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Before we can introduce techniques to prevent SQL injection attacks, we consider a variation of the vulnerability as it applies to queries with string-valued parameters. In the example introduced at the beginning of this section, the parameter vulnerable to injection was used in the query in a context in which a numeric quantity was expected: sql_query = ... + "AND order_month=" + request.getParameter("month"); In contrast, parameters that are used in an SQL statement in a context in which a string is expected need to be enclosed in quote characters to allow the SQL parser to correctly parse the data as a string literal. For example, suppose the application also provides a feature to users that allows them to review all orders of pizzas with a particular topping. The corresponding search form would have a field topping, and the resulting SQL query would be constructed as follows: sql_query = "SELECT pizza, toppings, quantity, order_day " + "FROM orders " + "WHERE userid=" + session.getCurrentUserId() + " " + "AND toppings LIKE '%" + request.getParameter("topping") + "%' ";

lock on a single-processor machine.)

nature, as it can live inside other objects, rather than needing its own space on the heap. Of course, this also means you need to be careful not to assign a SpinLock into a local variable, because you d end up making a copy, and locking that copy would not be useful.

Never use SpinLock without comparative performance tests: test all the performance metrics you care about using ordinary monitors and compare that against how the same test suite works when you replace a particular lock with a SpinLock, and consider switching only if the tests demonstrate a clear benefit. If you don t have a test infrastructure capable of verifying that you meet all of your performance requirements, or if you don t have quantitative, clearly specified performance requirements, your project is not ready for SpinLock.

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For some reason, a lot of developers just love to be armchair performance tuners. An astounding amount of time and effort is wasted on mailing lists, on web forums, and in internal company meetings on heated debates over which constructs are theoretically faster than others. Sadly, empirical testing of any kind rarely enters into the equation in such discussions. If someone tries to claim by logical argument alone that a particular technique is faster, be highly suspicious of her claims. Exotic and specialized synchronization primitives such as SpinLock seem to bring out the worst in these people. (And that s the main reason we re even mentioning it sooner or later you ll have to deal with someone who has become obsessed with finding a way to use SpinLock.) Testing and measurement is the only reliable path to performance.

Earlier in this chapter, we suggested immutability as a way to avoid having to synchronize access to your data in the .NET Framework, it s safe for any number of threads to read the same data simultaneously as long as no threads are trying to modify that data at the same time. Sometimes you may find yourself in the frustrating situation of having data that is almost read-only perhaps a website contains a message of the day which, presumably, changes only once a day, but which you may need to incorporate into each of the hundreds of web pages your busy website serves up every second of the day.

There are dozens of color-coordinated site color themes available. You can see the entire list by clicking the Color button. I like the Urban colors, so I selected that theme, as shown in Figure 5-18.

4. Depending on the configuration of the database server, this may, for example, be possible using the xp_cmdshell extended stored procedure supported by Microsoft s SQL Server.

Yielding is when a thread tells the OS scheduler that it wants to give other threads a turn using the CPU now, rather than waiting to be preempted. If there are no other runnable threads, yielding does nothing, and the thread will continue to run.

The monitor s mutually exclusive locking where only one thread at a time gets to acquire a lock seems ill-suited to this scenario You could find that this shared data becomes a bottleneck all threads are taking it in turns to access it, even though that really needs to happen only once a day This is where reader/writer locks come in The idea behind a reader/writer lock is that when you acquire the lock, you declare whether you need to modify the data or just read it.

The lock will allow any number of threads to get a read lock simultaneously, but if a thread tries to get a write lock, it ll have to wait until all the current readers are done, and then, once a thread has a write lock, other threads attempting to get a lock of any kind will be made to wait until the write lock has been released In other words, this kind of lock supports any number of simultaneous readers, but writers get exclusive access (The precise details are, as ever, a little more complex, as a lock of this kind has to avoid the scenario where a neverending stream of readers causes a writer to wait forever New readers may be made to wait even when other readers are currently active simply to clear the decks for a waiting writer.

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