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In some respects, the work with files and ASP.NET 3.5 is somewhat of a sideshow, especially compared with the power of using a database. However, the use of files provides an important functionality either where databases are unavailable or for storing small pieces of information that would make using a database somewhat awkward and overblown. This chapter has only touched on a few of the uses for text files with ASP.NET 3.5; by knowing what they can do, you can employ them for a wide range of applications. Often, even with a database, you may want to have the ability to tap into stored data that can be used to select a database, a table, or some other small task required. So, while certainly not as powerful as a database, text files can be handy for storing details that may be required by a database.

If you have ever employed SARs or written VPD policies with application context variables, you are quite familiar with the use of factors. Everything from the user s identity, to a client identifier, to an IP address are factors that are commonly used to ensure that the security policies are being upheld. With DBV, factors are declared, named, and stored in tables. This allows factors to be reused, validated, and security enhanced. Factor security is possible because the entire DBV infrastructure is secured. One of the biggest risks to any security implementation is an attack on the logical implementation itself. If you are using PL/SQL to protect your data, either as part of a SAR, a VPD, or even an API to prevent direct data access, what protects the PL/SQL Without DBV, nothing protects the security infrastructure other than standard security rights, which, as you have seen, are frequently overridden by system privileges. DBV ensures that the things that are used to secure the database are also protected. This is an important point: DBV significantly strengthens any security implementation. It cannot be replicated using any other database mechanism. NOTE DBV protects the things that protect the things.

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In the early 1900s, pellagra attained epidemic proportions in the southern United States and in the alcoholic population of large

As shown in Figure 5-10, most PCs will have a 1 8 stereo plug for a microphone or input device, and will often have a photo of a microphone or an arrow pointing towards the jack indicating that this is the plug for your microphone. I don t know if there are any color standards, but the microphone jacks on the PCs in my house have a pink outline. Some PCs and many laptops may have a microphone built right into the case somewhere,

A team expresses a coach s personality and its own personality, and this doesn t change from week to week.

executes as follows when the value passed is 5:

Depth- rst search readily identi es all the vertices of a graph that can be reached from a designated starting point. It also nds explicit paths to these vertices, summarized in its search tree (Figure 4.1). However, these paths might not be the most economical ones possible. In the gure, vertex C is reachable from S by traversing just one edge, while the DFS tree shows a path of length 3. This chapter is about algorithms for nding shortest paths in graphs. Path lengths allow us to talk quantitatively about the extent to which different vertices of a graph are separated from each other: The distance between two nodes is the length of the shortest path between them. To get a concrete feel for this notion, consider a physical realization of a graph that has a ball for each vertex and a piece of string for each edge. If you lift the ball for vertex s high enough, the other balls that get pulled up along with it are precisely the vertices reachable from s. And to nd their distances from s, you need only measure how far below s they hang. In Figure 4.2 for example, vertex B is at distance 2 from S, and there are two shortest paths to it. When S is held up, the strings along each of these paths become taut. On the other hand, edge (D, E) plays no role in any shortest path and therefore remains slack. Figure 4.1 (a) A simple graph and (b) its depth- rst search tree. (a) (b)

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