----------------------------------------------------------------------------- DATABASE SEMINAR ----------------------------------------------------------------------------- Prof. Yannis Papakonstantinou Computer Science and Engineering Univ of California at San Diego ----------------------------------------------------------------------------- Declarative, optimizable data-driven specifications of web & mobile applications ----------------------------------------------------------------------------- Giovedi', 12 settembre, 2013 -- h 10:30 **** Aula N3 **** Dipartimento di Ingegneria Universita' Roma Tre Via Vasca Navale, 79 piano terra ----------------------------------------------------------------------------- ABSTRACT Developers of web and mobile Ajax applications write too much low level "plumbing" code to efficiently access, integrate and coordinate application state that resides on the multiple tiers of the architecture, and is accessed using different languages: SQL at the database server; HTML and Javascript at the browser, which in HTML5 includes its own database state; Java or other programming languages at the application server. The FORWARD project replaces such low level programming by providing to the developer a programming abstraction where the web application is treated as a single state machine. FORWARD's cornerstones are (i) the unified application state virtual database, which enables manipulating the entire application state in an extension of SQL, named SQL++ (ii) specification of Ajax pages as essentially rendered views over the unified application state. The state machine abstraction replaces manual coding efforts by system-provided data-related optimizations and automations. We summarize such problems solved in the last four years: 1. The partial change of Ajax pages, in response to application state changes, is reduced to an incremental view maintenance problem for views with keys. 2. Efficient data access is reduced to distributed & semistructured query processing over an integrated view that involves large database(s) and small main memory-based sources. We then summarize a cluster of issues resulting from both mobile agents and demanding Big Data visualizations and propose a recently-initiated effort: 3. The inherent location transparency of the specifications is exploited in order to automatically perform computation at the appropriate location (browser vs server) and reducing latency along the way. Interesting static analysis problems arise in maintaining privacy. 4. An asynchronous version of SQL is suggested. The FORWARD system has been used in 8 commercial and academic applications. Recently a cloud-based version of it became available, which will enable developers and IT people to build data-driven applications over their databases without having to install any additional software. ----------------------------------------------------------------------------- Short Bio: Yannis Papakonstantinou (http://db.ucsd.edu/people/yannis.htm) is a Professor of Computer Science and Engineering at the University of California, San Diego. His research is in the intersection of data management technologies and the web, where he has published over eighty research articles. He has given multiple tutorials and invited talks, has served on journal editorial boards and has chaired and participated in program committees for many international conferences and workshops. Yannis enjoys to commercialize his research and to inform his research accordingly. He was the CEO and Chief Scientist of Enosys Software, which built and commercialized an early XML-based Enterprise Information Integration platform. Enosys Software was acquired in 2003 by BEA Systems. His lab's FORWARD platform (for the rapid development of data-driven Ajax applications) is now in use by many commercial applications. He is involved in data analytics in the pharmaceutical industry and is in the technical advisory board of Brightscope Inc. Yannis holds a Diploma of Electrical Engineering from the National Technical University of Athens, MS and Ph.D. in Computer Science from Stanford University (1997) and an NSF CAREER award for his work on data integration.