ASP.NET Web PDF Document Viewer/Editor Control Library

Figure 5-2. Modifying CIL code using notepad.exe Once an *.il file has been edited, the evildoer can recompile the CIL code into an identically named *.dll using the CIL assembler, ilasm.exe: ilasm /dll /out:MyCriticalClass.dll MyCriticalClass.il Clearly the potential of round trip engineering is unnerving if you ship your *.dll or *.exe files to an end user s machine. If an evildoer alters, recompiles, and redeploys your code base, you re the one to blame as far as the end user is concerned. Do understand that not all round trips are dangerous. This same technique can be very helpful when you need to modify an assembly you no longer have source code for, or happen to be building a sophisticated assembly for the purposes of communicating between COM and .NET. Nevertheless, the chances are good that you would like to prevent others from tampering with your compiled binaries.

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type 'a option = | None | Some of 'a Discriminated unions can include recursive references (the same is true of records and other type definitions). This is frequently used when representing structured languages via discriminated unions, a topic covered in depth in 9: type Proposition = | True | And of Proposition * Proposition | Or of Proposition * Proposition | Not of Proposition Recursive functions can be used to traverse such a type. For example: let rec eval (p: Proposition) = match p with | True -> true | And(p1,p2) -> eval p1 && eval p2 | Or (p1,p2) -> eval p1 || eval p2 | Not(p1) -> not (eval p1) Indeed, the F# type of immutable lists is defined in this way: type 'a list = | ([]) | (::) of 'a * 'a list A broad range of tree-like data structures are conveniently represented as discriminated unions. For example: type Tree<'a> = | Tree of 'a * Tree<'a> * Tree<'a> | Tip of 'a You can use recursive functions to compute properties of trees: let rec size tree = match tree with | Tree(_,l,r) -> 1 + size l + size r | Tip _ -> 1 Here is the inferred type of size:

In most cases, optimistic locking is the best alternative to avoid lost updates for the majority of web applications that use connection pooling. However, it does suffer from the disadvantage that a user may have spent a lot of time making changes, only to be told to try her changes again. Pessimistic locking, on the other hand, is suitable for client/server applications that maintain state across pages.

As you may know, a strong name is based in part on two mathematically related keys (the public key and the private key), which are generated using a command line utility named sn.exe (strong name). Like most command line tools, sn.exe has a great number of options; however, if you re simply interested in generating a new key pair, the k flag is all you require: sn k mykeypair.snk

Summary

Here is an example of a constructed tree term and the use of the size function:

In this chapter, you learned about the problem known as lost updates. You looked at various techniques you can use to solve this problem. Changing the transaction isolation level to SERIALIZABLE can solve the problem in some special cases. The technique of locking the row beforehand (pessimistic locking) solves the problem for cases where you maintain state across pages. Optimistic locking solves the problem by detecting the changes made by another transaction and asking the user to retry his transaction if unsuccessful. In most of the web applications that use connection pooling, optimistic locking is the only real alternative since it does not require the application to maintain connections across pages. You examined several implementations of optimistic locking, and finally briefly compared optimistic and pessimistic locking.

> let small = Tree("1",Tree("2",Tip("a"),Tip("b")),Tip("c"));; val small : Tree<string> > small;; val it : Tree<string> = Tree ("1",Tree ("2",Tip("a"),Tip("b")),Tip("c")) > size small;; val it : int = 5 We discuss symbolic manipulation based on trees in detail in s 8, 9, and 12.