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Introduction Today I thought I'd talk about a neat design pattern that doesn't seem to get much love: In its fullest form it's also sometimes called the Prototype Pattern. People use this pattern all over the place, and I'll give you a nice set of real-life examples in a little bit.
It's a design pattern that's useful in every programming language, and as we'll see shortly, it's also pretty darn useful as a general-purpose persistence strategy.
But even though this pattern is near-universal, people don't talk about it very often.
I think this is because while it's remarkably flexible and adaptable, the Properties Pattern has a reputation for not being "real" design or "real" modeling. In fact it's often viewed as a something of a shameful cheat, particularly by overly-zealous proponents of object-oriented design in language domains or relational design in database domains.
I hope to offer a different and richer perspective here. With luck, this article might even help begin the process making the Properties Pattern somewhat fashionable again.
Three Great Schools of Software Modeling Before I tell you anything else about the Properties Pattern, let's review some of the most popular techniques we programmers have for modeling problems.
I should point out that none of these techniques is tied to "static typing" or "dynamic typing" per se. Each of these modeling techniques can be used with or without static checking. The modeling problem is orthogonal to static typing, so regardless of your feelings about static checking, you should recognize the intrinsic value in each of these techniques.
Class Modeling You know all about this one. Class-based OO design is the pound gorilla of domain modeling these days. Its appeal is that it's a natural match for the way we already model things in everyday life.
It can take a little practice at first, but for most people class modeling quickly becomes second nature. Although the industry loves OO design, it's not especially well liked as an academic topic. This is because OO design has no real mathematical foundation to support it — at least, not until someone comes along and creates a formal model for side effects.
The concepts of OOP stem not from mathematics but from fuzzy intuition. This in some sense explains its popularity, and it also explains why OOP has so many subtly different flavors in practice: Industry folks can never quite agree on what OOP is, but we love it all the same.
Relational Modeling Relational database modeling is a bit harder and takes more practice, because its strength stems from its mathematical foundation. Relational modeling can be intuitive, depending on the problem domain, but most people would agree that it is not necessarily so: Object modeling and relational modeling produce very different designs, each with its strengths and weaknesses, and one of the trickiest problems we face in our industry has always been the object-relational mapping ORM problem.
It's a big deal. Some people may have let you to believe that it's simple, or that it's automatically handled by frameworks such as Rails or Hibernate.
Those who know better know just how hard ORM is in real-world production schemas and systems. Usually XML is used to model data, but it can also be used to model code. In many domains, programmers will decide on an XML representation before they've thought much about the class model, because for those domains XML actually offers the most convenient way of thinking about the problem.
I mention this not to start a fight, but only to illustrate that XML is a third modeling technique in its own right. It has both natural resonances and surfaces of friction with both relational design and OO design, as one might expect. Other schools I'm not claiming that these three modeling schools are the only schools out there — far from it!
Two other obvious candidates are Functional modeling in the sense of Functional Programming, with roots in the lambda calculus and Prolog-style logical modeling. Both are mature problem-modeling strategies, each with its pros and cons, and each having varying degrees of overlap with other strategies.
And there are still other schools, perhaps dozens of them.The computer package used was HOMPACK , a FORTRAN implementation of a homotopy continuation algorithm. A new relaxation approach using complementarity theory to set up the first-order necessary conditions results in a system of m polynomials in m variables which subsequently can be solved by HOMPACK.
Background and update on BOIDS, the model of group motion in flocks, herds, schools and related phenomena. Includes a Java-based demonstration and many links to related research and applications.
The reverse deferred acceptance algorithm is analyzed in great detail in \Deferred-Acceptance Auctions and Radio Spectrum Reallocation Reallo- cation" by Milgrom and Segal (). This course introduces the principles of animation through a variety of animation techniques. Topics include motion research and analysis, effective timing, spacing, volume control, stagecraft, and .
Journal / Refereed Papers: [Back to top ] - - Data-Driven Synthesis of Smoke Flows with CNN-based Feature Descriptors Mengyu Chu, Nils Thuerey. This is a comprehensive catalog of quantum algorithms. If you notice any errors or omissions, please email me at [email protected]