disciplined software engineering lecture #12 software engineering institute carnegie mellon...

Disciplined Software Engineering

Lecture #12

•Software Engineering Institute•Carnegie Mellon University•Pittsburgh, PA 15213

•Sponsored by the U.S. Department of Defense

Design Verification

•Design verification is covered in 2 lectures. This lecture addresses

–the reasons for design verification

–state machine correctness

–execution tables

–proof by induction

•The next lecture covers

–trace tables

–mathematical program verification

–program proofs

Need for Design Verification - 1

•As you work to improve your personal software process, you will likely find it hard to significantly reduce the numbers of design defects you make.

•By using checklists and taking increased care, you can improve the yield of your code reviews.

•To improve the yield of design reviews, you need to use disciplined verification methods.

Defects Injected in Coding -Range

Program Number

De

fec

ts/K

LO

C

0

50

100

150

200

2501 3 5 7 9

Max

Avg.

Min

Defects Injected in Design -Range

Program Number

De

fec

ts/K

LO

C

0

20

40

60

80

1001 3 5 7 9

Max

Avg

Min


•An orderly approach to design verification is essential because

–many common design defects are caused by overlooked conditions

–what seem like unlikely situations become more likely with high-powered computing systems

–conditions that were not possible with an initial program version may be induced by later modifications


•By following a structured design verification procedure, you are more likely to

–see overlooked conditions

–identify rarely exposed risks

–recognize possible future exposures

•By recording data on your design reviews, you can simplify later design inspections.

Using Design Verification - 1

•Design verification methods should be used

–during design

–during design reviews

–during design inspections

•Your design verification methods should focus on the defect types that have caused you the most trouble in test.

Using Design Verification- 2

•The topics covered in this and the next lecture were selected because they address the design defect categories that caused me the most trouble

–state machine structures

–loop constructs

•I would use additional verification methods for the following defect types if they were available

–pointers

–interfaces

Design Verification Topics

•The design verification topics covered in this and the next lecture are

–verifying state machine correctness

–execution tables

–proof by induction

–trace tables

–mathematical program verification

State Machine Correctness

•Any program that changes the state of the computing system is a state machine.

•A program is a state machine if it can behave differently with identical inputs.

•Seemingly simple state machines can have sophisticated behavior. It is thus important to verify them carefully.

State Machine Verification

•The steps in state machine verification are to

–check to ensure the state machine has no hidden traps or loops

–check that the set of all states is complete and orthogonal

–check that the set of all transitions from every state are complete and orthogonal

•After verifying state machine correctness, ensure that the program performs the intended application functions.

Hidden Traps or Loops - 1

•To check for hidden traps and loops

–construct the state template

–construct a state machine diagram

–determine if any exit states are unreachable from any other states

•If any exit states are unreachable from any other state, this is not a proper state machine.


•Example: consider an object BSet as follows

–2 states: EmptyState, MemberState

–4 methods: Push, Pop, Add, Subtract

–Push adds a member to BSet

–Pop removes a member from BSet

–Add adds a member to BSet if it does not already contain an identical member

–Subtract removes a member from BSet if it contains an identical member


•The state template for BSet would be as follows:

EmptyState

MemberState

EmptyState

MemberState

EmptyState

MemberState

n = 0

n >= 1

Pop or Subtract

Push or Add

Pop(n=1) or Subtract(n=1)(D in BSet)

Add or Push or Pop(n>1) orSubtract(D not in BSet) orSubtract(n>1)

Hidden Traps and Loops - 4

EmptyStaten = 0

MemberStaten > 0 Pop(n=1) or

Subtract(n=1)(D in BSet)

Pop or Subtract

Push or Add

Add or Push or Pop(n>1) orSubtract(D not in BSet) orSubtract(n>1)


•It is thus clear that this state machine has no hidden traps or loops.

All Possible States - 1

•A common problem is to overlook some state machine state.

•Examples are initial states, empty states, error states, and so forth.

•Examine all possible conditions of the state parameters to ensure they are either included or truly impossible.

All Possible States - 2

•Checking the BSet example:

–EmptyState has n = 0

–MemberState has n > 0

–since n cannot be < 0, this covers all cases

•To ensure that none of the n > 0 states should be distinct, check to see if any of them exhibit different behavior from the others.

•A check of the state template or state diagram shows that all n>0 states behave identically. Added states are thus unnecessary.

State Orthogonality

•For the states to be orthogonal, the state machine must not be able to be in 2 states at once.

•In the example state machine, either

•n = 0 or n > 0.

•The states are orthogonal because the machine must be in either the EmptyState (n = 0) or the MemberState (n > 0); it cannot be in both at once.

State Transitions - 1

•In a proper state machine, the state transitions must be complete and orthogonal.

•For this to be true

–every state must have a defined next state for every possible input

–every state must have a unique next state for every possible input


•First, check EmptyState in the BSet example for completeness:

–the conditions are Push, Pop, Add, and Subtract

–states are defined for each condition, so the EmptyState transitions are complete.

•The following table shows they are complete:

Push

Pop

Add

Subtract

MemberState

EmptyState

MemberState

EmptyState


•Next, check EmptyState transitions for orthogonality.

•The transition conditions to EmptyState are Pop and Subtract.

•The transition conditions to MemberState are Push and Add.

•Since these next state transition conditions do not overlap, the transition conditions are orthogonal.


•For MemberState completeness, the possible cases are

D in BSet D not in BSet

n = 1 n > 1 n = 1 n > 1Push

Pop

Add

Subtract

MemberState MemberState MemberState MemberState

MemberState MemberState

MemberState MemberState MemberState MemberState

MemberState MemberState MemberState

EmptyState EmptyState

EmptyState

Since these are all the possible cases, the MemberState transitions are complete.


•For MemberState orthogonality, there must be no overlap between the transitions.

–the transitions from MemberState to EmptyState occur when: Pop(n=1) or Subtract(n=1) and (D in BSet)

–the transitions from MemberState to MemberState occur when: Add + Push + Pop(n>1) + Subtract(D not in BSet) + Subtract(n>1)

•As is clear from the previous chart, these two cases have no condition in common and are thus orthogonal.

Class Exercise - 1

•The SignOn object is to have the following methods

–Open - initiates a sign-on procedure

–LogOn - requests a name

–if the name is correct, PassWord requests the password

–if the PassWord is correct, SignOn terminates with the value true

–if there is any error, the program starts again at LogOn

–for any two errors, SignOn terminates with the value false

Class Exercise - 2

•Construct the SignOn state template and state diagram.

•Check for hidden traps and loops.

•Check the states for completeness and orthogonality.

•Check the transitions for completeness and orthogonality.

Class Exercise - State DiagramStandBy

Error

Trial

Open LogOn(No)(false)

LogOn(No)

LogOn(Yes)

PassWord(Yes)(true)

PassWord(No)

LogOn(Yes)

PassWord(Yes) (true)PassWord(No) (false)

Start

NameOk

Exercise - State TemplateStandBy

Start Open

Start

n = 0

n = 1

NameOk

Error

LogOn(Yes)

LogOn(No)

NameOk n = 2

Error PassWord(No)

StandBy (true) Password(Yes)

Error n = 3

Trial LogOn(Yes)StandBy (false) LogOn(No)

Trial n = 4

StandBy (true) PassWord(Yes)

StandBy(false) PassWord(No)

Execution Tables - 1

•An execution table is an orderly way to trace program execution.

–it is a manual check of the program flow

–it starts with initial conditions

–a set of variable values is selected

–each execution step is examined

–every change in variable values is entered

–program behavior is checked against the specification

Execution Tables - 2

•The advantages of execution tables are

–they are simple

–they give reliable proofs

•The disadvantages of execution tables are

–they only check one case at a time

–they are time consuming

–they are subject to human error

Execution Table Procedure

•To use an execution table

–identify the key program variables and enter them at the top of the trace table

–enter the principal program steps

–determine and enter the initial conditions

–trace the variable values through each program step

–for repeating loops, add additional execution table steps for each additional loop cycle

–for long loops, group intermediate steps if their results are obvious

Execution Table Example - 1Cycle 1 ClearSpaces(var Input: string; State: int)

#

1

2

3

4

5

6

7

Instructions Condition Input Length State

Length = length(Input) ‘ AB ‘ 5 0

if Length > 0 true

repeat(until State=3 or Length=0)

if Input[Length-1] = ‘ ‘ true

Length = Length - 1

if State < 2 State=State+1

4

true 1

else State = 3

until State=3 or Length=0 false

Execution Table Example - 2

•3 cycles are required before the until condition is satisfied.

•Just as with a test case, the execution table will only prove the case for this specific variable combination.

•Carefully check the initial conditions to ensure they are set by the program.

•Double check the execution table for errors and omissions.

Proof by Induction

•This method applies to Boolean functions with integer parameters.

•It states

•if f(n) is true for n = k

•and if

–when n = z where z > k

–and f(z) is true

–you can show that f(z+1) is true

•then f(n) is true for all values of n larger than k

Proof by Induction Example

•Example:

• for i=1 to Limit

• do xyz

•

•If

–you can show that this is true for Limit = 1 and

–if it is true for some arbitrary value z

–you can then show it would be true for z+1

–then it is true for all positive values of Limit

A Proof by Induction Technique

•If

–you have a design element using variable x

–you verify that it works for x = k

•Next

–assume it works for some value x = z

–try to find a value of z where program behavior would be improper at z + 1

•If you cannot, the proof is completed.

Factorial Example - 1

•Prove that the following program produces N!

•long Factorial(int N)

•{ F = 1;

• for ( i = 1; i<= N;i++)

• F = F*i;

• return F;

•}

Factorial Example - 2•Pick k = 1 and show that when N=1, F = N!

–since 1 factorial is 1, this is correct

•Next, assume that when N = z, F = z!

•Finally, find any value of z where• F(z) = z! and F(z+1) <> (z+1)!

•Such cases would only occur when–the computing number system was exceeded–computing capacity was exceeded

Assignment #12

•Read Chapter 12 in the text.

•Continue developing program 10A.

•If you have time, start working on the Final Report, R5. The specifications for R5 can be found in Appendix D.

The Messages to Remember from Lecture 12

•1. Your design review yield will significantly

• improve if you use disciplined design

• review methods.

•2. The time spent verifying designs will be

• more than repaid by the testing time saved.

•3. Practice verification techniques and select

• the most effective for finding the defects

• you most commonly find in testing.