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he Quick Tag Editor has a rather nifty feature referred to as the hint list. To make it even quicker to use the Quick Tag Editor, a list of tags pops up when you pause in your typing. When you re entering attributes within a tag, a list of appropriate parameters pops up instead of tags. These lists are tied to what, if anything, you ve already typed. Suppose, for instance, you ve begun to enter blockquote and have only gotten as far typing b and l. When the hint list appears, it scrolls to blink the first tag in the list starting with those two letters. If you continue typing o, blockquote is selected. All you have to do to insert it into your code is press Enter (Return). Following are a few other hint list hints:

In recent years, many critics of expert systems have argued for more exibility in the user interface if further progress in the eld is to take place. While there have been several notable and successful commercial applications, such as XCON as discussed in the previous chapter, practitioners and researchers alike have recognized that traditional expert system user interfaces are largely rigid and intolerant of an user s need to understand the assumptions and reasoning underlying the knowledge base. The user, in effect, is forced to view the knowledge base as a black box. While some limited forms of explanation may be available, there is usually no easy and intuitive way to understand why and how a given set of inputs produced a nal recommendation. Especially problematic for the user is gaining an understanding of the problem-solving strategies employed by the expert system to make its decisions. For example, in a typical consultation with MYCIN, a user (typically a physician) would answer questions about patient data such as symptoms, test results, and patient characteristics. Based on these responses, MYCIN would reach a diagnosis on what the bacterial infection might be, and recommend an appropriate treatment. However, from the user s perspective, the system seemed to ask a series of unrelated questions, and there was no sense of coherence to what was being asked. In short, a user was unable to form an appropriate mental model of how the system produced its recommendation because the expert system is lacking in explanatory power. In 1, we de ned more precisely what explanatory power is. An intelligent system that is capable of explaining its actions is said to be one endowed

The SHINITDLGINFO structure contains information that determines how a dialog looks when it is invoked. Table 5.4 lists the structure members and their meanings.

5

) f (0, s)

to that when you validate your application. Refer also to other existing documents such as SOPs and the Quality Manual. There is no need to repeat the work. This chapter includes which information is needed somewhere. It is up to you to de ne where you want the information. It must exist, but there is no rule saying where. A well-planned approach can save the organization a lot of work. It isn t cost-effective or useful to invent the wheel over and over again.

where c ( x , y ) E P[x]/(xnl - 1, ynz - 1). That is, in the ring where xnl = 1 and yn2 = 1 (since the codes are cyclic). Thus nc(x, y) and yc(x, y) represent cyclic shifts of the rows and columns, respectively, of c. (a) Show that there exists a function Z(i, j ) such that for each pair (i, j ) with 0 5 i < n 1 and 0 5 j < n2, Z(i, j) is a unique integer in the range 0 5 I ( i , j) < nln2, such that

foreach n1 where n1.name='alice' do: foreach n2 where n2.name='bob' do: foreach e where e.orig=n1.id and e.dest=n2.id do: return e.* end end end

bookQuery = "select +SE-CONST. DBBOOKNAME+ ",'' +SE-CONST. DB-AUTHOR+ +SE-CONST .DB-PUBLISHER+ 'I , i-SE-CONST.DB-PRICE+ ' I , +SE-CONST. DB-ISBN+ +SE-CONST.DB-YEAR+ "from" +SE-CONST.BOOKSTORE+ "where" +SE-CONST. DB-ISBN+ "like ' % ' '' ;

Let us examine conditions under which an erasures-and-errors decoder can succeed. The decoder can succeed if there are apparently no errors and d d n - 1 erasures, or one error and dmin - 3 erasures, and SO forth up to to errors and dmin - 2t0 - 1 erasures, where to is the largest integer such that 2t0 5 dhn - 1. These possibilities are exactly those examined by the statement of the GMD decoder in Algorithm 11.1.