed to one of its concrete subclasses? (None of these methods will require double dispatch, which is the subject of the next comprehension question.)

    You are ready to write a few simple methods for Exercise 33 (large integers).

  9. Read Section 11.6.4 on pages 931 and 932.

    Of the methods listed in comprehension question 7 (subclass responsibilities of Number), list each one that needs to know whether its argument (not the receiver) is a large or small integer, and if large, whether it is positive or negative. These methods will require double dispatch.

    1. List the methods. For example, + is such a method.

    2. For each method, list what method it will dispatch to on its argument if the received is a LargePositiveInteger. For example, method + will dispatch to addLargePositiveIntegerTo:.

    You are ready to implement large integers (Exercise 33).

  10. Read about coercion in section Section 11.4.5 on page 895. Look at the protocol on page 894.

    Explain the roles of the methods asInteger, asFraction, asFloat, and coerce:. If you are unsure, look at the implementations of these methods on class Integer on pages 934 and 935.

    You are ready to implement mixed arithmetic, with coercions, in Exercise 34.

Individual Problems

Working on your own, please solve Exercise 9 on page 986 and Exercise 30(a) on page 991 of Ramsey. These exercises are warm-ups designed to prepare you for the Bignum problems in the pair portion of the assignment.

9. Collection Protocols. Do Exercise 9 on page 986 of Ramsey.

Related reading: Section 11.1, which uses the FinancialHistory class as the running example.

30(a). Interfaces as Abstraction Barriers. Do Exercise 30(a) on page 991 of Ramsey. When the problem says “Arrange the Fraction and Integer classes”, the text means to revise one or both of these classes or define a related class. Think about protocols, not implementation.

Put your solution in file frac-and-int.smt. At minimum, your solution should support addition, subtraction, multiplication, so include at least one unit test for each of these operations.


Related reading:

  • For an overview of the Magnitude class and its relationship to numbers, read the first page of Section 11.4.5, which starts on page 895. Also in that section, read about Integer and Fraction.

  • For the implementation of Integer, read pages 934 and 935. For the time being, you can ignore class SmallInteger.

  • For the implementation of Fraction, read pages 936 to 938. Study the implementation of method +, and observe how it relies on the exposure of representation through private methods num and den.

  • If nothing comes to you, try reading about how we get access to multiple representations in the object-oriented way: Section 11.6.4 on pages 931 and 932. You will need to read this section later anyway.

How big is it? To solve these problems, you shouldn’t need to add or change more than 10 lines of code in total. The optimal solution is no more than a few lines long.

Pair Problems: Bignum arithmetic

For these problems, you may work with a partner. Please solve Exercise 32 on page 991, Exercise 33 on page 994, and Exercise 34 on page 994 of Ramsey, and Exercise T below. You do not need to implement long division.

Sometimes you want to do computations that require more precision than you have available in a machine word. Full Scheme, Smalltalk, and Icon all provide “bignums.” These are integer implementations that automatically expand to as much precision as you need. Because of their dynamic-typing discipline, these languages make the transition transparently—you can’t easily tell when you’re using native machine integers and when you’re using bignums. In this portion of the homework, you will reimplement infinite-precision natural numbers in Smalltalk, use these natural numbers to define infinite-precision integers, and then modify the built-in SmallInteger class so that when more precision is needed, operations seamlessly roll over to infinite precision.

Big picture of the solution

Smalltalk code sends lots of messages back and forth among lots of methods that are defined on different classes. This model shows both the power of Smalltalk—you get a lot of leverage and code reuse—and the weakness of Smalltalk—every algorithm is smeared out over half a dozen methods defined on different classes, making it hard to debug. But this is the object-oriented programming model that lends power not just to Smalltalk but also to Ruby, Objective-C, Swift, Self, JavaScript, and to a lesser extent, Java and C++. To work effectively in any of these languages, one needs the big picture of which class is doing what. A good starting point is the Smalltalk bignums handout

Unit testing bignums in Smalltalk

Like the other bridge languages, μSmalltalk has check-expect. But in Smalltalk, checking for equality is often not useful—because many Smalltalk abstractions are mutable, equality is normally defined as object identity. For example, two lists compare equal only if they are the same list. If they are different lists containing the same elements, then the = method says they are different.

To test equality of bignums in Smalltalk, we will convert each bignum to a list of digits, which we will compare for similarity using the has:to: class method on class Similarity:

(class Similarity Object
  (class-method has:to: (ms ns)
    (locals i n equivalent)
    (set n (size ms))
    (if (!= n (size ns))
        {(set i 1)
         (set equivalent true)
         (while {(and: equivalent {(<= i n)})}
            {(ifTrue:ifFalse: (!= (at: ms i) (at: ns i))
                {(set equivalent false)}
                {(set i (+ i 1))})})

With this class method, we can even compare a list and an array for similarity, successfully. Here’s an example of how it works.

-> (val ns (new List))
List( )
-> (add: ns 1)
-> (add: ns 2)
-> (add: ns 3)
-> ns
List( 1 2 3 )
-> (= ns ns)
-> (= ns #( 1 2 3 ))
-> (has:to: Similarity ns #( 1 2 3 ))

If you want to test the results of arithmetic, your check-expect should send message has:to: to class Similarity and will compare the result with true. You can download class Similarity. If you want to test comparisons, your check-expect can simply refer to true and false as usual.

How to prepare your code for our testing

Many of our tests interact directly with the μSmalltalk interpreter. Our testing infrastructure enters definitions and looks at the responses. To pass our stringent test suites, you must define print methods that render numbers as normal people expect to see them. You cannot simply send decimal to self and print the result—you must print the individual digits, possibly preceded by a minus sign.

Array alert

Smalltalk arrays are numbered from 1, not from 0. It is very annoying that you are stuck with a 1-based array type to implement a 0-based abstraction (polynomials) for class Natural. The book recommends private methods digit: and digit:put:. I recommend that you define these methods, which hide the 1-based nature of the underlying representation:

(method digit: (i)
   (at:ifAbsent: digits (+ i 1) {0}))
(method digit:put: (i d)
   (at:put: digits (+ i 1) d))

Details of all the problems

32. Implementing arbitrary precision natural numbers. Do Exercise 32 on page 991 of Ramsey. Modify the protocol given in the assignment according to these instructions:

The algorithms are the same algorithms you would have used on the sml assignment. And although the book assumes you will represent a natural number using an array, you are free to use a list of digits instead. Just be aware that unlike Standard ML, μSmalltalk has no immutable list abstraction. If you want immutable lists, you will have to simulate them yourself. For example, you could try using the Cons and Nil classes that are already defined, along with the isNil message that is defined on every object.

Please do adapt your code from the sml assignment. Or if you prefer, you may adapt my solutions. Just be sure to attribute the source for whatever code you adapt.

How big is it? My solution for the Natural class, using the array representation and the hints in the book, is over 100 lines of μSmalltalk code.

Related reading:

  • There is a detailed implementation guide in the bignums handout.

  • In a system with abstract data types, binary operations like + and * are easy: you automatically have access to both representations. In a system with objects, not so! To learn how to get access to multiple representations in the object-oriented way, read section 11.6.4 on pages 931 and 932.

  • Class Natural is a subclass of Magnitude. Study the Magnitude protocol in Section 11.4.5. For information about the implementation of Magnitude, which should provide useful ideas about Natural, as well as the “subclass responsibilities,” study the implementation of Magnitude in section 11.6.5 on page 932.1

  • For the interface to a Smalltalk array, study the Collection protocol in Section 11.4.4, which starts on page 884. You have access to the protocol in Figure 11.9, but you are more likely to use the KeyedCollection protocol in Figure 11.10, especially at: and at:put:. Don’t overlook the Arrays section on pages 892 and 893, including its description of the array class methods new: and from:.

  • For list construction, which you will need for the decimal method, look at the List protocol in Section 11.4.4, especially Figure 11.12.

33. Implementing arbitrary precision integers. Do Exercise 33 on page 994 of Ramsey. You need not implement the div: method. But in order to facilitate testing, you must implement a decimal method like the one you implemented on class Natural. An implementation is shown in the bignums handout.

Because you build large integers on top of Natural, you don’t have to think about array or list representations any more. Instead you must focus on dynamic dispatch and on getting information from where it is to where it is needed.

How big is it? My solutions for the large integer classes are 22 lines apiece.

Related reading: This problem is all about dynamic dispatch, including double dispatch. Read Section 11.6.4, which starts on page 931. (You’ll also have a chance to practice double dispatch in recitation.)

34. Modifying SmallInteger so operations that overflow roll over to infinite precision. Do Exercise 34 on page 994 of Ramsey.

You must modify SmallInteger without editing the source code of the μSmalltalk interpreter. To do so, you will redefine class SmallInteger using the idiom on page 995:

     (class SmallInteger SmallInteger
        ... new method definitions ...

This idiom modifies the existing class SmallInteger; it can both change existing methods and define new methods. This code changes the basic arithmetic operations that the system uses internally. If you have bugs in your code, the system will behave erratically. At this point, you must restart your interpreter and fix your bugs. Then use the idiom again.

How big is it? My modifications to the SmallInteger class are about 25 lines.

Related reading: Everything about dispatch and double dispatch still applies. In addition, you need to know how overflow is handled using “exception blocks.”

  • Review the presentation of blocks, especially the parameterless blocks (written with curly braces) in Section 11.4.3, which starts on page 883.

  • A very simple example of an exception block appears above in the recommended implementation of method digit:. Read the description of at:ifAbsent: in the keyed-collection protocol in Figure 11.10 on page 890. Now study the example method:

    (method digit: (i)
       (at:ifAbsent: digits (+ i 1) {0}))

    Any reference out of bounds sends value to the “exception block” {0}, which answers zero.

  • Study the implementation of the at: method in chunk 923d, which uses at:ifAbsent: with an “exception block” that causes a run-time error if value is sent to it.

  • Finally, study the overflow-detecting primitive methods at the top of page 995, and study the implementation of addSmallIntegerTo: in code chunk 995a. That is the technique you must emulate.

T. Testing Bignums. You will write 9 tests for bignums:

Each test will have the same structure:

  1. The test will begin with a summary characterization of the test in at most 60 characters, formatted on a line by itself as follows:

         ; Summary: .........

    The summary must be a simple English phrase that describes the test. Examples might be “Ackermann’s function of (1, 1),” “sequence of powers of 2,” or “combinations of +, *, and - on random numbers.”

  2. Code will compute a result of class Natural, LargePositiveInteger, or LargeNegativeInteger. The code may appear in a method, a class method, a block, or wherever else you find convenient.

  3. The expected result will be written as a literal array, like one of the following:

    #( 1 2 3 9 4 9 )
    #( - 6 5 5 3 6 )
  4. The test itself will send the decimal message to the computed result, then compare the decimal representation with the literal array. Comparison will use class method has:to: on class Similarity.

  5. Finally, the comparison will appear in a check-expect, expecting the result of has:to: to be true.2

Each test must take less than 2 CPU seconds to evaluate.

Here is a complete example:

; Summary: 10 to the tenth power, mixed arithmetic
(class Test10Power Object
  (class-method run: (power)
     [locals n 10-to-the-n]
     (set n 0)
     (set 10-to-the-n 1)
     (whileTrue: {(< n power)}
         {(set n (+ n 1))
          (set 10-to-the-n (* 10 10-to-the-n))})
(check-expect (has:to: Similarity (decimal (run: Test10Power 10))
                                  #( 1 0 0 0 0 0 0 0 0 0 0)) 

Here is another complete example:

; Summary: 20 factorial
(define factorial (n)
  (ifTrue:ifFalse: (strictlyPositive n) 
     {(* n (value factorial (- n 1)))}

(check-expect (has:to: Similarity (decimal (value factorial 20))
                                  #( 2 4 3 2 9 0 2 0 0 8 1 7 6 6 4 0 0 0 0 ))

Related reading: No special reading is recommended for the testing problem. As long as you understand the examples above, that should be enough.

A simple sanity check

As a test, the factorial function has grave limitations:

These properties of factorial make it a poor test of correctness, but they do make it a good initial sanity check. Here, for example, is code that computes and prints factorials:

(class Factorial Object
  (class-method printUpto: (limit) [locals n nfac]
     (set n 1)
     (set nfac 1)
     (whileTrue: {(<= n limit)}
        {(print n) (print #!) (printu 32) (print #=) (printu 32) (println nfac)
         (set n (+ n 1))
         (set nfac (* n nfac))})))

As a sanity check sending (printUpto: Factorial 25) should print the following table of factorials:

     1! = 1
     2! = 2
     3! = 6
     4! = 24
     5! = 120
     6! = 720
     7! = 5040
     8! = 40320
     9! = 362880
    10! = 3628800
    11! = 39916800
    12! = 479001600
    13! = 6227020800
    14! = 87178291200
    15! = 1307674368000
    16! = 20922789888000
    17! = 355687428096000
    18! = 6402373705728000
    19! = 121645100408832000
    20! = 2432902008176640000
    21! = 51090942171709440000
    22! = 1124000727777607680000
    23! = 25852016738884976640000
    24! = 620448401733239439360000
    25! = 15511210043330985984000000

More advice about testing natural numbers

Try testing your class Natural by generating a long, random string of digits, then computing the corresponding number using a combination of addition and multiplication by 10.

If you don’t have multiplication working yet, you can use the following sequence to multiply by 10:

(set p n)       ; p == n
(set p (+ p p)) ; p == 2n
(set p (+ p p)) ; p == 4n
(set p (+ p n)) ; p == 5n
(set p (+ p p)) ; p == 10n

This idea will test only your addition; if you have bugs there, fix them before you go on.

You can write, in μSmalltalk itself, a method that uses the techniques above to convert a sequenceable collection of decimal digits into a natural number.

Once you are confident that addition works, you can test subtraction of natural numbers by generating a long random sequence, then subtracting the same sequence in which all digits except the most significant are replaced by zero.

You can create more ambitious tests of subtraction by generating random natural numbers and using the algebraic law (m + n)−m = n. You can also check to see that unless n is zero, m − (m + n) causes a run-time error on class Natural.

It is harder to test multiplication, but you can at least use repeated addition to test multiplication by small values. The timesRepeat: method is defined on any integer.

You can also easily test multiplication by large powers of 10.

You can use similar techniques to test large integers.

If you want more effective tests of multiplication and so on, compare your results with a working implementation of bignums. The languages Scheme, Icon, and Haskell all provide such implementations. (Be aware that the real Scheme define syntax is slightly different from what we use in uScheme.) We recommend you use ghci on the command line; standard infix syntax works. If you want something more elaborate, use Standard ML of New Jersey (command sml), which has an IntInf module that implements bignums.

Other hints and guidelines

Start early. Seamless arithmetic requires in-depth cooperation among about eight different classes (those you write, plus Magnitude, Number, Integer, and SmallInteger). This kind of cooperation requires aggressive message passing and inheritance, which you are just learning. There is a handout online with suggestions about which methods depend on which other methods and in what order to tackle them.

For your reference, Dave Hanson’s book discusses bignums and bignum algorithms at some length. It should be free online to Tufts students. You can think about borrowing code from Hanson’s implementation (see also his distribution). Be aware though that your assignment differs significantly from his code and unless you have read the relevant portions of the book, you may find the code overwhelming.

If you do emulate Hanson’s code, acknowledge him in your README file.

Avoid common mistakes

Below you will find some common mistakes to avoid.

It is common to overlook class methods. They are a good place to put information that doesn’t change over the life of your program.

It’s not common, but it’s a terrible mistake to try to implement mixed operations by interrogating an object about its class—a so-called “run-time type test.” Run-time type tests destroy behavioral subtyping. If you find yourself wanting to ask an object what its class is, seek help immediately.

It is surprisingly common for students to submit code for the small problems without ever even having run the code or loaded it into an interpreter. If you run even one test case, you will be ahead of the game.

It is too common to submit bignum code without having tested all combinations of methods and arguments. Your best plan is to write a program, in the language if your choice, that loops over operator and both operands and generates at least one test case for every combination. Because μSmalltalk is written using S-expressions, you could consider writing this program in μScheme—but any language will do.

It is relatively common for students’ code to make a false distinction between two flavors of zero. In integer arithmetic, there is only one zero, and it always prints as “0”.

It’s surprisingly common to fail to tag the test summary with the prefix Summary:, or to forget it altogether.

Extra credit

Seamless bignum arithmetic is an accomplishment. But it’s a long way from industrial. The extra-credit problems explore some ideas you would deploy if you wanted everything on a more solid foundation.

Base variations. A key problem in the representation of integers is the choice of the base b. Today’s hardware supports b = 2 and sometimes b = 10, but when we want bignums, the choice of b is hard to make in the general case:

  • If b = 10, then converting to decimal representation is trivial, but storing bignums requires lots of memory.

  • The larger b is, the less memory is required, and the more efficient everything is.

  • If b is a power of 10, converting to decimal is relatively easy and is very efficient. Otherwise, as long as b ≥ 10, conversion requires only short division.

  • If (b-1) * (b-1) fits in a machine word, than you can implement multiplication in high-level languages without difficulty. (Serious implementations pick the largest b such that one digit fits in a machine word, e.g., 264 on modern machines. Unfortunately, to work with such large values of b requires special machine instructions to support “add with carry” and 128-bit multiply, so serious implementations have to be written in assembly language.)

  • If b is a power of 2, bit-shift can be very efficient, but conversion to decimal is expensive. Fast bit-shift can be important in cryptographic and communications applications.

If you want signed integers, there are more choices: signed-magnitude and b’s-complement. Knuth volume 2 is pretty informative about these topics.

For extra credit, try the following variations on your implementation of class Natural:

  1. Implement the class using an internal base b = 10. Measure the time needed to compute the first 50 factorials.

  2. Argue for the largest possible base that is still a power of 10. Change your class to use that base internally. (If you are both careful and clever, you should be able to change only the class method base and not any other code.) Measure the time needed to compute and print the first 50 factorials.

  3. Argue for the largest possible base that is a power of 2. Change your class to use that base internally. Measure the time needed to compute and print the first 50 factorials. Does having fewer digits recoup the higher cost of converting to decimal?

Because Smalltalk hides the representation from clients, a well-behaved client won’t be affected by a change of base. If we wanted, we could take more serious measurements and pick the most efficient representation.

Remember that the private decimal method must return a list of decimal digits, even if base 10 is not what is used in the representation. Suppress leading zeroes unless the value of Natural is itself zero.

Write up your arguments and your measurements in your README file.

Long division. Implement long division for Natural and for large integers. If this changes your argument for the largest possible base, explain how. This article by Per Brinch Hansen describes how to implement long division.

Mixed Comparisons. Make sure comparisons work, even with mixed kinds of integers. So for example, make sure comparisons such as (< 5 (* 1000000 1000000)) produce sensible answers.

Space costs. Instrument your Natural class to keep track of the size of numbers, and measure the space cost of the different bases. Estimate the difference in garbage-collection overhead for computing with the different bases, given a fixed-size heap.

Pi (hard). Use a power series to compute the first 100 digits of pi (the ratio of a circle’s circumference to its diameter). Be sure to cite your sources for the proper series approximation and its convergence properties. Hint: I vaguely remember that there’s a faster convergence for pi over 4. Check with a numerical analyst.

What and how to submit: Individual problems

Submit these files:

Please identify your solutions using conspicuous comments, e.g.,

     ;;;;  Solution to Exercise 9
     (class Array ...

As soon as you have the files listed above, run submit105-small-solo to submit a preliminary version of your work. Keep submitting until your work is complete; we grade only the last submission.

What and how to submit: Pair problems

Submit these files:

As soon as you have the files listed above, run submit105-small-pair to submit a preliminary version of your work. Keep submitting until your work is complete; we grade only the last submission.

How your work will be evaluated

All our usual expections for form, naming, and documentation apply. But in this assignment we will focus on clarity and structure. To start, we want to be able to understand your code.

Exemplary Satisfactory Must improve

• Course staff see no more code than is needed to solve the problem.

• Course staff see how the structure of the code follows from the structure of the problem.

• Course staff see somewhat more code than is needed to solve the problem.

• Course staff can relate the structure of the code to the structure of the problem, but there are parts they don’t understand.

• Course staff roughly twice as much code as is needed to solve the problem.

• Course staff cannot follow the code and relate its structure to the structure of the problem.

Structurally, your code should hide information like the base of natural numbers, and it should use proper method dispatch, not bogus techniques like run-time type checking.
Exemplary Satisfactory Must improve

• The base used for natural numbers appears in exactly one place, and all code that depends on it consults that place.

Or, the base used for natural numbers appears in exactly one place, and code that depends on either consults that place or assumes that the base is some power of 10

• No matter how many bits are used to represent a machine integer, overflow is detected by using appropriate primitive methods, not by comparing against particular integers.

• Code uses method dispatch instead of conditionals.

• Mixed operations on different classes of numbers are implemented using double dispatch.

Or, mixed operations on different classes of numbers are implemented by arranging for the classes to share a common protocol.

Or, mixed operations on different classes of numbers are implemented by arranging for unconditional coercions.

• Code deals with exceptional or unusual conditions by passing a suitable exnBlock or other block.

• Code achieves new functionality by reusing existing methods, e.g., by sending messages to super.

Or, code achieves new functionality by adding new methods to old classes to respond to an existing protocol.

• An object’s behavior is controlled by dispatching (or double dispatching) to an appropriate method of its class.

• The base used for natural numbers appears in exactly one place, but code that depends on it knows what it is, and that code will break if the base is changed in any way.

• Overflow is detected only by assuming the number of bits used to represent a machine integer, but the number of bits is explicit in the code.

• Code contains one avoidable conditional.

• Mixed operations on different classes of integers involve explicit conditionals.

• Code protects itself against exceptional or unusual conditions by using Booleans.

• Code contains methods that appear to have been copied and modified.

• An object’s behavior is influenced by interrogating it to learn something about its class.

• The base used for natural numbers appears in multiple places.

• Overflow is detected only by assuming the number of bits used to represent a machine integer, and the number of bits is implicit in the value of some frightening decimal literal.

• Code contains more than one avoidable conditional.

• Mixed operations on different classes of integers are implemented by interrogating objects about their classes.

• Code copies methods instead of arranging to invoke the originals.

• Code contains case analysis or a conditional that depends on the class of an object.

  1. Note: an object of class Natural is not a Number as Smalltalk understands it. In particular, class Natural does not support methods negated or reciprocal.

  2. In μSmalltalk, truth is true, not #t.