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If a process needs to have exclusive access to file X and file Y, it must lock the files in that order Likewise, if a process first locks the printer, it may not then lock either file Having locked the printer, however, the process could still go on to lock the CD-ROM drive It can be shown rather easily that such a scheme will prevent circular wait The difficulty in a general-purpose operating system is to enforce such a discipline among all the application programs In addition, if the more abstract resources such as entries in various system tables, and individual records in files, are considered resources, the complexity of the ordering becomes much greater Because of these implementation problems, general-purpose operating systems do not provide such a facility for deadlock prevention However, this principle can be of great practical value to application developers who work with complex, multithreaded applications.

A frequency table:

public class FrequencyTable { private Map<String,String> map = new TreeMap<String,String>(); public FrequencyTable(String file) { int lineNumber = 0; try { Scanner input = new Scanner(new File(file)); while (input.hasNextLine()) { String line = input.nextLine(); ++lineNumber; StringTokenizer parser = new StringTokenizer(line,",.;:()-! ' ");

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The application developer can impose their own ordering on the shared resources of the application (files, timers, data-base tables, etc) and insure that threads or processes within the application access the resources in order Doing so can insure that the application never deadlocks Deadlock avoidance Since deadlock prevention is not, in general, practical, another approach is to have the operating system maintain a vigilance that will avoid situations where deadlock is possible In 1965, Edgar Dijkstra published the banker s algorithm for deadlock avoidance The banker s algorithm behaves as a banker might in considering whether to grant loans If granting a new loan would put the bank at risk of failing, should too many borrowers make demands on the bank s resources, the banker will deny the loan Thus does the banker avoid difficulty.

while (parser.hasMoreTokens()) { String word = parser.nextToken().toUpperCase(); String frequency = (String)map.get(word); if (frequency==null) { frequency = "1"; } else { int n=Integer.parseInt(frequency); ++n; frequency = "" + n; } map.put(word, frequency); // insert lines 21-40 from Example 8.9

A recursive function is one that calls itself. This powerful technique produces repetition without using loops (e.g., while loops or for loops). Thus it can produce substantial results from very little code. Recursion allows elegantly simple solutions to difficult problems. But it can also be misused, producing inefficient code. Recursive code is usually produced from recursive algorithms. SIMPLE RECURSIVE FUNCTIONS EXAMPLE 9.1 The Factorial Function

The banker s algorithm requires that each process declare at the start the maximum number of resources of each type (eg, how many printers, how many tape drives, etc) it will require over the course of its execution Then, whenever a process requests exclusive access to new resources, the OS simulates granting the request, and checks to see that there is some way for all processes to complete, even assuming that each process immediately requests its maximum requirement of all resources If the check is favorable, that means that the system will remain in a safe state, and the OS grants the resource request Otherwise, the OS blocks the requesting process As appealing as the banker s blgorithm may be, it is not usually applied in practice, for several reasons.

0 1 2 3 4 5 6 7 8 9

1 1 2 6 24 120 720 5,040 40,310 362,880

Many times, processes do not know in advance what their maximum requirement for resources will be; it depends on the results of the computation or the dynamic needs of the application The number of processes is not fixed, either; processes can be added to the mix at any moment, rendering previous calculations of the safe state invalid Likewise, the number of resources may change, as when a device fails or goes off-line (eg, a printer runs out of paper) Deadlock detection Some systems or subsystems (eg, data-base systems) implement deadlock detection This is different from deadlock prevention and deadlock avoidance, which we have discussed and concluded are impractical in general purpose systems On the other hand, deadlock detection can be implemented with beneficial results in some systems Deadlock detection works by having a deadlock detection routine run either periodically, or in response to some circumstance (e.

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