Slide 11.1
Fifth Edition, WCB/McGraw-Hill, 2002
Stephen R. Schach srs@vuse.vanderbilt.edu
© The McGraw-Hill Companies, 2002

CHAPTER 11
Slide 11.2
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Overview
 The specification document
 Informal specifications
 Structured systems analysis
 Other semiformal techniques
 Entity-relationship modeling
 Finite state machines
 Petri nets
 Other formal techniques
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Slide 11.3

Overview (contd)
 Comparison of specification techniques
 Testing during the specification phase
 CASE tools for the specification phase
 Metrics for the specification phase
 Air Gourmet Case Study: structured systems analysis
 Air Gourmet Case Study: software project management plan
 Challenges of the specifications phase
Slide 11.4
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Specification Phase
 Specification document must be
– Informal enough for client
– Formal enough for developers
– Free of omissions, contradictions, ambiguities
Slide 11.5
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Specification Document
 Constraints
– Cost
– Time
– Parallel running
– Portability
– Reliability
– Rapid response time
Slide 11.6
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Specification Document (contd)
Slide 11.7
 Acceptance criteria
– Vital to spell out series of tests
– Product passes tests, deemed to satisfy specifications
– Some are restatements of constraints
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Solution Strategy




General approach to building the product
Find strategies without worrying about constraints
Modify strategies in the light of constraints, if necessary
Keep a written record of all discarded strategies, and why they were discarded
– To protect the specification team
– To prevent unwise new “solutions” during the maintenance phase
Slide 11.8
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Informal Specifications
Slide 11.9
 Example
“If sales for current month are below target sales, then report is to be printed, unless difference between target sales and actual sales is less than half of difference between target sales and actual sales in previous month, or if difference between target sales and actual sales for the current month is under 5%”
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Meaning of Specification
Slide 11.10
 Sales target for January was $100,000, actual sales were only $64,000 (36% below target)
– Print report
 Sales target for February was $120,000, actual sales were only $100,000 (16.7% below target)
– Percentage difference for February (16.7%) less than half of previous month’s percentage difference (36%), do not print report
 Sales target for March was $100,000, actual sales were $98,000 (2% below target)
– Percentage difference < 5%, do not print
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But Specifications Do Not Say This
Slide 11.11

“[D]ifference between target sales and actual sales”
– There is no mention of percentage difference



Difference in January was $36,000, difference in
February was $20,000
– Not less than half of $36,000, so report is printed
“[D]ifference … [of] 5%”
– Again, no mention of percentage
Ambiguity —should the last clause read
“percentage difference … [of] 5%” or “difference …
[of] $5,000” or something else entirely?
 Style is poor
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Informal Specifications (contd)
Slide 11.12
 Claim
– This cannot arise with professional specifications writers
 Refutation
– Text Processing case study
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Episode 1
Slide 11.13
 1969 — Naur Paper
Given a text consisting of words separated by blank or by nl
(new line) characters, convert it to line-byline form in accordance with following rules:
(1) line breaks must be made only where given text has blank or nl ;
(2) each line is filled as far as possible, as long as
(3) no line will contain more than maxpos characters
 Naur constructed a procedure (25 lines of Algol
60), and informally proved its correctness
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Episode 2
Slide 11.14
 1970 — Reviewer in Computing Reviews
– First word of first line is preceded by a blank unless the first word is exactly maxpos characters long
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Episode 3
Slide 11.15
 1971 — London found 3 more faults
– Including: procedure does not terminate unless a word longer than maxpos characters is encountered
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Episode 4
Slide 11.16
 1975 — Goodenough and Gerhart found 3 further faults
– Including —last word will not be output unless it is followed by blank or nl
 Goodenough and Gerhart then produced new set of specifications, about four times longer than
Naur’s
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Case Study (contd)
Slide 11.17


1985 — Meyer detected 12 faults in Goodenough and Gerhart’s specifications
Goodenough and Gerhart’s specifications
– Were constructed with the greatest of care
– Were constructed to correct Naur’s specifications
– Went through two versions, carefully refereed
– Were written by experts in specifications
– With as much time as they needed
– For a product about 30 lines long
 What chance do we have of writing fault-free specifications for a real product?
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Episode 5
 1989 — Schach found fault in Meyer’s specifications
– Item (2) of Naur’s original requirement (“each line is filled as far as possible”) is not satisfied
Slide 11.18
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Informal Specifications
Slide 11.19
 Conclusion
– Natural language is not a good way to specify product
 Fact
– Many organizations still use natural language, especially for commercial products
 Reasons
– Uninformed management
– Undertrained computer professionals
– Management gives in to client pressure
– Management is unwilling to invest in training
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Structured Systems Analysis
Slide 11.20
 Three popular graphical specification methods of
’70s
– DeMarco
– Gane and Sarsen
– Yourdon
 All equivalent
 All equally good
 Many U.S. corporations use them for commercial products
 Gane and Sarsen used for object-oriented design
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Structured Systems Analysis Case Study
Slide 11.21
Sally’s Software Store buys software from various suppliers and sells it to the public. Popular software packages are kept in stock, but the rest must be ordered as required. Institutions and corporations are given credit facilities, as are some members of the public.
Sally’s Software Store is doing well, with a monthly turnover of 300 packages at an average retail cost of
$250 each. Despite her business success, Sally has been advised to computerize. Should she?
 Better question
– What sections?
 Still better
– How? Batch, or online? In-house or out-service?
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Case Study (contd)
Slide 11.22
 Fundamental issue
– What is Sally’s objective in computerizing her business?



Because she sells software?
– She needs an in-house system with sound and light effects
Because she uses her business to launder “hot” money?
– She needs a product that keeps five different sets of books, and has no audit trail
Assume: Computerization “in order to make more money”
– Cost/benefit analysis for each section of business
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Case Study (contd)


The danger of many standard approaches
– First produce the solution, then find out what the problem is!
Gane and Sarsen’s method
– Nine-step method
– Stepwise refinement is used in many steps
Slide 11.23
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Case Study (contd)
Slide 11.24
 Data flow diagram (DFD) shows logical data flow
– “what happens, not how it happens”
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Step 1. Draw the DFD
 First refinement
 Infinite number of possible interpretations
Slide 11.25
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Step 1 (contd)

 Second refinement pending orders scanned daily
Slide 11.26
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 Portion of third refinement
Step 1 (contd)
Slide 11.27
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Step 1 (contd)
Slide 11.28




Final DFD
– Larger, But easily understood by client
Larger DFDs
– Hierarchy
– Box becomes DFD at lower level
Frequent problem
– Process P at level L, expanded at level L+1
– Correct place for sources and destinations of data for process P is level L+1
– Clients cannot understand DFD —sources and destinations of data for P are “missing”
Solution
– Draw “correct” DFD, modify by moving sources and destinations of data one or more levels up
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Step 2. Decide What Parts to Computerize
Slide 11.29
 Depends on how much client is prepared to spend
 Large volumes, tight controls
– Batch
 Small volumes, in-house microcomputer
– Online
 Cost/benefit analysis
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Step 3. Refine Data Flows
 Data items for each data flow
 Refine each flow stepwise
 Refine further
 Need a data dictionary
Slide 11.30
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Step 3. Refine Data Flows (contd)
Slide 11.31
 Sample data dictionary entries
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Step 4. Refine Logic of Processes
Slide 11.32
 Have process give educational discount
– Sally must explain discount for educational institutions
– 10% on up to 4 packages, 15% on 5 or more
 Translate into decision tree
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Step 4 (contd)
 Advantage of decision tree
– Missing items are quickly apparent
Slide 11.33
 Can also use decision tables
– CASE tools for automatic translation
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Step 5. Refine Data Stores
Slide 11.34
 Define exact contents and representation (format)
– COBOL: specify to pic level
– Ada: specify digits or delta
 Specify where immediate access is required
– Data immediate access diagram (DIAD)
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Step 6. Define Physical Resources
Slide 11.35
 For each file, specify
– File name
– Organization (sequential, indexed, etc.)
– Storage medium
– Blocking factor
– Records (to field level)
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Step 7. Determine Input/Output Specs
Slide 11.36
 Specify input forms, input screens, printed output
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Step 8. Perform Sizing
 Numerical data for Step 9 to determine hardware requirements
– Volume of input (daily or hourly)
– Size, frequency, deadline of each printed report
– Size, number of records passing between CPU and mass storage
– Size of each file
Slide 11.37
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Step 9. Hardware Requirements
 DASD requirements
 Mass storage for back-up
 Input needs
 Output devices
 Is existing hardware adequate?
 If not, recommend buy/lease
Slide 11.38
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However
Slide 11.39
 Response times cannot be determined
 Number of I/O channels can only be guessed
 CPU size and timing can only be guessed
 Nevertheless, no other method provides these data for arbitrary products
 The method of Gane and Sarsen/De
Marco/Yourdon has resulted in major improvements in the software industry
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Entity-Relationship Diagrams
 Semi-formal technique
 Widely used for specifying databases
 Used for object-oriented analysis
Slide 11.40
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Entity-Relationship Diagrams (contd)
Slide 11.41


Many-to-many relationship
More complex entity-relationship diagrams
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Formality versus Informality



Informal method
– English (or other natural language)
Semiformal methods
– Gane & Sarsen/DeMarco/Yourdon
– Entity-Relationship Diagrams
– Jackson/Orr/Warnier,
– SADT, PSL/PSA, SREM, etc.
Formal methods
– Finite State Machines
– Petri Nets
– Z
– ANNA, VDM, CSP, etc.
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Slide 11.42

Finite State Machines
Slide 11.43
 Case study
A safe has a combination lock that can be in one of three positions, labeled 1, 2, and 3. The dial can be turned left or right (L or R). Thus there are six possible dial movements, namely 1L, 1R, 2L, 2R,
3L, and 3R. The combination to the safe is 1L, 3R,
2L; any other dial movement will cause the alarm to go off
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Finite State Machines (contd)
Slide 11.44
 Transition table
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Extended Finite State Machines
 Extend FSM with global predicates
 Transition rules have form state and event and predicate
 new state
Slide 11.45
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Elevator Problem
Slide 11.46
A product is to be installed to control n elevators in a building with m floors. The problem concerns the logic required to move elevators between floors according to the following constraints:
1.
Each elevator has a set of m buttons, one for each floor. These illuminate when pressed and cause elevator to visit corresponding floor. Illumination is canceled when corresponding floor is visited by elevator
2.
Each floor, except the first and the top floor, has 2 buttons, one to request an up-elevator, one to request a down-elevator. These buttons illuminate when pressed.
The illumination is canceled when an elevator visits the floor, then moves in the desired direction
3.
If an elevator has no requests, it remains at its current floor with its doors closed
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Elevator Problem: FSM
Slide 11.47
 Two sets of buttons
– Elevator buttons —in each elevator, one for each floor
– Floor buttons —two on each floor, one for up-elevator, one for down-elevator
EB(e, f): Elevator Button in elevator e pressed to request floor f
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Elevator Buttons (contd)
 Two states
EBON(e, f): Elevator Button (e,f) ON
EBOFF(e,f): Elevator Button (e,f) OFF
Slide 11.48
– If button is on and elevator arrives at floor f , then light turned off
– If light is off and button is pressed, then light comes on
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Elevator Buttons (contd)
 Two events
EBP(e,f): Elevator Button (e,f) Pressed
EAF(e,f): Elevator e Arrives at Floor f
 Global predicate
V(e,f): Elevator e is Visiting (stopped at) floor f
 Transition Rules
EBOFF(e,f) and EBP(e,f) and not V(e,f)

EBON(e,f)
EBON(e,f) and EAF(e,f) Þ EBOFF(e,f)
Slide 11.49
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Floor Buttons
Slide 11.50
 Floor buttons
FB(d, f): Floor Button on floor f that requests elevator traveling in direction d
 States
FBON(d, f): Floor Button (d, f) ON
FBOFF(d, f): Floor Button (d, f) OFF
– If floor button is on and an elevator arrives at floor f, traveling in correct direction d, then light is turned off
– If light is off and a button is pressed, then light comes on
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Floor Buttons (contd)
Slide 11.51



Events
FBP(d, f): Floor Button (d, f) Pressed
EAF(1..n, f):E levator 1 or … or n Arrives at Floor f
Predicate
S(d, e, f): elevator e is visiting floor f
Direction of motion is up (d = U), down (d = D), or no requests are pending (d = N)
Transition rules
FBOFF(d, f) and FBP(d, f) and not S(d, 1..n, f)

FBON(d, f)
FBON(d, f) and EAF(1..n, f) and S(d, 1..n, f)

FBOFF(d, f), d = U or D
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Elevator Problem: FSM (contd)
 State of elevator consists of component substates, including:
– Elevator slowing
– Elevator stopping
– Door opening
– Door open with timer running
– Door closing after a timeout
Slide 11.52
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Elevator Problem: FSM (contd)
Slide 11.53
 Assume elevator controller moves elevator through substates
– Three elevator states
M(d, e, f):
S(d, e, f):
Moving in direction d (floor f is next)
Stopped (d-bound) at floor f
W(e,f): Waiting at floor f (door closed)
– For simplicity, three stopped states S(U, e, f) , S(N, e, f) , and S(D, e, f) are grouped into one larger state
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Elevator Problem: FSM (contd)
Slide 11.54
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Elevator Problem: FSM (contd)
Slide 11.55
 Events
DC(e,f): Door Closed for elevator e, floor f
ST(e,f): Sensor Triggered as elevator e nears floor f
RL: Request Logged (button pressed)
 Transition Rules
If elevator e is in state S(d, e, f) (stopped, d-bound, at floor f), and doors close, then elevator e will move up, down, or go into wait state
DC(e,f) and S(U, e, f)

M(U, e, f+1)
DC(e,f) and S(D, e, f)

M(D, e, f-1)
DC(e,f) and S(N, e, f)

W(e,f)
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Power of FSM to Specify Complex Systems
Slide 11.56
 No need for complex preconditions and postconditions
 Specifications take the simple form current state and event and predicate
 next state
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Power of FSM to Specify Complex Systems
Slide 11.57
 Using an FSM, a specification is
– Easy to write down
– Easy to validate
– Easy to convert into design
– Easy to generate code automatically
– More precise than graphical methods
– Almost as easy to understand
– Easy to maintain
 However
– Timing considerations are not handled
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Who Is Using FSMs?



Commercial products
– Menu driven
– Various states/screens
– Automatic code generation a major plus
System software
– Operating system
– Word processors
– Spreadsheets
Real-time systems
– Statecharts are a real-time extension of
FSMs
» CASE tool: Rhapsody
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Slide 11.58

Petri Nets


A major difficulty with specifying real-time systems is timing
– Synchronization problems
– Race conditions
– Deadlock
Often a consequence of poor specifications
Slide 11.59
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Petri Nets (contd)
 Petri nets
– Powerful technique for specifying systems with potential timing problems
 A Petri net consists of four parts:
– Set of places P
– Set of transitions T
– Input function I
– Output function O
Slide 11.60
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Petri Nets (contd)




Set of places
P is
{p
1
, p
2
, p
3
, p
4
}
Set of transitions
T is
{t
1
, t
2
}
Input functions:
I(t
1
) = {p
2
, p
4
}
I(t
2)
= {p
2
}
Output functions:
O(t
1
) = {p
1
}
O(t
2
) = {p
3
, p
3
}
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Slide 11.61

Petri Nets (contd)







More formally, a Petri net is a 4-tuple
C = (P, T, I, O)
P = {p
1
, p
2
,…,p n
} is a finite set of places , n ≥ 0
T = {t
1
, t
2
,…,t m
} is a finite set of and
T disjoint transitions , m ≥ 0 , with
P
I : T

P
∞ is input function, mapping from transitions to bags of places
O : T

P
∞ is output function, mapping from transitions to bags of places
(A bag is a generalization of sets which allows for multiple instances of element in bag, as in example above)
Marking of a Petri net is an assignment of tokens to that Petri net
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Slide 11.62

Petri Nets (contd)
Slide 11.63


Four tokens, one in p
1
, two in p
2
, none in p
3
, and one in p
4
– Represented by vector (1,2,0,1)
Transition is enabled if each of its input places has as many tokens in it as there arcs from the place to that transition
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Petri Nets (contd)
Slide 11.64


Transition t
1 is enabled (ready to fire)
– If t
1 fires, one token is removed from p
2 p
4
, and one new token is placed in p
1 and one from
Important: Number of tokens is not conserved
 Transition t
2 is also enabled
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Petri Nets (contd)
 Petri nets are indeterminate
– Suppose t
1 fires
Slide 11.65
 Resulting marking is
(2,1,0,0)
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Petri Nets (contd)
 Now only t
2 enabled
– It fires is
Slide 11.66
 Marking is now
(2,0,2,0)
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Petri Nets (contd)
Slide 11.67
 More formally, a marking
M of a Petri net
C = (P, T, I, O) is a function from the set of places
P to the non-negative integers
N
M : P

N
 A marked Petri net is then 5-tuple
(P, T, I, O, M )
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Petri Nets (contd)
Slide 11.68
 Inhibitor arcs
– Inhibitor arc is marked by small circle, not arrowhead
 Transition t
1 is enabled
– In general, transition is enabled if at least one token on each (normal) input arc, and no tokens on any inhibitor input arcs
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Elevator Problem: Petri Net
 Product is to be installed to control n elevators in a building with m floors
– Each floor represented by place F f
, 1
 f
 m
– Elevator represented by token
– Token in F f denotes that an elevator is at floor F f
Slide 11.69
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Elevator Problem: Petri Net (contd)
Slide 11.70



First constraint
1.
Each elevator has a set of m buttons, one for each floor. These illuminate when pressed and cause the elevator to visit the corresponding floor. The illumination is canceled when the corresponding floor is visited by an elevator
Elevator button for floor f is represented by place
EB f
, 1
 f
 m
Token in
EB f denotes that the elevator button for floor f is illuminated
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Elevator Problem: Petri Net (contd)
Slide 11.71
 A button must be illuminated the first time button is pressed and subsequent button presses must be ignored


If button
EB f is not illuminated, no token in place and transition
EB f pressed is enabled
– Transition fires, new token is placed in EB f
Now, no matter how many times button is pressed, transition
EB f pressed cannot be enabled
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Elevator Problem: Petri Net (contd)
Slide 11.72
 When elevator reaches floor g, token is in place
F g
, transition Elevator in action is enabled, and then fires
– Tokens in EB f and F g removed
– This turns off light in button EB f
– New token appears in F f
– This brings elevator from floor g to floor f
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Elevator Problem: Petri Net (contd)
Slide 11.73
 Motion from floor g to floor f cannot take place instantaneously
– Timed Petri nets
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Elevator Problem: Petri Net (contd)
Slide 11.74
 Second constraint
2.
Each floor, except the first and the top floor, has 2 buttons, one to request an up-elevator, one to request a down-elevator. These buttons illuminate when pressed.
The illumination is canceled when the elevator visits the floor, and then moves in desired direction
 Floor buttons represented by places
FB u f and
FB d f
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Elevator Problem: Petri Net (contd)
Slide 11.75
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Elevator Problem: Petri Net (contd)
Slide 11.76
 The situation when an elevator reaches floor f from floor g with one or both buttons illuminated
– If both buttons are illuminated, only one is turned off
– (A more complex model is needed to ensure that the correct light is turned off)
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Elevator Problem: Petri Net (contd)
Slide 11.77
 Third constraint
C
3
. If an elevator has no requests, it remains at its current floor with its doors closed
 If no requests, no
Elevator in action transition is enabled
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Petri Nets (contd)
 Petri nets can also be used for design
 Petri nets possess the expressive power necessary for specifying timing aspects of real-time systems
Slide 11.78
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Z (“zed”)
 Formal specification language
 High squiggle factor
 Z specification consists of four sections:
– 1.
Given sets, data types, and constants
– 2.
State definition
– 3.
Initial state
– 4.
Operations
Slide 11.79
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Elevator Problem: Z
 1. Given Sets
 Sets that need not be defined in detail
– Names appear in brackets
– Here we need the set of all buttons
– Specification begins
[Button]
Slide 11.80
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Elevator Problem: Z (contd)
 2. State Definition
Slide 11.81
 Z specification consists of a number of schemata
– Schema consists of group of variable declarations, plus
– List of predicates that constrain values of variables
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Elevator Problem: Z (contd)
Slide 11.82
 Four subsets of Button
– The floor buttons
– The elevator buttons
– buttons (the set of all buttons in the elevator problem)
– pushed (the set of buttons that have been pushed)
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Elevator Problem: Z (contd)
Slide 11.83
 Schema Button_State
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Elevator Problem: Z (contd)
 3. Initial State
Slide 11.84
 State when the system is first turned on
B utton_Init

[ Button_State ' | pushed' =

]
– (In the above equation, the
 should be a = with a ^ on top. Unfortunately, this is hard to type in PowerPoint!)
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Elevator Problem: Z (contd)
 4. Operations
Slide 11.85
 Button pushed for first time is turned on, and added to set pushed
 Without third precondition, results would be unspecified
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Elevator Problem: Z (contd)
Slide 11.86
 If elevator arrives at a floor, the corresponding button(s) must be turned off
 The solution does not distinguish between up and down floor buttons
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Analysis of Z
Slide 11.87
 Most widely used formal specification language
– CICS (part)
– Oscilloscope
– CASE tool
– Large-scale projects (esp. Europe)
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Analysis of Z (contd)


Difficulties
– Symbols
– Mathematics
Reasons for great success
– Easy to find faults in Z specification
– Specifier must be extremely precise
– Can prove correctness
– Only high-school math needed to read Z
– Decreases development time
– “Translation” clearer than informal specification
© The McGraw-Hill Companies, 2002
Slide 11.88

Other Formal Methods
 Anna
– Ada
 Gist, Refine
– Knowledge-based
 VDM
– Denotational semantics
 CSP
– Sequence of events
– Executable specifications
– High squiggle factor
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Slide 11.89

Comparison of Specification Techniques
Slide 11.90
 We must always choose the appropriate specification method
 Formal methods
– Powerful
– Difficult to learn and use
 Informal methods
– Little power
– Easy to learn and use
 Trade-off
– Ease of use versus power
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Comparison of Specification Techniques (contd)
Slide 11.91
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Newer Methods
 Many are untested in practice
 Risks
– Training costs
– Adjustment from classroom to actual project
– CASE tools may not work properly
 However, possible gains may be huge
Slide 11.92
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Which Specification Method to Use?
Slide 11.93
 Depends on the
– Project
– Development team
– Management team
– Myriad other factors
 It is unwise to ignore the latest developments
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Testing during the Specification Phase
Slide 11.94
 Specification inspection
– Checklist
 Doolan [1992]
– 2 million lines of FORTRAN
– 1 hour of inspecting saved 30 hours of execution-based testing
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CASE Tools for the Specification Phase
Slide 11.95
 Graphical tool
 Data dictionary
– Integrate them
 Specification method without CASE tools fails
– SREM
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CASE Tools for the Specification Phase
Slide 11.96
 Typical tools
– Analyst/Designer
– Software through Pictures
– System Architect
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Metrics for the Specification Phase
Slide 11.97
 Five fundamental metrics


Quality
– Fault statistics
– Number, type of each fault
– Rate of detection
Metrics for “predicting” size of target product
– Total number of items in data dictionary
– Number of items of each type
– Processes vs. modules
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Air Gourmet Case Study: Structured Sys. Anal.
Slide 11.98
 Data flow diagram reflects centrality of
SPECIAL MEAL DATA
 See Appendix E for remainder of structured systems analysis
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Air Gourmet Case Study: SPMP
Slide 11.99
 The Software Project Management Plan is given in Appendix F
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Challenges of the Specification Phase
Slide 11.100


A specification document must be
– Informal enough for the client; and
– Formal enough for the development team
The specification phase (“what”) should not cross the boundary into the design phase (“how”)
 Do not try to assign modules to process boxes of
DFDs until the design phase
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