Embed finite domain constraint programming into Java and some Web-based applications

Abstract

Although constraint programming has attracted much attention in logic programming, nowadays the importance to integrate constraints with imperative programming is widely acknowledged. In particular, in artificial intelligence domains, the benefits deriving from merging constraint-based programming with object-oriented paradigms seem to be still more attractive because of the lack of 'pure' AI languages in supporting structured representations. This work presents the extension of the Java language towards finite domain constraint programming. This extension has been possible thanks to a high-level approach to low-level resource management: the sleeper mechanism. As practical results, this paper shows how Java programmers can develop meaningful applications in which finite domain constraints have been extensively used, as in the design of visual, interactive, user-interface environments in a client-server architecture.

Synchronizing Interactive Web Documents With Fd-Java Constraints

“…In the work discussed in [21], a Web author as well a Web viewer can perform runtime constraint solving. An experimentation about the constraint approach to design complex graphical interfaces using Java can be found in [22], where constraints are used to specify the desired spatial layout of Web pages.…”

“…The proposal intends to be as general and flexible as possible, so that whatever the Constraint Satisfaction Problem (CSP) is, the programmer may keep the Java programming paradigm. The design of the Java extensions has been accomplished to provide for: − a declarative specification of Web contents by using basic and simple constructs; − an easy integration in the Java o-o model [23]; − an efficient execution (details about the constraint satisfaction issues as well as the implementation choices are not discussed in this paper since they are presented elsewhere [22]).…”

“…The simplest cause is referred to as node inconsistency [41]. The constraint method illustrated in later parts of this paper follows the backtracking technique, even if we avoid some performances drawbacks thanks to a specific implementation strategy that minimizes the memory allocation [22]. 3.…”