I say this because of recent trends in our industry and my hands-on experience with many enterprise and Internet applications, mostly at client sites. You might be thinking that I’m referring to the mainstream breakout of Functional Programming (FP), which is happening right now. The killer app for FP is concurrency. We’ve all heard that more and more applications must be concurrent these days (which doesn’t necessarily mean multithreaded). When we remove side effects from functions and disallow mutable variables, our concurrency issues largely go away. The success of the Actor model of concurrency, as used to great effect in Erlang, is one example of a functional-style approach. The rise of map-reduce computations is another example of a functional technique going mainstream. A related phenomenon is the emergence of key-value store databases, like BigTable and CouchDB, is a reaction to the overhead of SQL databases, when the performance cost of the Relational Model isn’t justified. These databases are typically managed with functional techniques, like map-reduce.

But actually, I’m thinking of something else. Hybrid languages like Scala, F#, and OCaml have demonstrated that OOP and FP can complement each other. In a given context, they let you use the idioms that make the most sense for your particular needs. For example, immutable “objects” and functional-style pattern matching is a killer combination.

What’s really got me thinking that objects are losing their supremacy is a very mundane problem. It’s a problem that isn’t new, but like concurrency, it just seems to grow worse and worse.

The problem is that there is never a stable, clear object model in applications any more. What constitutes a BankAccount or Customer or whatever is fluid. It changes with each iteration. It’s different from one subsystem to another even within the same iteration! I see a lot of misfit object models that try to be all things to all people, so they are bloated and the teams that own them can’t be agile. The other extreme is “balkanization”, where each subsystem has its own model. We tend to think the latter case is bad. However, is lean and mean, but non-standard, worse than bloated, yet standardized?

The fact is, for a lot of these applications, it’s just data. The ceremony of object wrappers doesn’t carry its weight. Just put the data in a hash map (or a list if you don’t need the bits “labeled”) and then process the collection with your iterate, map, and reduce functions. This may sound heretical, but how much Java code could you delete today if you replaced it with a stored procedure?

These alternatives won’t work for all situations, of course. Sometimes polymorphism carries its weight. Unfortunately, it’s too tempting to use objects as if more is always better, like cow bell.

So what would replace objects for supremacy? Well, my point is really that there is no one true way. We’ve led ourselves down the wrong path. Or, to be more precise, we followed a single, very good path, but we didn’t know when to take a different path.

Increasingly, the best, most nimble designs I see use objects with a light touch; shallow hierarchies, small objects that try to obey the Single Responsibility Principle, composition rather than inheritance, etc. Coupled with a liberal use of functional idioms (like iterate, map, and reduce), these designs strike the right balance between the protection of data hiding vs. openness for easy processing. By the way, you can build these designs in almost any of our popular languages. Some languages make this easier than others, of course.

Despite the hype, I think Domain-Specific Languages (DSLs) are also very important and worth mentioning in this context. (Language-Oriented Programming – LOP – generalizes these ideas). It’s true that people drink the DSL Kool-Aid and create a mess. However, when used appropriately, DSLs reduce a program to its essential complexity, while hiding and modularizing the accidental complexity of the implementation. When it becomes easy to write a user story in code, we won’t obsess as much over the details of a BankAccount as they change from one story to another. We will embrace more flexible data persistence models, too.

Back to OOP and FP, I see the potential for their combination to lead to a rebirth of the old vision of software components, but that’s a topic for another blog post.