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Lecture 7

Lecture 7. Discuss midterm Scheduling. Alternative Directory Structure. See hw 1 and hw 2. This one more aligned with UNIX directory structure. Idea for implementing processing is the same: at least conceptually separate traversal from maximum computation. UNIX style directory structure. *.

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Lecture 7

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  1. Lecture 7 Discuss midterm Scheduling

  2. Alternative Directory Structure • See hw 1 and hw 2. • This one more aligned with UNIX directory structure. • Idea for implementing processing is the same: at least conceptually separate traversal from maximum computation.

  3. UNIX style directory structure * Directory entries DirectoryEntry inode filename INode FileName Ident Block Size int i; Mode * mode blocks RegularFile

  4. Maximum RegularFile size * Directory entries DirectoryEntry inode filename INode FileName Ident Block Size int i; Mode * mode blocks RegularFile Traversal: from Directory to RegularFile

  5. Maximum RegularFile size: implementation structure Directory entries DirectoryEntry_List inode INode DirectoryEntry Vector * Size int i; Mode Object mode RegularFile

  6. Collecting Informationduring traversal • Java does not have call by reference like C++ or Pascal. • Use IntegerRef class instead: class IntegerRef { private int i_; IntegerRef(int i) { i = i_;} public int getValue() {return i_;} public void setValue(int n) {i_ = n;} }

  7. From IntegerRef to Visitor pattern • Using class IntegerRef is not optimal: The code for computing the maximum is mixed with the traversal code. • A better but more elaborate solution would be to apply the visitor design pattern: instead of an IntegerRef-object, we give a MaxVisitor-object to the traversal.

  8. MaxVisitor class MaxVisitor { private int max; int size; MaxVisitor() { max = 0;} public int get_result() {return max;} public void before(INode host) {size = host.get_size();} public void before(RegularFile host) {if (size > max) max=size;} } // this visitor takes care of transporting size // the traversal is: from Directory to RegularFile

  9. DJ • If you use a library like DJ you can easily program in this style. • DJ: www.ccs.neu.edu/research/demeter/DJ • To learn about software development technology in general and Demeter in particular, take the COM 3360 class in the fall of 2000. See my home page.

  10. Vector in Java 2 • Vector now implements ListInterface. Use following idiom to iterate through list: for (ListIterator I = this.listIterator(); I.hasNext();) { … I.next(); … } • Start using Collection framework as much as possible.

  11. Semaphores in Java:Compare with WaitingStack public final class CountingSemaphore { private int count_ = 0; public CountingSemaphore(int inC) { count_ = inC;} public void P() { // down -- pop while (count_ = 0) try {wait();} catch (InterruptedException ex) {} --count_;} public void V() { // up -- push ++count_; notifyAll(); } } From: Concurrent Programming in Java by Doug Lea

  12. Puzzle: what is this? 0 N1 N2 T1 N2 1 N1 T2 N1 C2 C1 N2 T1 T2 T1 T2 C1 T2 T1 C2

  13. State modeling: two-process mutual exclusion N: noncritical region T: trying region C: critical region 0 N1 N2 T1 N2 1 N1 T2 N1 C2 C1 N2 T1 T2 T1 T2 Note: it is important to have two (T1,T2) C1 T2 T1 C2

  14. State modeling: two-process mutual exclusion N: noncritical region T: trying region C: critical region 0 N1 N2 T1 N2 1 N1 T2 N1 C2 C1 N2 T1 T2 T1 T2 C1 T2 T1 C2 AF(C1) true in 1 EF(C1 and C2) false in 0

  15. Reasoning about concurrency • Abstract from code • Computation tree logic reasons about systems at this level • Uses model-checking techniques

  16. Symbolic Model Checking • Determine correctness of finite state systems. • Developed at Harvard and later at CMU by Clarke/Emerson/Sistla • Specifications are written as formulas in a propositional temporal logic. • Temporal logic: expressing ordering of events without introducing time explicitly

  17. Temporal Logic • A kind of modal logic. Origins in Aristotle and medieval logicians. Studied many modes of truth. • Modal logic includes propositional logic. Embellished with operators to achieve greater expressiveness. • A particular temporal logic: CTL (Computation Tree Logic)

  18. Computation Tree Logic • Used to express properties that will be verified • Computation trees are derived from the state transition graphs • State transition graphs unwound into an infinite tree rooted at initial state

  19. S0 a b S0 S1 S2 S2 a c b c S0 S1 S1 S1 S2 structure S0 computation tree for S0

  20. Computation Tree Logic • CTL formulas built from • atomic propositions, where each proposition corresponds to a variable in the model • Boolean connectives • Operators. Two parts • path quantifier (A, E) • temporal operator (F,G,X,U)

  21. Computation Tree Logic • Paths in tree represent all possible computations in model. • CTL formulas refer to the computation tree If the signal req is high then eventually ack will also be high

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