Reading 9: Mutability & Immutability

Let’s start with a simple method that sums the integers in a list:

/** @return the sum of the numbers in the list */
public static int sum(List<Integer> list) {
    int sum = 0;
    for (int x : list)
        sum += x;
    return sum;
}

Suppose we also need a method that sums the absolute values. Following good DRY practice ( Don’t Repeat Yourself ), the implementer writes a method that uses sum() :

/** @return the sum of the absolute values of the numbers in the list */
public static int sumAbsolute(List<Integer> list) {
    // let's reuse sum(), because DRY, so first we take absolute values
    for (int i = 0; i < list.size(); ++i)
        list.set(i, Math.abs(list.get(i)));
    return sum(list);
}

Notice that this method does its job by mutating the list directly . It seemed sensible to the implementer, because it’s more efficient to reuse the existing list. If the list is millions of items long, then you’re saving the time and memory of generating a new million-item list of absolute values. So the implementer has two very good reasons for this design: DRY, and performance.

But the resulting behavior will be very surprising to anybody who uses it! For example:

// meanwhile, somewhere else in the code...
public static void main(String[] args) {
    // ...
    List<Integer> myData = Arrays.asList(-5, -3, -2);
    System.out.println(sumAbsolute(myData));
    System.out.println(sum(myData));
}

What will this code print? Will it be 10 followed by -10? Or something else?

Let’s think about the key points here:

• Safe from bugs? In this example, it’s easy to blame the implementer of sum­Absolute() for going beyond what its spec allowed. But really, passing mutable objects around is a latent bug . It’s just waiting for some programmer to inadvertently mutate that list, often with very good intentions like reuse or performance, but resulting in a bug that may be very hard to track down.

• Easy to understand? When reading main() , what would you assume about sum() and sum­Absolute() ? Is it clearly visible to the reader that myData gets changed by one of them?

We just saw an example where passing a mutable object to a function caused problems. What about returning a mutable object?

Let’s consider Date , one of the built-in Java classes. Date happens to be a mutable type. Suppose we write a method that determines the first day of spring:

/** @return the first day of spring this year */
public static Date startOfSpring() {
    return askGroundhog();
}

Here we’re using the well-known Groundhog algorithm for calculating when spring starts (Harold Ramis, Bill Murray, et al. Groundhog Day , 1993).

Clients start using this method, for example to plan their big parties:

// somewhere else in the code...
public static void partyPlanning() {
    Date partyDate = startOfSpring();
    // ...
}

All the code works and people are happy. Now, independently, two things happen. First, the implementer of startOfSpring() realizes that the groundhog is starting to get annoyed from being constantly asked when spring will start. So the code is rewritten to ask the groundhog at most once, and then cache the groundhog’s answer for future calls:

/** @return the first day of spring this year */
public static Date startOfSpring() {
    if (groundhogAnswer == null) groundhogAnswer = askGroundhog();
    return groundhogAnswer;
}
private static Date groundhogAnswer = null;

(Aside: note the use of a private static variable for the cached answer. Would you consider this a global variable, or not?)

Second, one of the clients of startOfSpring() decides that the actual first day of spring is too cold for the party, so the party will be exactly a month later instead:

// somewhere else in the code...
public static void partyPlanning() {
    // let's have a party one month after spring starts!
    Date partyDate = startOfSpring();
    partyDate.setMonth(partyDate.getMonth() + 1);
    // ... uh-oh. what just happened?
}

(Aside: this code also has a latent bug in the way it adds a month. Why? What does it implicitly assume about when spring starts?)

What happens when these two decisions interact? Even worse, think about who will first discover this bug — will it be startOfSpring() ? Will it be partyPlanning() ? Or will it be some completely innocent third piece of code that also calls startOfSpring() ?

Key points:

• Safe from bugs? Again we had a latent bug that reared its ugly head.

• Ready for change? Obviously the mutation of the date object is a change, but that’s not the kind of change we’re talking about when we say “ready for change.” Instead, the question is whether the code of the program can be easily changed without rewriting a lot of it or introducing bugs. Here we had two apparently independent changes, by different programmers, that interacted to produce a bad bug.

In both of these examples — the List<Integer> and the Date — the problems would have been completely avoided if the list and the date had been immutable types. The bugs would have been impossible by design.

In fact, you should never use Date ! Use one of the classes from package java.time : LocalDateTime , Instant , etc. All guarantee in their specifications that they are immutable .

This example also illustrates why using mutable objects can actually be bad for performance. The simplest solution to this bug, which avoids changing any of the specifications or method signatures, is for startOfSpring() to always return a copy of the groundhog’s answer:

    return new Date(groundhogAnswer.getTime());

This pattern is defensive copying , and we’ll see much more of it when we talk about abstract data types. The defensive copy means partyPlanning() can freely stomp all over the returned date without affecting startOfSpring() ’s cached date. But defensive copying forces startOfSpring() to do extra work and use extra space for every client — even if 99% of the clients never mutate the date it returns. We may end up with lots of copies of the first day of spring throughout memory. If we used an immutable type instead, then different parts of the program could safely share the same values in memory, so less copying and less memory space is required. Immutability can be more efficient than mutability, because immutable types never need to be defensively copied.

To better understand how an iterator works, here’s a simple implementation of an iterator for ArrayList<String> :

/**
 * A MyIterator is a mutable object that iterates over
 * the elements of an ArrayList<String>, from first to last.
 * This is just an example to show how an iterator works.
 * In practice, you should use the ArrayList's own iterator
 * object, returned by its iterator() method.
 */
public class MyIterator {

    private final ArrayList<String> list;
    private int index;
    // list[index] is the next element that will be returned
    //   by next()
    // index == list.size() means no more elements to return

    /**
     * Make an iterator.
     * @param list list to iterate over
     */
    public MyIterator(ArrayList<String> list) {
        this.list = list;
        this.index = 0;
    }

    /**
     * Test whether the iterator has more elements to return.
     * @return true if next() will return another element,
     *         false if all elements have been returned
     */
    public boolean hasNext() {
        return index < list.size();
    }

    /**
     * Get the next element of the list.
     * Requires: hasNext() returns true.
     * Modifies: this iterator to advance it to the element 
     *           following the returned element.
     * @return next element of the list
     */
    public String next() {
        final String element = list.get(index);
        ++index;
        return element;
    }
}

MyIterator makes use of a few Java language features that are different from the classes we’ve been writing up to this point. Make sure you’ve read the linked Java Tutorial sections so that you understand them:

Instance variables , also called fields in Java. Instance variables differ from method parameters and local variables; the instance variables are stored in the object instance and persist for longer than a method call. What are the instance variables of My­Iterator ?

A constructor , which makes a new object instance and initializes its instance variables. Where is the constructor of My­Iterator ?

The static keyword is missing from My­Iterator ’s methods, which means they are instance methods that must be called on an instance of the object, e.g. iter.next() .

The this keyword is used at one point to refer to the instance object , in particular to refer to an instance variable ( this.list ). This was done to disambiguate two different variables named list (an instance variable and a constructor parameter). Most of My­Iterator ’s code refers to instance variables without an explicit this , but this is just a convenient shorthand that Java supports — e.g., index actually means this.index .

private is used for the object’s internal state and internal helper methods, while public indicates methods and constructors that are intended for clients of the class ( access control ).

final is used to indicate which of the object’s internal variables can be reassigned and which can’t. index is allowed to change ( next() updates it as it steps through the list), but list cannot (the iterator has to keep pointing at the same list for its entire life — if you want to iterate through another list, you’re expected to create another iterator object).

Here’s a snapshot diagram showing a typical state for a MyIterator object in action:

Note that we draw the arrow from list with a double line, to indicate that it’s final . That means the arrow can’t change once it’s drawn. But the ArrayList object it points to is mutable — elements can be changed within it — and declaring list as final has no effect on that.

Why do iterators exist? There are many kinds of collection data structures (linked lists, maps, hash tables) with different kinds of internal representations. The iterator concept allows a single uniform way to access them all, so that client code is simpler and the collection implementation can change without changing the client code that iterates over it. Most modern languages (including Python, C#, and Ruby) use the notion of an iterator. It’s an effective design pattern (a well-tested solution to a common design problem). We’ll see many other design patterns as we move through the course.

This is a fundamental issue with mutable data structures. Multiple references to the same mutable object (also called aliases for the object) may mean that multiple places in your program — possibly widely separated — are relying on that object to remain consistent.

To put it in terms of specifications, contracts can’t be enforced in just one place anymore, e.g. between the client of a class and the implementer of a class. Contracts involving mutable objects now depend on the good behavior of everyone who has a reference to the mutable object.

As a symptom of this non-local contract phenomenon, consider the Java collections classes, which are normally documented with very clear contracts on the client and implementer of a class. Try to find where it documents the crucial requirement on the client that we’ve just discovered — that you can’t modify a collection while you’re iterating over it. Who takes responsibility for it? Iterator ? List ? Collection ? Can you find it?

The need to reason about global properties like this make it much harder to understand, and be confident in the correctness of, programs with mutable data structures. We still have to do it — for performance and convenience — but we pay a big cost in bug safety for doing so.

Mutable objects make the contracts between clients and implementers more complicated, and reduce the freedom of the client and implementer to change. In other words, using objects that are allowed to change makes the code harder to change. Here’s an example to illustrate the point.

The crux of our example will be the specification for this method, which looks up a username in MIT’s database and returns the user’s 9-digit identifier:

/**
 * @param username username of person to look up
 * @return the 9-digit MIT identifier for username.
 * @throws NoSuchUserException if nobody with username is in MIT's database
 */
public static char[] getMitId(String username) throws NoSuchUserException {        
    // ... look up username in MIT's database and return the 9-digit ID
}

A reasonable specification. Now suppose we have a client using this method to print out a user’s identifier:

char[] id = getMitId("bitdiddle");
System.out.println(id);

Now both the client and the implementor separately decide to make a change. The client is worried about the user’s privacy, and decides to obscure the first 5 digits of the id:

char[] id = getMitId("bitdiddle");
for (int i = 0; i < 5; ++i) {
    id[i] = '*';
}
System.out.println(id);

The implementer is worried about the speed and load on the database, so the implementer introduces a cache that remembers usernames that have been looked up:

private static Map<String, char[]> cache = new HashMap<String, char[]>();

public static char[] getMitId(String username) throws NoSuchUserException {        
    // see if it's in the cache already
    if (cache.containsKey(username)) {
        return cache.get(username);
    }

    // ... look up username in MIT's database ...

    // store it in the cache for future lookups
    cache.put(username, id);
    return id;
}

These two changes have created a subtle bug. When the client looks up "bitdiddle" and gets back a char array, now both the client and the implementer’s cache are pointing to the same char array. The array is aliased. That means that the client’s obscuring code is actually overwriting the identifier in the cache, so future calls to getMidId("bitdiddle") will not return the full 9-digit number, like “928432033”, but instead the obscured version “*****2033”.

Sharing a mutable object complicates a contract . If this contract failure went to software engineering court, it would be contentious. Who’s to blame here? Was the client obliged not to modify the object it got back? Was the implementer obliged not to hold on to the object that it returned?

Here’s one way we could have clarified the spec:

public static char[] getMitId(String username) throws NoSuchUserException 
  requires: nothing
  effects: returns an array containing the 9-digit MIT identifier of username,
             or throws NoSuchUserException if nobody with username is in MIT’s
             database. Caller may never modify the returned array.

This is a bad way to do it . The problem with this approach is that it means the contract has to be in force for the entire rest of the program. It’s a lifetime contract! The other contracts we wrote were much narrower in scope; you could think about the precondition just before the call was made, and the postcondition just after, and you didn’t have to reason about what would happen for the rest of time.

Here’s a spec with a similar problem:

public static char[] getMitId(String username) throws NoSuchUserException 
  requires: nothing
  effects: returns a new array containing the 9-digit MIT identifier of username,
             or throws NoSuchUserException if nobody with username is in MIT’s
             database.

This doesn’t entirely fix the problem either . This spec at least says that the array has to be fresh. But does it keep the implementer from holding an alias to that new array? Does it keep the implementer from changing that array or reusing it in the future for something else?

Here’s a much better spec:

public static String getMitId(String username) throws NoSuchUserException 
  requires: nothing
  effects: returns the 9-digit MIT identifier of username, or throws
             NoSuchUserException if nobody with username is in MIT’s database.

The immutable String return value provides a guarantee that the client and the implementer will never step on each other the way they could with char arrays. It doesn’t depend on a programmer reading the spec comment carefully. String is immutable . Not only that, but this approach (unlike the previous one) gives the implementer the freedom to introduce a cache — a performance improvement.