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Published byFelicity Randall Modified over 9 years ago
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Announcements We are done with homeworks Second coding exam this week, in recitation –Times will be posted later today –If in doubt, show up for your regular recitation time
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Invariants Invariants: properties which must always hold –Class invariants hold between (but not necessarily during) method invocations –Loop invariants hold before, during and after execution of a loop Pre/post conditions –Post-conditions of a method spell out what must be true after a method execution completes, if preconditions are satisfied –Pre-conditions of a method spell out what must be true at method invocation in order for method to perform as promised
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Class invariant Recall our Bag implementation: public class Bag implements Collection { private E [] _values; /* CLASS INVARIANTS * _size denotes the number of elements in the bag, and also * the first available position within the array _values */ private int _size; public Bag() { _values = (E[]) (new Object[10]); _size = 0; } // POST: _values is initialized, _size is zero public boolean add(E item) { … } // POST: item is in Bag public void clear() { … } // POST: _size is zero public boolean remove(Object item) { … } // POST: one fewer item is in Bag … }
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Axiomatic semantics Basic idea: you make assertions about statements in a program. A precondition is an assertion about what is true prior to execution of a statement. A postcondition is an assertion about what is true after execution of a statement. For example: sum = 2*sum + 1 {sum > 1} Quotes on upcoming slides are from Concepts of Programming Languages, by Robert Sebesta.
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Weakest precondition “The weakest precondition is the least restrictive precondition that will guarantee the validity of the associated postcondition.” [p. 151] In example above {sum>10} is a valid precondition but {sum>0} is the weakest precondition: {sum > 0} sum = 2*sum + 1 {sum > 1}
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Correctness proofs “If the weakest precondition can be computed from the given postconditions for each statement of a language, then correctness proofs can be constructed for programs in that language.” [p. 151] To do this, start with output specifications for the program as the postcondition for the program as a whole.
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Next, work backwards, computing weakest preconditions one statement at a time, to derive the weakest precondition for the program as a whole: stmt1{c0} stmt1 {c1} stmt2{c1} stmt2 {c2}.. .. stmtN {cN}{cN-1} stmtN {cN}
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If the input specification for the program satisfies the program’s weakest precondition, then the program will (provably) produce the correct result.
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Assignment statements The axiomatic semantics of an assignment statement x=E is written as P=Q x E This means that the precondition is the postcondition with all instances of x replaced by E. Example: a = b/2-1 {a<10} To compute precondition, replace all instances of a in postcondition a<10 by b/2–1 : b/2-1 < 10, or b < 22 Semantics: {b<22} a = b/2-1 {a<10} In general: {Q x E } x=E {Q}
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Inference Suppose we wanted to prove the following: {sum > 5} sum = 2*sum + 1 {sum > 3} Starting with the postcondition, we derive as the weakest precondition something different: 2*sum + 1 > 3 2*sum > 2 sum > 1 (weakest precondition) Clearly this is OK, because the actual precondition {sum>5} implies the weakest precondition {sum>1}: sum>5 => sum>1 We use an inference rule, the rule of consequence, to prove this.
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Rule of consequence General form: S1, S2, …, Sn S Precondition strengthening: P=>P’, {P’} C {Q} {P} C {Q} Postcondition weakening: Q’=>Q, {P} C {Q’} {P} C {Q}
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Precondition strengthening applied Recall our example. We want to prove the following: {sum > 5} sum = 2*sum + 1 {sum > 3} The weakest precondition we derive is: sum > 1 Apply precondition strengthening to finish proof: P=>P’, {P’} C {Q} {P} C {Q} sum>5 => sum>1, {sum>1} sum=2*sum+1 {sum>3} {sum>5} sum=2*sum+1 {sum>3}
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Hang on! Why get so formal? Because this way correctness proofs can be (partially) automated.
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Sequences: S1 S2 Start with a sequence of statements: y = 3*x+1; x = y+3; {x<10} Compute weakest precondition for 2 nd stmt: {y+3<10} or {y<7}, use as postcondition for 1 st stmt: y = 3*x+1; {y<7} {y<7} x = y+3; {x<10} Compute weakest precondition for 1 st stmt: {3x+1<7} or {x<2} {x<2} y = 3*x+1; {y<7} {y<7} x = y+3; {x<10} Conclude, applying sequence rule: {x<2} y = 3*x+1; x = y+3; {x<10} {P} S1 {Q}, {Q} S2 {R} {P} S1 S2 {R}
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Selection: if B then S1 else S2 Start with a conditional statement: if (x>0) then y=y-1 else y=y+1 {y>0} Deal with arms of the conditional one at a time, first the then-arm: y = y-1 {y>0} {y>1} y = y-1; {y>0} Now the else-arm: y = y+1 {y>0} {y>-1} y = y+1; {y>0} Use rule of precondition strengthening on the else-arm result (to make both arms uniform): {y>1} y = y+1; {y>0} Now strengthen both arms’ preconditions by imposing a constraint on x: { x>0 & y>1} y = y-1; {y>0} {!(x>0) & y>1} y = y+1; {y>0} Conclude, applying selection rule: {y>1} if (x>0) then y=y-1 else y=y+1 {y>0} {B & P} S1 {Q}, {!B & P} S2 {Q} {P} if B then S1 else S2 {Q}
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While: while B do S end Let’s prove the following: {true} r=x; q=0; while y<=r do r=r-y; q=q+1; end {y>r & x=r+y*q} Start by proving loop body: {y<=r & x=r+y*q} r=r-y; q=q+1;{x=r+y*q} Start with last statement: q=q+1 {x=r+y*q} {x=r+y*(q+1)} q=q+1 {x=r+y*q} {x=r+y+y*q} q=q+1 {x=r+y*q} Continue with second-to-last statement: r=r-y {x=r+y+y*q} {x=r-y+y+y*q} r=r-y {x=r+y+y*q} {x=r+y*q} r=r-y {x=r+y+y*q} Use rule for sequence to get: {x=r+y*q} r=r-y; q=q+1; {x=r+y*q} Now strengthen precondition to conclude proof of loop body: {y<=r & x=r+y*q} r=r-y; q=q+1; {x=r+y*q} This lets us derive a weakest precondition for the while loop: {x=r+y*q} while y<=r do r=r-y; q=q+1; end {x=r+y*q & !(y<=r)} {B & I} S {I} _ {I} while B do S end {I and !B}
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While: while B do S end The next step is to prove the sequence {true} r=x; q=0; while y r)} Start by moving backwards from the while loop (since we derived a weakest precondition from its postcondition already): {true} r=x; q=0; {x=r+y*q} Start with last statement: q=0; {x=r+y*q} {x=r+y*0} q=0 {x=r+y*q} {x=r} q=0 {x=r+y*q} Continue with second-to-last statement: r=x {x=r} {x=x} r=x {x=r} Precondition strengthening: {true} r=x {x=r} Sequence rule (applied in general form): {true} r=x; q=0; while y<=r do r=r-y; q=q+1; end {x=r+y*q & !(y<=r)} Finally, postcondition weakening because !(y y>r : {true} r=x; q=0; while y r} We're done! {B & I} S {I} _ {I} while B do S end {I and !B}
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Loop invariant Recall the While rule: {B & I} S {I} _ {I} while B do S end {I and !B} I is called the loop invariant: –"…if executing [the body] once preserves the truth of [the invariant], then executing [the body] any number of times also preserves the truth of [the invariant]." [Gordon, Programming Language Theory and its Implementation, paraphrased from page 24]
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Importance of loop invariants Developing loop invariants are a powerful way to design and understand algorithms. Consider selection sort: selectionSort(int[] array) { int min, temp, bar=0; while (bar < array.length - 1) { min = indexOfSmallest(array, bar); // find min temp = array[bar]; // swap array[bar] = array[min]; array[min] = temp; bar = bar + 1; // Loop invariant: region before bar is sorted: // for all i,j<=bar, i<j array[i] <= array[j] } }
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Example [ 7 4 6 8 3 2 ] [ 2 4 6 8 3 7 ] [ 2 3 6 8 4 7 ] [ 2 3 4 8 6 7 ] [ 2 3 4 6 8 7 ] [ 2 3 4 6 7 8 ] region not known to be sorted region known to be sorted
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Priority queues Queue –Ordered by some priority –Regular queue – ordered by time of arrival –Think of ER queue Implementation –List –Heap (a heap-ordered tree)
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