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window to send the event to from the exact location of the click Pointer grabbing and capturing affect it too The normal sequence of pointer events starts with a pointer down event, is followed by zero or more pointer drag events, and ends with a pointer up event It is possible for all of these events to go to the window visible on the screen at the location that they occur However, there are two features that clients can use to vary this behavior: grabbing and capturing If a window receives a down event and it is set to grab pointer events, then WSERV sends all the drag events and the following up event to that window, even if they actually take place over other windows.

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information is I 0 j; x j1 ; . . . ; jn ; x1 ; . . . ; xn and the conditional aggregate mean is E B t jI 0 M tjj; x

17:5

If a window is capturing, and the down event is on a window behind it, then the window that is capturing will receive the event If that window is also grabbing, then it will receive the following drag and up events too In practice, most windows will grab pointer events and some windows will also capture them too Capturing allows dialogs to prevent pointer events from being sent to windows behind them.

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public void run() { try { while (!converged) { update(); int myIndex = barbarrier(); // wait for all to update if (myIndex == 0) convergenceCheck(); barbarrier(); // wait for convergence check } } catch(Exception ex) { // clean up } } void convergenceCheck() { for (int i = 0; i < allSegmentslength; ++i) if (allSegments[i]maxDiff > EPSILON) return; for (int i = 0; i < allSegmentslength; ++i) allSegments[i]converged = true; } }

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From Eq. (17.5), we see that we need to compute the conditional distribution of i the level, that is, the probabilities Pjk tjx , for each source i. However, we can nd i relatively simple expressions for the Laplace transform of Pjk tjx with respect to time because the level process of each source has been assumed to be a semi-Markov process. We now consider a single source and assume that its required bandwidth process is a semi-Markov process (SMP). (We now have no within-level variation process.) We now omit the superscript i. Let L t and B t be the level and required bandwidth, respectively, at time t as in Eq. (17.4). The process fL t : t ! 0g is assumed to be an SMP, while the process fB t : t ! 0g is a function of an SMP, that is B t bL t , where bj is the required bandwidth in level j. If bj T bk for j T k, then fB t : t ! 0g itself is an SMP, but if bj bk for some j T k, then in general fB t : t ! 0g is not an SMP. 17.4.2 Laplace Transform Analysis

WSERV takes the following major steps during the processing of pointer events: Calculates the actual window the pointer event is on Determines if another window s grabbing or capturing means that it should get the pointer event Queues enter and exit events if the current window has changed Tells the key click plug-in about the pointer event For move and drag events, checks the window to see if it doesn t want such events If the window has requested it, stores move and drag events in a pointer buffer If window has a virtual keyboard and the event occurs on one of the virtual keys, converts the event to a key event Checks the event to see if it should be a double-click event, and if a drag-drop event is needed too.

Let A t be the age of the level holding time at time t. We are interested in calculating Pjk tjx P L t kjL 0 j; A 0 x 17:6

For a survey of approaches to high-performance parallel processing, see Skillicorn, David, and Domenico Talia, "Models and Languages for Parallel Computation", Computing Surveys, June 1998 Most texts on parallel programming concentrate on algorithms designed for use on fine-grained parallel machine architectures, but also cover design techniques and algorithms that can be implemented using the kinds of stock multiprocessors most amenable to supporting a JVM See, for example: Foster, Ian Designing and Building Parallel Programs, Addison Wesley, 1995 Roosta, Seyed Parallel Processing and Parallel Algorithms, Springer-Verlag, 1999 Wilson, Gregory Practical Parallel Programming, MIT Press, 1995

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