How Functional Programming will (Finally) do Away With the GoF Patterns

A recent article about various ways to implement structural pattern matching in Java has triggered my interest:

The article mentions a Scala example where a tree data structure can be traversed very easily and neatly using Scala’s match keyword, along with using algebraic data types (more specifically, a sum type):

def depth(t: Tree): Int = t match {
  case Empty => 0
  case Leaf(n) => 1
  case Node(l, r) => 1 + max(depth(l), depth(r))

Even if you’re not used to the syntax, it is relatively easy to understand what it does:

  • There’s a function depth that calculates the (maximum) depth of a tree structure
  • It does so by checking if the input argument is empty, a leaf node, or any other node
  • If it is any other node, then it adds 1 to the maximum of the remaining tree, recursively

The elegant thing here is that the Scala type system helps the author of the above code get this right from a formal point of view, by offering formal type checking. The closest we can do in Java as illustrated by the article is this

public static int depth(Tree t) {
  if (t instanceof Empty)
    return 0;
  if (t instanceof Leaf)
    return 1;
  if (t instanceof Node)
    return 1 + max(depth(((Node) t).left), depth(((Node) t).right));
  throw new RuntimeException("Inexhaustive pattern match on Tree.");

But these instanceof checks do smell kind of fishy…

For more details, read the full article here, highly recommended:

How does this compare to the GoF design patterns?

In our object-orientation-brainwashed Java ecosystem (which inherited the OO brainwash from C++), the above instanceof logic would most likely be refactored into an implementation using the visitor pattern from the GoF design patterns book. This refactoring would be done by The Team Architect™ himself, as they are supervising the object oriented quality of your software. The 7 lines of code using instanceof would quickly bloat up to roughly 200 lines of weird interfaces, abstract classes, and cryptic accept() and visit() methods. When in fact, the functional programming approach was so much leaner, even in its imperfect Java instanceof form!

A lot of the GoF design patterns stem from a time when EVERYTHING needed to be an object. Object orientation was the new holy grail, and people even wanted to push objects down into databases. Object databases were invented (luckily, they’re all dead) and the SQL standard was enhanced with ORDBMS features (only really implemented in Oracle, PostgreSQL, and Informix, and maybe some other minor DBs), most of which – also luckily – were never widely adopted.

Since Java 8, finally, we’re starting to recover from the damage that was made in early days of object orientation in the 90s, and we can move back to a more data-centric, functional, immutable programming model where data processing languages like SQL are appreciated rather than avoided, and Java will see more and more of these patterns, hopefully.

If you’re not convinced by the above visitor pattern vs pattern matching example, do read this very interesting series of articles by Mario Fusco:

You will see that with functional programming, many patterns lose their meaning as you’re just starting to pass around functions, making code very simple and easy to understand.

As a wrap up, as Mario presented the content at Voxxed Days Ticino:

Happy functional programming!

The Visitor Pattern Re-visited

The visitor pattern is one of the most overrated and yet underestimated patterns in object-oriented design. Overrated, because it is often chosen too quickly (possibly by an architecture astronaut), and then bloats an otherwise very simple design, when added in the wrong way. Underestimated, because it can be very powerful, if you don’t follow the school-book example. Let’s have a look in detail.

Problem #1: The naming

Its biggest flaw (in my opinion) is its naming itself. The “visitor” pattern. When we google it, we most likely find ourselves on the related Wikipedia article, showing funny images like this one:

Wikipedia Visitor Pattern example

Wikipedia Visitor Pattern example

Right. For the 98% of us thinking in wheels and engines and bodies in their every day software engineering work, this is immediately clear, because we know that the mechanic billing us several 1000$ for mending our car will first visit the wheels, then the engine, before eventually visiting our wallet and accepting our cash. If we’re unfortunate, he’ll also visit our wife while we’re at work, but she’ll never accept, that faithful soul.

But what about the 2% that solve other problems in their worklife? Like when we code complex data structures for E-Banking systems, stock exchange clients, intranet portals, etc. etc. Why not apply a visitor pattern to a truly hierarchical data structure? Like folders and files? (ok, not so complex after all)

OK, so we’ll “visit” folders and every folder is going to let its files “accept” a “visitor” and then we’ll let the visitor “visit” the files, too. What?? The car lets its parts accept the visitor and then let the visitor visit itself? The terms are misleading. They’re generic and good for the design pattern. But they will kill your real-life design, because no one thinks in terms of “accepting” and “visiting”, when in fact, you read/write/delete/modify your file system.

Problem #2: The polymorphism

This is the part that causes even more headache than the naming, when applied to the wrong situation. Why on earth does the visitor know everyone else? Why does the visitor need a method for every involved element in the hierarchy? Polymorphism and encapsulation claim that the implementation should be hidden behind an API. The API (of our data structure) probably implements the composite pattern in some way, i.e. its parts inherit from a common interface. OK, of course, a wheel is not a car, neither is my wife a mechanic. But when we take the folder/file structure, aren’t they all java.util.File objects?

Understanding the problem

The actual problem is not the naming and horrible API verbosity of visiting code, but the mis-understanding of the pattern. It’s not a pattern that is best suited for visiting large and complex data structures with lots of objects of different types. It’s the pattern that is best suited for visiting simple data structures with few different types, but visiting them with hundreds of visitors. Take files and folders. That’s a simple data structure. You have two types. One can contain the other, both share some properties. Various visitors could be:

  • CalculateSizeVisitor
  • FindOldestFileVisitor
  • DeleteAllVisitor
  • FindFilesByContentVisitor
  • ScanForVirusesVisitor
  • … you name it

I still dislike the naming, but the pattern works perfectly in this paradigm.

So when is the visitor pattern “wrong”?

I’d like to give the jOOQ QueryPart structure as an example. There are a great many of them, modelling various SQL query constructs, allowing jOOQ to build and execute SQL queries of arbitrary complexity. Let’s name a few examples:

  • Condition
    • CombinedCondition
    • NotCondition
    • InCondition
    • BetweenCondition
  • Field
    • TableField
    • Function
    • AggregateFunction
    • BindValue
  • FieldList

There are many more. Each one of them must be able to perform two actions: render SQL and bind variables. That would make two visitors each one knowing more than… 40-50 types…? Maybe in the faraway future, jOOQ queries will be able to render JPQL or some other query type. That would make 3 visitors against 40-50 types. Clearly, here, the classic visitor pattern is a bad choice. But I still want to “visit” the QueryParts, delegating rendering and binding to lower levels of abstraction.

How to implement this, then?

It’s simple: Stick with the composite pattern! It allows you to add some API elements to your data structure, that everyone has to implement.

So by intuition, step 1 would be this

interface QueryPart {
  // Let the QueryPart return its SQL
  String getSQL();

  // Let the QueryPart bind variables to a prepared
  // statement, given the next bind index, returning
  // the last bind index
  int bind(PreparedStatement statement, int nextIndex);

With this API, we can easily abstract a SQL query and delegate the responsibilities to lower-level artefacts. A BetweenCondition for instance. It takes care of correctly ordering the parts of a [field] BETWEEN [lower] AND [upper] condition, rendering syntactically correct SQL, delegating parts of the tasks to its child-QueryParts:

class BetweenCondition {
  Field field;
  Field lower;
  Field upper;

  public String getSQL() {
    return field.getSQL() + " between " +
           lower.getSQL() + " and " +

  public int bind(PreparedStatement statement, int nextIndex) {
    int result = nextIndex;

    result = field.bind(statement, result);
    result = lower.bind(statement, result);
    result = upper.bind(statement, result);

    return result;

Whereas BindValue on the other hand, would mainly take care of variable binding

class BindValue {
  Object value;

  public String getSQL() {
    return "?";

  public int bind(PreparedStatement statement, int nextIndex) {
    statement.setObject(nextIndex, value);
    return nextIndex + 1;

Combined, we can now easily create conditions of this form: ? BETWEEN ? AND ?. When more QueryParts are implemented, we could also imagine things like MY_TABLE.MY_FIELD BETWEEN ? AND (SELECT ? FROM DUAL), when appropriate Field implementations are available. That’s what makes the composite pattern so powerful, a common API and many components encapsulating behaviour, delegating parts of the behaviour to sub-components.

Step 2 takes care of API evolution

The composite pattern that we’ve seen so far is pretty intuitive, and yet very powerful. But sooner or later, we will need more parameters, as we find out that we want to pass state from parent QueryParts to their children. For instance, we want to be able to inline some bind values for some clauses. Maybe, some SQL dialects do not allow bind values in the BETWEEN clause. How to handle that with the current API? Extend it, adding a “boolean inline” parameter? No! That’s one of the reasons why the visitor pattern was invented. To keep the API of the composite structure elements simple (they only have to implement “accept”). But in this case, much better than implementing a true visitor pattern is to replace parameters by a “context”:

interface QueryPart {
  // The QueryPart now renders its SQL to the context
  void toSQL(RenderContext context);

  // The QueryPart now binds its variables to the context
  void bind(BindContext context);

The above contexts would contain properties like these (setters and render methods return the context itself, to allow for method chaining):

interface RenderContext {
  // Whether we're inlining bind variables
  boolean inline();
  RenderContext inline(boolean inline);

  // Whether fields should be rendered as a field declaration
  // (as opposed to a field reference). This is used for aliased fields
  boolean declareFields();
  RenderContext declareFields(boolean declare);

  // Whether tables should be rendered as a table declaration
  // (as opposed to a table reference). This is used for aliased tables
  boolean declareTables();
  RenderContext declareTables(boolean declare);

  // Whether we should cast bind variables
  boolean cast();

  // Render methods
  RenderContext sql(String sql);
  RenderContext sql(char sql);
  RenderContext keyword(String keyword);
  RenderContext literal(String literal);

  // The context's "visit" method
  RenderContext sql(QueryPart sql);

The same goes for the BindContext. As you can see, this API is quite extensible, new properties can be added, other common means of rendering SQL can be added, too. But the BetweenCondition does not have to surrender its encapsulated knowledge about how to render its SQL, and whether bind variables are allowed or not. It’ll keep that knowledge to itself:

class BetweenCondition {
  Field field;
  Field lower;
  Field upper;

  // The QueryPart now renders its SQL to the context
  public void toSQL(RenderContext context) {
    context.sql(field).keyword(" between ")
           .sql(lower).keyword(" and ")

  // The QueryPart now binds its variables to the context
  public void bind(BindContext context) {

Whereas BindValue on the other hand, would mainly take care of variable binding

class BindValue {
  Object value;

  public void toSQL(RenderContext context) {

  public void bind(BindContext context) {
    context.statement().setObject(context.nextIndex(), value);

Conclusion: Name it Context-Pattern, not Visitor-Pattern

Be careful when jumping quickly to the visitor pattern. In many many cases, you’re going to bloat your design, making it utterly unreadable und difficult to debug. Here are the rules to remember, summed up:

  1. If you have many many visitors and a relatively simple data structure (few types), the visitor pattern is probably OK.
  2. If you have many many types and a relatively small set of visitors (few behaviours), the visitor pattern is overkill, stick with the composite pattern
  3. To allow for simple API evolution, design your composite objects to have methods taking a single context parameter.
  4. All of a sudden, you will find yourself with an “almost-visitor” pattern again, where context=visitor, “visit” and “accept”=”your proprietary method names”

The “Context Pattern” is at the same time intuitive like the “Composite Pattern”, and powerful as the “Visitor Pattern”, combining the best of both worlds.