Data-driven web applications are usually structured in three tiers with different programming models at each tier. This division forces developers to manually partition application functionality across the tiers, resulting in complex logic, suboptimal partitioning, and expensive re-partitioning of applications. In this paper, we introduce a unified platform for automatic partitioning of data-driven web applications. Our approach is based on Hilda[41, 46], a high-level declarative programming language with a unified data and programming model for all the layers of the application. Based on run-time properties of the application, Hilda's run time system automatically partitions the application between the tiers to improve response time while adhering to memory and/ or processing constraints at the clients. We evaluate our methodology with traces from a real application and with TPC-W, and our results show that automatic partitioning outperforms manual partitioning without the associated development overhead.

Current application development tools provide completely different programming models for the application server (e.g., Java and J2EE) and the client web browser (e.g., JavaScript and HTML). Consequently, the application developer is forced to partition the application code between the server and client at the time of writing the application. However, the partitioning of the code between the client and server may have to be changed during the evolution of the application for performance reasons (it may be better to push more functionality to the client), for correctness reasons (data that conflicts with multiple clients cannot always be pushed to clients), and for supporting clients with different computing power (browsers on desktops vs. PDAs). Since the client and server use different programming models, moving application code from client to server (and vice versa) reduces programmer productivity and also has the potential to introduce concurrency bugs. In this demonstration, we advocate an alternative solution to this problem: we propose developing applications using a unified declarative high-level language called Hilda, and show how a Hilda compiler can automatically (and correctly) partition Hilda code between the client and the server using a real Course Management System application. We illustrate our techniques using two clients: a powerful laptop machine and a less powerful PDA.