PPT-Dynamic Choreographies

Safe Runtime Updates of Distributed Applications Ivan Lanese Computer Science Department Univers ity of BolognaINRIA Italy Joint work with Mila Dalla Preda Maurizio Gabbrielli Saverio Giallorenzo and Jacopo Mauro. Haidong. . Xue. Part One: Knowledge in Textbook. Motivation, Models, Concepts, Algorithms. Part Two: Recent Work. Use the Mobile Agent and Include I/O. Duplex Loading Balancing Strategy. Stability Analysis Based. Computer Science Department. Univers. ity of Bologna/INRIA. Italy. Amending Choreographies. Joint work with . Fabrizio Montesi . and Gianluigi Zavattaro. Map of the talk. Choreographies. Amending choreographies. Anthony R. Lupo. 302 E ABNR Building. Department of Soil, Environmental, and Atmospheric Science . University of Missouri . Columbia, MO 65211. Phone: 573-884-1638 . Email: . LupoA@missouri.edu. Web.missouri.edu/~. Klein: Humiliation Dynamic Introduction ************ There it is: it doesn't make any difference who we are or what we are, there's always somebody to look down on. - Mark Twain, 3,000 Years amon Daniel Trugman. , July . 2013. 2D Rough-Fault Dynamic Simulations. Homogenous background stress + complex fault geometry . . heterogeneity in tractions. Eliminates important source of uncertainty: fault geometry is a direct observable. Institutional Marxian political economy: a basic theory of capitalism, intermediate theories of capitalist world systems, and empirical analyses. 1. Dynamic theory of comparative advantage: dynamic industries and value added per unit of labour (VAL for short). Manufacturing . Systems. By . Djamila. . Ouelhadj. and . Sanja. . Petrovic. Okan Dükkancı. 02.12.2013. Introduction. Dynamic . environments . with inevitable unpredictable real time events. ;. Machine failures . Kibble-. Zurek. Michael Kolodrubetz. Boston University. In collaboration with: . B.K. Clark, D. . Huse. (Princeton). A. . Polkovnikov. , A. Katz (BU). Kibble-. Zurek. Scaling. Disordered. Ordered. Kibble-. Dafny. K. Rustan M. Leino. RiSE. , Microsoft Research. 17 July 2009. JML seminar. Dagstuhl. , Germany. Dafny. experimental language. sequential, object based (no . subclassing. ). specifications in the style of . Dynamic Programming. Dynamic programming is a useful mathematical technique for making a sequence of interrelated decisions. It provides a systematic procedure for determining the optimal combination of decisions.. Student: Josien Jansen. Supervisor: Victor de Boer. Second reader: Frank Nack. 13-07-2017. Introduction. Making . choreographies. . can. . be. . costly. , time-. consuming. . and. . requires. Originally the “Tabular Method”. Key idea:. Problem solution has one or more . subproblems. that can be solved recursively. The . subproblems. are overlapping. The same . subproblem. will get solved multiple times. Presentation for use with the textbook, . Algorithm Design and Applications. , by M. T. Goodrich and R. Tamassia, Wiley, 2015. Application: DNA Sequence Alignment. DNA sequences can be viewed as strings of . Dynamic Apex. Enables you to create more flexible applications by providing you the ability to access . sObject. and field metadata descriptions.. Allows you to write dynamic SOQL and SOSL queries and dynamic DML..