Tools
Sorted by:
Try your query at:
 |
 |
 |
 |
 |
 |
Results 1 - 10
of
9,098
Table 4. Predicates used for the predicate abstraction in Fig. 4, and their meaning. Note that the maximal tracked length K is fixed a priori
2005
"... In PAGE 8: ... Table4 shows an example set of predicates similar to the ones used in [1, 8]. Example 3.... In PAGE 8: ...xample 3. Fig. 4(c) shows the predicate abstraction of the concrete state shown in Fig. 4(a) using the predicates of Table4 . A predicate of the form NotNull[x] records the fact that x is not null.... ..."
Cited by 29
Table 4. Predicates used for the predicate abstraction in Fig. 4, and their meaning. Note that the maximal tracked length K is fixed a priori
"... In PAGE 8: ... Table4 shows an example set of predicates similar to the ones used in [1, 8]. Example 3.... In PAGE 8: ...xample 3. Fig. 4(c) shows the predicate abstraction of the concrete state shown in Fig. 4(a) using the predicates of Table4 . A predicate of the form NotNull[x] records the fact that x is not null.... ..."
Table 2: Update predicates
"... In PAGE 3: ... The update of the user knowledge about an item can be: incremental or fixed (the degree of user knowledge is set to a fixed degree of knowledge), absolute (it uses an absolute labelSEM) or relative (it uses the degree of user knowledge about the visited item), each-time or first-time (it is run only the first time the item in the head is visited). Table2 shows the available update predicates and Table 3 includes examples of updates to the item I6 after I4 is visited. To help the author, the system generates by default a set of Ru for each CSL.... ..."
Table 2. The intended meaning of the predicate symbols.
"... In PAGE 6: ... Once we have introduced the notion of individuals we are ready to model ambients by structures of the kind already mentioned in Section 3 and defined formally below. These structures are obtained by fixing the set of predicate symbols so as to be able to represent ambients; we shall use the predicates shown in Table2 . In particular, there is a binary relation pa to represent the parent relation between individuals, and a number of unary relation symbols to represent the ambient information associated with individuals.... ..."
Table 1: Three Fault-relevant Predicates
2006
"... In PAGE 6: ...Table 1: Three Fault-relevant Predicates A glance over the top predicates of the 21 rankings in C1 immediately identifies the fault location. Specifically, the predicates P1 and P2 (see Table1 and Figure 3) appear as the top-2 predicates in 17 of the 21 rankings. Therefore, predicates P1 and P2 are the clear indicator of fault loca- tions.... In PAGE 7: ... This reset of lastout finally causes the predicate P1 at line 549 to evaluate as false. Therefore, based on a proper case f10, the localization result in Table1 is interpreted in a concrete way, which can finally guide developers to fix the fault. In this case, f10 is a proper failing case that developers can base debugging on.... ..."
Cited by 4
Table 2 shows the in and out sets for the first two iterations. Once the fixed point has been reached, the in sets of each statement contain information that approximates the Buf- ferReady predicate. For example, the in set of statement 1 shows that it is safe to deposit data into array A on the right
1996
"... In PAGE 5: ...Stmt in/out 0 in = f lt; ; A gt; lt; ; B gt; g out = f lt; ; A gt; lt; ; B gt; g 1 in = f lt; ; A gt; lt; ; B gt; g out = f lt; ; B gt; g 2 in = f lt; ; B gt; g out = f lt; +shift; A gt; lt; ?shift; A gt;g After iteration 2 Stmt in/out 0 in = f lt; ; A gt; lt; ; B gt; g out = f lt; ; A gt; lt; ; B gt; g 1 in = f lt; +shift; A gt; lt; ?shift; A gt;g out = f lt; +shift; B gt; lt; ?shift; B gt; g 2 in = f lt; +shift; B gt; lt; ?shift; B gt;g out = f lt; +shift; A gt; lt; ?shift; A gt;g Table2 : in and out sets for the first two iterations of the data flow algorithm. and left neighboring nodes without additional synchroniza- tion.... ..."
Cited by 4
Table 1: Accuracy of several predicates for each of the files created on each day. The Zero-Length predicate is that the file will never contain any data. The Lock File predicate is this file will be zero- length and also live less than 5 seconds. The Small File predicate is this file will be written to, but will not grow to more than 16k. The Write Only predicate is that data will be written to the file but the file will never be read (at least during the 24-hour testing period). The predictive model is created by using data from the first day only, and then held fixed for the rest of the test. The d-err is the improvement in accuracy provided by the model, compared with simply guessing the value of each predicate for each file based on the observed probability for that predicate across all files created on the day that the model was built (given as the p for each model).
Table 3 explicitly shows the difference in expressive power, indicating the level of support for each operator. The existing faceted browsers support the ba- sic selection and intersection operators; they also support joins but only with a predefined and fixed join-path, and only on predefined join-predicates. The com- mercial tools are more polished but have in essence the same functionality. Our interface adds the existential operator, the more flexible join operator and the inverse operators. Together these significantly improve the query expressiveness. operator
2006
"... In PAGE 11: ... Table3 : Expressiveness of faceted browsing interfaces Other related work Some non-faceted, domain-independent, browsers for RDF data exist, most notably Noadster [18] and Haystack [16]. Noadster (and its predecessor Topia) focuses on resource presentation and clustering, as opposed to navigation and search, and relies on manual specification of property weights, whereas we automatically compute facet quality.... ..."
Cited by 15
Table 3 explicitly shows the difference in expressive power, indicating the level of support for each operator. The existing faceted browsers support the ba- sic selection and intersection operators; they also support joins but only with a predefined and fixed join-path, and only on predefined join-predicates. The com- mercial tools are more polished but have in essence the same functionality. Our interface adds the existential operator, the more flexible join operator and the inverse operators. Together these significantly improve the query expressiveness. operator
2006
"... In PAGE 11: ... Table3 : Expressiveness of faceted browsing interfaces Other related work Some non-faceted, domain-independent, browsers for RDF data exist, most notably Noadster [18] and Haystack [16]. Noadster (and its predecessor Topia) focuses on resource presentation and clustering, as opposed to navigation and search, and relies on manual specification of property weights, whereas we automatically compute facet quality.... ..."
Cited by 15
Results 1 - 10
of
9,098
