From returning null values to overusing getters and setters, there are idioms that we as Java developers are accustom to making, even when unwarranted. While they may be appropriate in some occasions, they are usually forces of habit or fallbacks that we make to get the system working. In this article, we will go through three things that are common among Java developers, both novice and advanced, and explore how they can get us into trouble. It should be noted that these are not hard-and-fast rules that should always be adhered to, regardless of the circumstances. At times, there may be a good reason to use these patterns to solve a problem, but on the whole, they should be used a lot less than they are now. To start us off, we will begin with one of the most prolific, but double-edged keywords in Java: Null.

1. Returning Null

Null has been the best friend and worst enemy of developers for decades and null in Java is no different. In high-performance applications, null can be a solid means of reducing the number of objects and signaling that a method does not have a value to return. In contrast to throwing an exception, which has to capture the entire stack trace when it is created, null serves as a quick and low-overhead way to signal clients that no value can be obtained.

Outside the context of high-performance systems, null can wreak havoc in an application by creating more tedious checks for null return values and causing NullPointerException s when dereferencing a null object. In most applications, nulls are returned for three primary reasons: (1) to denote no elements could be found for a list, (2) to signal that no valid value could be found, even if an error did not occur, or (3) to denote a special case return value.

Barring any performance reasons, each of these cases has a much better solution which does not use null and force developers to handle null cases. Whatsmore, clients of these methods are not left scratching their heads wondering if the method will return a null in some edge case. In each case, we will devise a cleaner approach that does not involve returning a null value.

No Elements

When returning lists or other collections, it can be common to see a null collection returned in order to signal that elements for that collection could not be found. For example, we could create a service that manages users in a database that resembles the following (some method and class definitions have been left out for brevity):

public class UserService { public List<User> getUsers() { User[] usersFromDb = getUsersFromDatabase(); if (usersFromDb == null) { // No users found in database return null; } else { return Arrays.asList(usersFromDb); } } } UserServer service = new UserService(); List<Users> users = service.getUsers(); if (users != null) { for (User user: users) { System.out.println("User found: " + user.getName()); } }





Since we have elected to return a null value in the case of no users, we are forcing our client to handle this case before iterating over the list of users. If instead, we returned an empty list to denote no users were found, the client can remove the null check entirely and loop through the users as normal. If there are no users, the loop will be skipped implicitly without having to manually handle that case; in essence, looping through the list of users functions as we intend for both an empty and populated list without having to manually handle one case or the other:

public class UserService { public List<User> getUsers() { User[] usersFromDb = getUsersFromDatabase(); if (usersFromDb == null) { // No users found in database return Collections.emptyList(); } else { return Arrays.asList(usersFromDb); } } } UserServer service = new UserService(); List<Users> users = service.getUsers(); for (User user: users) { System.out.println("User found: " + user.getName()); }





In the case above, we have elected to return an immutable, empty list. This is an acceptable solution, so long as we document that the list is immutable and should not be modified (doing so may throw an exception). If the list must be mutable, we can return an empty, mutable list, as in the following example:

public List<User> getUsers() { User[] usersFromDb = getUsersFromDatabase(); if (usersFromDb == null) { // No users found in database return new ArrayList<>(); // A mutable list } else { return Arrays.asList(usersFromDb); } }





In general, the following rule should be adhered to when signaling that no elements could be found:

Return an empty collection (or list, set, queue, etc.) to denote that no elements can be found

Doing so not only reduces the special-case handling that clients must perform, but it also reduces the inconsistencies in our interface (i.e. we return a list object sometimes and not others).

Optional Value

Many times, null values are returned when we wish to inform a client that an optional value is not present, but no error has occurred. For example, getting a parameter from a web address. In some cases, the parameter may be present, but in other cases, it may not. The lack of this parameter does not necessarily denote an error, but rather, it denotes that the user did not want the functionality that is included when the parameter is provided (such as sorting). We can handle this by returning null if no parameter is present or the value of the parameter if one is supplied (some methods have been removed for brevity):

public class UserListUrl { private final String url; public UserListUrl(String url) { this.url = url; } public String getSortingValue() { if (urlContainsSortParameter(url)) { return extractSortParameter(url); } else { return null; } } } UserService userService = new UserService(); UserListUrl url = new UserListUrl("http://localhost/api/v2/users"); String sortingParam = url.getSortingValue(); if (sortingParam != null) { UserSorter sorter = UserSorter.fromParameter(sortingParam); return userService.getUsers(sorter); } else { return userService.getUsers(); }





When no parameter is supplied, a null is returned and a client must handle this case, but nowhere in the signature of the getSortingValue method does it state that the sorting value is optional. For us to know that this method is optional and may return a null if no parameter is present, we would have to read the documentation associated with the method (if any were provided).

Instead, we can make the optionality explicit returning an Optional object. As we will see, the client still has to handle the case when no parameter is present, but now that requirement is made explicit. Whatsmore, the Optional class provides more mechanisms to handle a missing parameter than a simple null check. For example, we can simply check for the presence of the parameter using the query method (a state-testing method) provided by Optional :

public class UserListUrl { private final String url; public UserListUrl(String url) { this.url = url; } public Optional<String> getSortingValue() { if (urlContainsSortParameter(url)) { return Optional.of(extractSortParameter(url)); } else { return Optional.empty(); } } } UserService userService = new UserService(); UserListUrl url = new UserListUrl("http://localhost/api/v2/users"); Optional<String> sortingParam = url.getSortingValue(); if (sortingParam.isPresent()) { UserSorter sorter = UserSorter.fromParameter(sortingParam.get()); return userService.getUsers(sorter); } else { return userService.getUsers(); }





This is nearly identical to that of the null-check case, but we have made the optionality of the parameter explicit (i.e. the client cannot access the parameter without calling get() , which will throw a NoSuchElementException if the optional is empty). If we were not interested in returning the list of users based on the optional parameter in the web address, but rather, consuming the parameter in some manner, we could use the ifPresentOrElse method to do so:

sortingParam.ifPresentOrElse( param -> System.out.println("Parameter is :" + param), () -> System.out.println("No parameter supplied.") );





This greatly reduces the noise required for null checking. If we wished to disregard the parameter if no parameter is supplied, we could do so using the ifPresent method:

sortingParam.ifPresent(param -> System.out.println("Parameter is :" + param));





In either case, using an Optional object, rather than returning null, explicitly forces clients to handle the case that a return value may not be present and provides many more avenues for handling this optional value. Taking this into account, we can devise the following rule:

If a return value is optional, ensure clients handle this case by returning an Optional that contains a value if one is found and is empty if no value can be found

Special-Case Value

The last common use case is that of a special case, where a normal value cannot be obtained and a client should handle a corner case different than the others. For example, suppose we have a command factory from which clients periodically request commands to complete. If no command is ready to be completed, the client should wait 1 second before asking again. We can accomplish this by returning a null command, which clients must handle, as illustrated in the example below (some methods are not shown for brevity):

public interface Command { public void execute(); } public class ReadCommand implements Command { @Override public void execute() { System.out.println("Read"); } } public class WriteCommand implements Command { @Override public void execute() { System.out.println("Write"); } } public class CommandFactory { public Command getCommand() { if (shouldRead()) { return new ReadCommand(); } else if (shouldWrite()) { return new WriteCommand(); } else { return null; } } } CommandFactory factory = new CommandFactory(); while (true) { Command command = factory.getCommand(); if (command != null) { command.execute(); } else { Thread.sleep(1000); } }





Since the CommandFactory can return null commands, clients are obligated to check if the command received is null and if it is, sleep for 1 second. This creates a set of conditional logic that clients must handle on their own. We can reduce this overhead by creating a null-object (sometimes called a special-case object). A null-object encapsulates the logic that would have been executed in the null scenario (namely, sleeping for 1 second) into an object that is returned in the null case. For our command example, this means creating a SleepCommand that sleeps when executed:

public class SleepCommand implements Command { @Override public void execute() { Thread.sleep(1000); } } public class CommandFactory { public Command getCommand() { if (shouldRead()) { return new ReadCommand(); } else if (shouldWrite()) { return new WriteCommand(); } else { return new SleepCommand(); } } } CommandFactory factory = new CommandFactory(); while (true) { Command command = factory.getCommand(); command.execute(); }





As with the case of returning empty collections, creating a null-object allows clients to implicitly handle special cases as if they were the normal case. This is not always possible, though; there may be instances where the decision for dealing with a special case must be made by the client. This can be handled by allowing the client to supply a default value, as is done with the Optional class. In the case of Optional , clients can obtain the contained value or a default using the orElse method:

UserListUrl url = new UserListUrl("http://localhost/api/v2/users"); Optional<String> sortingParam = url.getSortingValue(); String sort = sortingParam.orElse("ASC");





If there is a supplied sorting parameter (i.e. if the Optional contains a value), this value will be returned. If no value exists, "ASC" will be returned by default. The Optional class also allows a client to create a default value when needed, in case the default creation process is expensive (i.e. the default will be created only when needed):

UserListUrl url = new UserListUrl("http://localhost/api/v2/users"); Optional<String> sortingParam = url.getSortingValue(); String sort = sortingParam.orElseGet(() -> { // Expensive computation });





Using a combination of null-objects and default values, we can devise the following rule:

When possible, handle null cases with a null-object or allow clients to supply a default value

2. Defaulting to Functional Programming

Since streams and lambdas were introduced in Java Development Kit (JDK) 8, there has been a push to migrate towards functional programming, and rightly so. Before lambdas and streams, performing simple functional tasks were cumbersome and resulted in severely unreadable code. For example, filtering a collection in the traditional style resulted in code that resembled the following:

public class Foo { private final int value; public Foo(int value) { this.value = value; } public int getValue() { return value; } } Iterator<Foo> iterator = foos.iterator(); while(iterator.hasNext()) { if (iterator.next().getValue() > 10) { iterator.remove(); } }





While this code is compact, it does not tell us in an obvious way that we are trying to remove elements of a collection if some criterion is satisfied. Instead, it tells us that we are iterating over a collection while there are more elements in the collection and removing each element if its value is greater than 10 (we can surmise that filtering is occurring, but it obscured in the verbosity of the code). We can shrink this logic down to one statement using functional programming:

foos.removeIf(foo -> foo.getValue() > 10);





Not only is this statement much more concise than its iterative alternative, it also tells us exactly what it is trying to do. We can even make it more readable if we name the predicate and pass it to the removeIf method:

Predicate<Foo> valueGreaterThan10 = foo -> foo.getValue() > 10; foos.removeIf(valueGreaterThan10);





The final line of this snippet reads like a sentence in English, informing us exactly of what the statement is doing. With code that looks so compact and readable, it is tempting to try and use functional programming in every situation where iteration is required, but this is a naive philosophy. Not every situation lends itself to functional programming. For example, if we tried to print the cross product of the set of suits and ranks in a deck of cards (every combination of suits and ranks), we could create the following (see Effective Java, 3rd Edition for a more detailed listing of this example):

public static enum Suit { CLUB, DIAMOND, HEART, SPADE; } public static enum Rank { ONE, TWO, THREE, FOUR, FIVE, SIX, SEVEN, EIGHT, NINE, TEN, JACK, QUEEN, KING; } Collection<Suit> suits = EnumSet.allOf(Suit.class); Collection<Rank> ranks = EnumSet.allOf(Rank.class); suits.stream() .forEach(suit -> { ranks.stream().forEach(rank -> System.out.println("Suit: " + suit + ", rank: " + rank)); });





While this is not over-complicated to read, it is not the most straightforward implementation we could devise. It is pretty clear that we are trying to force streams into a realm where traditional iteration is much more favorable. If we used traditional iteration, we could have simplified the cross product of suits and ranks to the following:

for (Suit suit: suits) { for (Rank rank: ranks) { System.out.println("Suit: " + suit + ", rank: " + rank); } }





This style, although much less flashy, is much more straightforward. We can quickly see that we are attempting to iterate over each suit and rank and pair each rank with each suit. The tediousness of functional programming becomes much more acute the larger the stream expression becomes. Take for example the following code snippet created by Joshua Bloch in Effective Java, 3rd Edition (pp. 205, Item 45) to find all the anagrams over a specified length contained in a dictionary at the path supplied by the user:

public class Anagrams { public static void main(String[] args) throws IOException { Path dictionary = Paths.get(args[0]); int minGroupSize = Integer.parseInt(args[1]); try (Stream<String> words = Files.lines(dictionary)) { words.collect( groupingBy(word -> word.chars().sorted() .collect(StringBuilder::new, (sb, c) -> sb.append((char) c), StringBuilder::append).toString())) .values().stream() .filter(group -> group.size() >= minGroupSize) .map(group -> group.size() + ": " + group) .forEach(System.out::println); } } }





Even the most seasoned stream adherents would probably balk at this implementation. It is unclear as to the intention of the code and would take a decent amount of thinking to uncover what the above stream manipulations are trying to accomplish. This does not mean that streams are complicated or that they are too wordy, but they are not always the best choice. As we saw above, using the removeIf reduced a complicated group of statements into a single, easily-comprehensible statement. Therefore, we should not try to replace every instance of traditional iteration with streams or even lambdas. Instead, we should abide by the following rule when deciding whether to functional programming or use the traditional route:

Functional programming and traditional iteration both have their benefits and disadvantages: Use whichever results in the simplest and most readable code

Although it may be tempting to use the flashiest, most up-to-date features of Java in every possible scenario, this is not always the best route. Sometimes, the old-school features work best.

3. Creating Indiscriminate Getters and Setters

One of the first things that novice programmers are taught is to encapsulate the data associated with a class in private fields and expose them through public methods. In practice, this results in creating getters to access the private data of a class and setters to modify the private data of a class:

public class Foo { private int value; public void setValue(int value) { this.value = value; } public int getValue() { return value; } }





While this is a great practice for newer programmers to learn, it is not a practice that should go unrefined into intermediate or advanced programming. What normally occurs in practice is that every private field is given a pair of getters and setters, exposing the internals of the class to external entities. This can cause some serious issues, especially if the private fields are mutable. This is not only a problem with setters but even when only a getter is present. Take for example the following class, which exposes its only field using a getter:

public class Bar { private Foo foo; public Bar(Foo foo) { this.foo = foo; } public Foo getFoo() { return foo; } }





This exposure may seem innocuous since we have wisely restricted removed a setter method, but it is far from it. Suppose that another class accesses an object of type Bar and changes the underlying value of Foo without the Bar object knowing:

Foo foo = new Foo(); Bar bar = new Bar(foo); // Another place in the code bar.getFoo().setValue(-1);





In this case, we have changed the underlying value of the Foo object without informing the Bar object. This can cause some serious problems if the value that we provided the Foo object breaks an invariant of the Bar object. For example, if we had an invariant that stated the value of Foo could not be negative, then the above snippet silently breaks this invariant without notifying the Bar object. When the Bar object goes to use the value of its Foo object, things may go south very quickly, especially if the Bar object assumed that the invariant held since it did not expose a setter to directly reassign the Foo object it held. This can even cause failure to a system if data is severely altered, as in the following example of an array being inadvertently exposed:

public class ArrayReader { private String[] array; public String[] getArray() { return array; } public void setArray(String[] array) { this.array = array; } public void read() { for (String e: array) { System.out.println(e); } } } public class Reader { private ArrayReader arrayReader; public Reader(ArrayReader arrayReader) { this.arrayReader = arrayReader; } public ArrayReader getArrayReader() { return arrayReader; } public void read() { arrayReader.read(); } } ArrayReader arrayReader = new ArrayReader(); arrayReader.setArray(new String[] {"hello", "world"}); Reader reader = new Reader(arrayReader); reader.getArrayReader().setArray(null); reader.read();





Executing this code would cause a NullPointerException because the array associated with the ArrayReader object is null when it tries to iterate over the array. What is disturbing about this NullPointerException is that it can occur long after the change to the ArrayReader was made and maybe even in an entirely different context (such as in a different part of the code or maybe even in a different thread), making the task of tracking down the problem very difficult.

The astute reader may also notice that we could have made the private ArrayReader field final since we did not expose a way to reassign it after it has been set through the constructor. Although it might seem that this would make the ArrayReader constant, ensuring that the ArrayReader object we return cannot be changed, this is not the case. Instead, adding final to a field only ensures that the field itself is not reassigned (i.e. we cannot create a setter for that field). It does not stop the state of the object itself from being changed. If we tried to add final to the getter method, this is futile as well, since final modifier on a method only means that the method cannot be overridden by subclasses.

We can even go one step further and defensively copy the ArrayReader object in the constructor of Reader , ensuring that the object that was passed into the object cannot be tampered with after it has been supplied to the Reader object. For example, the following cannot happen:

ArrayReader arrayReader = new ArrayReader(); arrayReader.setArray(new String[] {"hello", "world"}); Reader reader = new Reader(arrayReader); arrayReader.setArray(null); // Change arrayReader after supplying it to Reader reader.read(); // NullPointerException thrown





Even with these three changes (the final modifier on the field, the final modifier on the getter, and the defensive copy of the ArrayReader supplied to the constructor), we still have not solved the problem. The problem is not found in how we are exposing the underlying data of our class, but in the fact that we are doing it in the first place. For us to solve this issue, we have to stop exposing the internal data of our class and instead provide a method to change the underlying data, while still adhering to the class invariants. The following code solves this problem, while at the same time introducing a defensive copy of the supplied ArrayReader and marking the ArrayReader field final, as should be the case since there is no setter:

public class ArrayReader { public static ArrayReader copy(ArrayReader other) { ArrayReader copy = new ArrayReader(); String[] originalArray = other.getArray(); copy.setArray(Arrays.copyOf(originalArray, originalArray.length)); return copy; } // ... Existing class ... } public class Reader { private final ArrayReader arrayReader; public Reader(ArrayReader arrayReader) { this.arrayReader = ArrayReader.copy(arrayReader); } public ArrayReader setArrayReaderArray(String[] array) { arrayReader.setArray(Objects.requireNonNull(array)); } public void read() { arrayReader.read(); } } ArrayReader arrayReader = new ArrayReader(); arrayReader.setArray(new String[] {"hello", "world"}); Reader reader = new Reader(arrayReader); reader.read(); Reader flawedReader = new Reader(arrayReader); flawedReader.setArrayReaderArray(null); // NullPointerException thrown





If we look at the flawed reader, a NullPointerException is still thrown, but it is thrown immediately when the invariant (that a non-null array is used when reading) is broken, not at some later time. This ensures that the invariant fails-fast, which makes debugging and finding the root of the problem much easier.

We can take this principle one step further and state that it is a good idea to make the fields of a class completely inaccessible if there is no pressing need to allow for the state of a class to be changed. For example, we could make the Reader class fully encapsulated by removing any methods that modify its state after creation:

public class Reader { private final ArrayReader arrayReader; public Reader(ArrayReader arrayReader) { this.arrayReader = ArrayReader.copy(arrayReader); } public void read() { arrayReader.read(); } } ArrayReader arrayReader = new ArrayReader(); arrayReader.setArray(new String[] {"hello", "world"}); Reader reader = new Reader(arrayReader); // No changes can be made to the Reader after instantiation reader.read();





Taking this concept to its logical conclusion, it is a good idea to make a class immutable if it is possible. Thus, the state of the object never changes after the object has been instantiated. For example, we can create an immutable Car object as follows:

public class Car { private final String make; private final String model; public Car(String make, String model) { this.make = make; this.model = model; } public String getMake() { return make; } public String getModel() { return model; } }





It is important to note that if the fields of the class are non-primitive, a client can modify the underlying object as we saw above. Thus, immutable objects should return defensive copies of these objects, disallowing clients to modify the internal state of the immutable object. Note, though, that defensive copying can reduce performance since a new object is created each time the getter is called. This issue should not be prematurely optimized (disregarding immutability for the promise of possible performance increases), but it should be noted. The following snippet provides an example of defensive copying for method return values:

public class Transmission { private String type; public static Transmission copy(Transmission other) { Transmission copy = new Transmission(); copy.setType(other.getType); return copy; } public String setType(String type) { this.type = type; } public String getType() { return type; } } public class Car { private final String make; private final String model; private final Transmission transmission; public Car(String make, String model, Transmission transmission) { this.make = make; this.model = model; this.transmission = Transmission.copy(transmission); } public String getMake() { return make; } public String getModel() { return model; } public Transmission getTransmission() { return Transmission.copy(transmission); } }





This leaves us with the following principle:

Make classes immutable, unless there is a pressing need to change the state of a class. All fields of an immutable class should be marked as private and final to ensure that no reassignments are performed on the fields and no indirect access should be provided to the internal state of the fields

Immutability also brings with it some very important advantages, such as the ability of the class to be easily used in a multi-threaded context (i.e. two threads can share the object without fear that one thread will alter the state of the object while the other thread is accessing that state). In general, there are many more instances that we can create immutable classes than we realize at first: Many times, we add getters or setters out of habit.

Conclusion

Many of the applications we create end up working, but in a large number of them, we introduce sneaky problems that tend to creep up at the worst possible times. In some of those cases, we do things out of convenience, or even out of habit, and pay little mind to whether these idioms are practical (or safe) in the context we use them. In this article, we delved into three of the most common of these practices, such null return values, affinity for functional programming, and careless getters and setters, along with some pragmatic alternatives. While the rules in this article should not be taken as absolute, they do provide some insight into the uncommon dangers of common practices and may help in fending off laborious errors in the future.