In this module we will learn

Transcription

Prof. V.Rajaraman
System Analysis and Design
System Analysis and Design/ Structured systems analysis and design
Learning Objectives
Learning Objectives
In this module we will learn

How to use structured English to precisely specify processes

The terminology used in structured English

Terminology of decision tables and how it is used to
specify complex logic

How to detect errors in decision table specifications

Terminology and use of decision trees

Comparison of structured English, decision tables and
decision trees
V. Rajaraman/IISc. Bangalore
Indian Institute of Science Bangalore
//V1/June 04/1
Prof. V.Rajaraman
Motivation
Motivation

Before designing a system an analyst must clearly understand the logic to be
followed by each process block in a DFD

An analyst’s understanding must be cross checked with the user of the
information system.

A notation is thus needed to specify process block in detail which can be
understood by a user.

Notation used must be appropriate for the type of the application to be modeled.

Different notations are needed to represent repetition structures,complex decision
situation and situations where sequencing of testing of conditions is important

For complex logical procedures a notation is needed which can also be used to
detect logical errors in the specifications.

A tabular structure for representing logic can be used as a communication tool and
can be automatically converted to a program.
V. Rajaraman/IISc, Bangalore
//V1/July 04/1
Process Specification
• Once a DFD is obtained the next step is to precisely specify
the process.
• Structured English, Decision tables and Decision Trees are
used to describe process.
• Decision tables are used when the process is logically
complex involving large number of conditions and alternate
solutions
• Decision Trees are used when conditions to be tested must
follow a strict time sequence.
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M6/LU1/V1/2004
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Structured English
• Structured English is similar to a programming language such
as Pascal
• It does not have strict syntax rules as programming language
• Intention is to give precise description of a process
• The structured English description should be understandable
to the user
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Structured English
if customer pays advance
then Give 5% Discount
else
if purchase amount >=10,000
then
if the customer is a regular customer
then Give 5% Discount
else No Discount
end if
else No Discount
end if
end if
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Decision
Table-example
Same structured English procedure given as decision table
CONDITIONS
Advance payment made
Purchase amt >=10,000
Regular Customer?
RULE1
Y
-
RULE2
N
Y
Y
RULE3
N
Y
N
RULE4
N
N
-
ACTIONS
Give 5% Discount
Give No Discount
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X
-
X
-
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X
X
4
Decision
Table-explanation
• Conditions are questions to be asked
• ‘Y’ is yes,’N’ is no & ‘-’ is irrelevant
• A ‘X’ against the action says the action must be taken
• A ‘-’ against the action says the action need not be taken
Rule 2 in decision table DISCOUNT states:
if no advance payment and purchase amount >=10000
and regular customer then give 5% discount
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Structured English
• Imperative sentences- Actions to be performed should be
precise and quantified
Good Example: Give discount of 20%
Bad Example: Give substantial discount
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Structure English (Contd.)
• Operators -Arithmetic : +, -, /, *
Relational : >, >=, <, <=, =, !=
Logical : and, or, not
Keywords : if, then, else, repeat, until, while, do, case,
until, while, do, case, for, search, retrieve, read, write
• Delimiters – {, }, end, end if, end for
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Decision
Tree-example
The structured English procedure given in 6.1.3 is expressed as a
Decision tree below
Give 5% Discount
Y
Y
C1
C3
N
Y
C2
Give 5% Discount
N
No Discount
N
No Discount
C1: Advance payment made
C2: Purchase amount >=10,000
C3: Regular Customer
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Y = Yes
N = No
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Structured
English-decision Structures
If condition
then
{ Group of statements }
else
{ Group of statements }
end if
Example: if(balance in account >= min.balance)
then honor request
else reject request
end if
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Structured
English-case Statement
Case (variable)
Variable = P: { statements for alternative P}
Variable = Q: { statements for alternative Q}
Variable = R: { statements for alternative R}
None of the above: { statements for default case}
end case
Example : Case(product code)
product code =1 : discount= 5%
product code =2 : discount =7%
None of the above : discount=0
end case
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STRUCTURED
ENGLISH-REPETITION STRUCTURE
for index = initial to final do
{ statements in loop }
end for
Example : Total =0
for subject =1 to subject =5 do
total marks=total marks +marks(subject)
write roll no,total marks
end for
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STRUCTURED
ENGLISH-WHILE LOOP
while condition do
{ statements in loop }
end while
Example : while there are student records left to do
read student record
compute total marks
find class
write total marks, class, roll no
end while
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Example
Update inventory file
for each item accepted record do
{ search inventory file using item code
if successful
then { update retrieved inventory record;
write updated record in inventory file using accepted
record}
else { create new record in inventory file;
enter accepted record in inventory file}
end if
end for
DECISION
TABLE-MOTIVATION
• A procedural language tells how data is processed
• Structured English is procedural
• Most managers and users are not concerned how data is processedthey want to know what rules are used to process data.
• Specification of what a system does is non-procedural.
• Decision Tables are non-procedural specification of rules used in
processing data
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ADVANTAGES
OF DECISION TABLE
•Easy
to understand by non-computer literate users and managers
•Good documentation of rules used in data processing.
•Simple representation of complex decision rules .
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ADVANTAGES
OF DECISION TABLE (Contd.)
• Tabular representation allows systematic validation of
specification detection of redundancy,incompleteness &
inconsistency of rules
• Algorithms exist to automatically convert decision tables to
equivalent computer programs.
• Allows systematic creation of test data
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METHOD OF OBTAINING
DECISION TABLE FROM
WORD STATEMENT OF RULES
EXAMPLE
A bank uses the following rules to classify new accounts
If depositor's age is 21 or above and if the deposit is Rs 100 or more,
classify the account type as A If the depositor is under 21 and the deposit
is Rs 100 or more, classify it as type B If the depositor is 21 or over and
deposit is below Rs 100 classify it as C If the depositor is under 21 and
deposit is below Rs 100 do-not open account
Identify Conditions: Age >= 21 Cl
Deposits >= Rs 100: C2
Identify Actions : Classify account as A, B or C
Do not open account
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DECISION TABLE
FROM WORD STATEMENT
Condition Stub
CODITIONS
Rule 1
Rule 2
Rule 3
Rule 4
C1 : Age >= 21
Y
N
Y
N
C2: Deposit >=100
Y
Y
N
N
A1: Classify as A
X
-
-
-
A2: Classify as B
-
X
-
-
A3: Classify as C
-
-
X
-
-
-
-
X
ACTIONS
A4: Do not open
Account
Action Stub
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DECISION TABLE
NOTATION EXPLAINED
CONDITION
STUB
CONDITION ENTRIES
ACTION
STUB
ACTION ENTRIES
RULE
• 4 Quadrants-demarcated by two double lines
•CONDITION STUB LISTS ALL CONDITIONS TO BE CHECKED
•ACTION STUB LISTS ALL ACTIONS TO BE CARRIED OUT
•LIMITED ENTRY DECISION TABLE:ENTRIES ARE Y or N or -.Y-YES,NNO,-IRRELEVANT(DON’T CARE)
•X against action states it is to be carried out.
•-against action states it is to be ignored.
•Entries on a vertical column specifies a rule
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DECISION TABLE
NOTATION -CONTD
• ORDER OF LISTING CONDITIONS IRRELEVANT
i.e. CONDITIONS MAY BE CHECKED IN ANY ORDER
• ORDER OF LISTING ACTIONS IMPORTANT
• ACTIONS LISTED FIRST CARRIED OUT FIRST
SEQUENTIAL EXECUTION OF ACTIONS
• RULES MAY BE LISTED IN ANY ORDER
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INTERPRETING
DECISION TABLE-ELSE RULE
C1: Is applicant sponsored
C2: Does he have min
qualification
C3: Is fee paid?
R1
R2
Y
Y
Y
Y
Y
N
A1: Admit letter
A2: Provisional Admit
letter
A3: Regret letter
X
-
-
-
X
-
-
-
X
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ELSE
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INTERPRETING
DECISION TABLE-ELSE RULE (Contd.)
• Interpretation
• R1: If applicant sponsored and he has minimum qualifications
and his fee is paid –Send Admit letter
• R2: If applicant sponsored and has minimum qualifications
and his fee not paid send provisional admit letter
• ELSE: In all cases send regret letter.The else rule makes a
decision table complete
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DECISION TABLE
FOR SHIPPING RULES
C1: Qty ordered <= Quantity
in stock?
C2: (Qty in stock-Qty ordered)
<=reorder level
C3: Is the partial shipment ok?
A1:Qty shipped=Qty ordered
A2:Qty shipped=Qty in stock
A3:Qty shipped=0
A4:Qty in stock=0
A5:Back order=qty orderedqty shipped
A6:Initiative reorder procedure
A7: Qty in stockÅQty in
stock-Qty shipped
V. Rajaraman
R1
R2
R3
R4
Y
Y
N
N
N
Y
-
-
-
-
Y
N
X
X
-
-
-
-
X
X
X
-
-
-
X
X
-
X
X
X
X
X
-
-
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EXTENDED ENTRY
DECISION TABLE
Condition Entries not necessarily Y or N
Action entries not necessarily X or Extended Entry Decision Tables(EEDT) more concise
EEDT can always be expanded to LEDT
Example
R1
R2
R3
R4
R5
R6
C1 : Product code
1
1
1
1
1
2
C2 : Customer code
A
B
A
B
C
-
C3 : Order amount
Discount =
V. Rajaraman
<=500 <=500
5%
7.5%
>500
7.5%
M6/LU2/V1/2004
>500
10%
-
-
6%
5%
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MIXED ENTRY
DECISION TABLE
Can mix up Yes, No answers with codes
Rl
R2
R3
R4
R5
Cl : Product code = 1?
C2: Customer code =
C3: Order amount < 500?
A
Y
Y
B
Y
Y
A
N
Y
B
N
Y
C
-
Discount =
5%
7 5%
7 5%
10%
6%
R6
N
5%
Choice of LEDT, EEDT, MEDT depends on ease of communication with user,
software available to translate DTs to programs, ease of checking etc.
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LINKED
DECISION TABLE
Decision table 2
Decision table 1
Salary point=6
Conduct OK?
Diligence OK?
Efficiency OK?
N
Y
Y
Y
e
l
s
e
Go to table 2
No promotion
X
-
X
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Salary point>2
1 yr as class 1
officer
Departmental test
Passed?
Advance to next
salary point
No promotion
Go to Table3
M6/LU2/V1/2004
N
Y
N
N
N
-
Y
-
Y -
N -
X - X
X
-
-
-
X
-
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LINKED
DECISION TABLE
Decision table3
Complete departmental
Course
1 yr since last increment
Advance to next salary
point
No promotion
V. Rajaraman
Y
else
1.Observe that one can branch
between tables
Y
X
-
-
X
2. Whenever complex rules are
given it is a good idea to break
them up into manageable parts
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LOGICAL
CORRECTNESS OF DECISION TABLE
Consider decision table DTI:
Cl: x>60
C2:x<40
Rl
Y
-
R2
.
Y
Al
A2 :
X
-
X
V. Rajaraman
We can expand decision table by
replacing each –by Y & N
M6/LU3/V1/2004
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LOGICAL CORRECTNESS
DT2:
R11
R12
R21
R22
N
Y
Y
Y
Cl: x>60
C2:x<40
Y
Y
Y
N
Al
A2 :
X
-
X
-
X
X
A rule which has no – is an
Elementary rule
DT2 is an Elementary Rule Decision Table (ERDT)
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LOGICAL CORRECTNESS
• A decision table with 1 condition should have 2 elementary rules
• Each elementary rule must be distinct
• Each elementary rule must have distinct action
• If a decision table with k conditions does not have 2k rules
specified
it is said to be incomplete
For example : DT2 does not have the elementary rule C1:N,
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LOGICAL CORRECTNESS
• C2:N.
• It is thus incomplete.
• If the decision table has the same elementary rule occurring
more than once it is said to have multiplicity of specifications
• For Example:In DT2 The rule C1:Y,C2:Y occurs twice.Thus it
has multiplicity of specification
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LOGICAL CORRECTNESS
• If action specified for multiple identical rules are different then it
is called ambiguous specifications
• DT2 has an ambiguity.Rules R11 and R21 are identical but have
different actions
• Ambiguity may be apparent or real
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LOGICAL CORRECTNESS
If an apparently ambiguous specification is real then it is a
contradiction
For example : If C1:(X > 60) = Y and C2:(X > 40) = Y
then X = 70 will satisfy both inequalities.
As two actions are specified for (Cl = Y, C2 = Y) and they
are different the rule is really ambiguous and is called
Contradictory Specification.
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LOGICAL CORRECTNESS
• If all 2k elementary rules are not present in a k condition
decision table is said to be incomplete.
•DT2 (PPT 6.3.1) is incomplete as rule C1:N, C2:N is missing
•Rule C1=N, C2:=N is logically possible as C1=N is X<=60
and C2=N is X >= 40. A value of X = 50 will make C1=N,C2=N
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LOGICAL CORRECTNESS
• Thus DT2 has a real incomplete specification
• A decision table which has no real ambiguities or real
incompleteness is said to be logically correct
• A decision table with logical errors should be corrected
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USE OF KARNAUGH MAPS
• KARNAUGH map abbreviated K-map is a 2 dimensional
diagram with one square per elementary rule
• The k-map of DT2 is
C1
N
C2
N
?
Y
A2
Y
Al
A1,A2
• If more than one action is in one square it is an ambiguous
rule
• If a square is empty it signifies incomplete specification
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USE OF KARNAUGH MAPS
Structured English procedure:
If carbon content<0.7
then if Rockwell hardness>50
then if tensile strength>30000
then steel is grade 10
else steel is grade 9
end if
end if
end if
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USE OF
KARNAUGH MAPS
Decision table-Grading steel
C1:Carbon content <0.7
C2:Rockwell hardness>50
C3 tensile strength>30000
Grade
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Y Y Y N Y N N N
Y Y N N N Y Y N
Y N N N Y Y N Y
10 9 8 7 ? ? ? ?
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KARNAUGH
MAPS – GRADING STEEL
C1 C2
NN
C3
N
7
Y
?
NY
YY
YN
?
9
8
?
10
?
• The 3 conditions are independent
• The decision table is thus incomplete
• Observe that in the Structured English specifications
the incompleteness is not obvious
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DECISION TABLEARREARS MANAGEMENT
R1
R2
R3
R4
R5 R6
Y
N N
-
-
-
C1:Payment in current month
>min.specified payment
C2:Payment in current month>0
C3:Any payment in last 3 months
C4: Actual arrears > 3(min.
Specified payment per month)
-
Y
-
Y
-
N
N
Y
N
Y
-
Y
N
Y N
Y
A1 : Send letter A
A2 : Send letter B
A3 : Send letter C
A4 : Send letter D
A5 : Send letter E
X
-
X
-
X - X
-
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X
X
1
KARNAUGH MAP
C1C2
C3C4
NN
NN
?
NY
YY
YN
A3
A1
A1*
NY
A4
A2A4+
A1A4+
A1A4*
YY
A4
A2
A1
A1A4*
YN
A5
A3
A1
A1A5*
K – Map for decision table
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KARNAUGH MAP
• C1 : x>m C2:x>0 C3:y>0 C4:z>3m
• C3,C4 independent of C1,C2
m>0
C1,C2 dependent
• C1: Y C2: Y x>m, x>0 possible
• C1: Y C2: N x>m, x<=0 not logically possible
• C1: N C2: Y x<=m,x>0 possible
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KARNAUGH MAP
• C1: N C2: N x<=m,x<=0 possible
• Thus C1,C2,C3 C4:NNNN incomplete specification
• BOXES MARKED * NOT LOGICALLY POSSIBLE
• Rules C1 C2 C3 C 4 : NYNY and YYNY logical errors
• Errors to be corrected after consulting users who formulated
the rules
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CORRECT DECISION TABLE
• If users say that for rules C1C2C3C4:NYNY AND NYNY
(marked with + in k-map) the action is A4 and for
C1C2C3C4:NNNN also it is A4, the corrected map is
C1C2
NN
C3C4
NY
YY
NN
A4
A3
A1
NY
A4
A4
A4
YY
A4
A2
A1
YN
A5
A3
A1
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YN
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Impossible rules
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CORRECTED
DECISION TABLE
C1
Y
Y
Y
N
N
N
N
Y
N
N
N
N
C2
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
C3
N
Y
Y
Y
N
Y
N
N
Y
N
N
Y
C4
N
Y
N
Y
N
N
Y
Y
Y
Y
N
N
A1
A1
A1
A2 A3
A3
A4
A4
A4
A5
Action
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A4 A4
18
CORRECTED
DECISION TABLE (Contd.)
Question: Can the number of rules be reduced
Answer : Yes, by combining rules with the same action
Action A1 can be represented by the Boolean expression:
C1C2C3C4 + C1C2C3C4 + C1C2C3C4
= C1C2C3C4 + C1C2C3 (C4+C4)
= C1C2C3C4+C1C2C3 = C1C2C4 + C1C2C3
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REDUNDANCY
ELIMINATION
• Redundancy can be eliminated by systematically applying four
identities of Boolean Algebra
• These identities are
A + A=1
l.A = A
A+A=A
1+A=1
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M6/LU4/V1/2004
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REDUNDANCY
ELIMINATION (Contd.)
• K-map assists in identifying Boolean terms in which One or
more variables can be eliminated
• K-map is constructed in such a way that two boxes which are
physically adjacent in it are also logically adjacent
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2
KARNAUGH
MAP REDUCTION
C1 C2
NN NY YY YN
C3 C4
NN
NY
C1 C2
NN
C3 C4
A4
NN
A4
NY
YY
YN
A4=C1C2C3(C4+C4)=C1C2C3
V. Rajaraman
A4
NY YY YN
A4
A4
A4
YY
YN
A4=C3C4(C1C2+C1C2+C1C2+C1C2)=C3C4
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KARNAUGH
MAP REDUCTION
•
•
•
•
•
Combining 2 adjacent boxes eliminates 1 variable
First and last columns of k-map are logically adjacent
First and last rows are also logically adjacent
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4
KARNAUGH
MAP REDUCTION
C1C2
NN
C3 C4
NY YY YN
A1
A1
NN
NY
YY
C1C2
NN NY YY YN
C3 C4
A2
A2
A1
YN A1
V. Rajaraman
A1
A1
A1
A2
A2
NY
YY
YN
NY YY YN
NN
NN
A1
C3 C4
C1C2
NN
A3
A3
A3
A3
NY
A2
A2
YY
A2
A2
YN
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5
KARNAUGH
MAP REDUCTION (Contd.)
A1=(C3C4+C3C4+C3C4+C3C4).(C1C2+C1C2)=C2(C3+C3)=C2
A2=(C1C2+C1C2)(C3C4+C3C4+C3C4+C3C4)=C2
A3=C1C2C3C4+C1C2C3C4+C1C2C3C4+C1C2C3C4
=C2C3C4(C1+C1)+C2C3C4(C1+C1)
=C2C4(C3+C3)=C2C4
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REDUCING DECISION
TABLES-USE OF K-MAP
This is the K-map corresponding to DT of 6.3.12
C1C2
NN NY
C3C4
NN A4 A3
YY
A1
A4
A4
A4
YY
A4
A2
A1
YN
A5
A3
A1
NY
V. Rajaraman
YN
Boxes marked X correspond to impossible rules.
They can be used if they are useful in reducing rules
Using k-map reduction rules we get
A1 : C1C4+C1C3
A2 : C1C2C3C4
A3 : C1C2C4
A4 : C3C4+C2C3+C2C4
A5 : C2C3C4
M6/LU4/V1/2004
7
REDUCING
DECISION TABLES
REDUCED DECISION TABLE for DT of 6.3.12
C1: Payment in current month >
min specified payment
C2: Payment in current month>0
C3: Any payment in last 3 months
C4: Actual arrears> 3(minimum specified
payment per month)
A: Send letter A
B: Send letter B
C: Send letter C
D: Send letter D
E: Send letter E
V. Rajaraman
Y
-
Y
Y
N N
Y Y
Y -
N
N
N
N
-
N
Y
N
-
Y
Y
-
Y
N
X
-
X
-
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N
- - - X - - X - - X X
- - -
-
X - X
8
EXAMPLE-REDUCTION
OF RULES IN WORD STATEMENT
Rules : Insure Driver if following rules are satisfied
1.
2.
3.
4.
5.
Drivers annual income > 20000 & is married male
Drivers annual income > 20000 & is married and over 30
Drivers annual income <= 20000 & she is married female
Driver is male over 30
Driver is married and age is not relevant
Else do not insure
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M6/LU4/V1/2004
9
EXAMPLE-REDUCTION
OF RULES IN WORD STATEMENT
Conditions:
• C1 : Annual income > 20000
• C2 : Male
• C3 : Married
• C4: Age > 30
Action: Insure or do not insure
V. Rajaraman
M6/LU4/V1/2004
10
DECISION TABLE
FOR INSURANCE RULES
Cl : Annual income> 20000
C2: Male
C3: Married
C4: Age > 30
Y
Y
Y
-
A1:Insure
A2 :Do not insure
Y
Y
Y
X
C1C2
NN
C3C4
N
N
Y
X
-
Y
Y
X
-
X
-
Y
N
X
-
E
L
S
E
X
NY YY YN
NN
A1
NY
V. Rajaraman
A1
A1=C3+C2.C4
YY
A1
A1
A1
A1
YN
A1
A1
A1
A1
M6/LU4/V1/2004
11
REDUCED
DECISION TABLE
C2 : Male
-
Y
C3 : Married
Y
-
C4 : Age > 30
-
Y
X
X
-
-
-
X
Al : Insure
A2 : Do not Insure
ELSE
Reduced rules : Insure if married or male over 30
Observe 5 rules simplified to 2 and 1 condition removed
V. Rajaraman
M6/LU4/V1/2004
12
DECISION TREES
• Used when sequence of testing condition is important
• It is more procedural compared to Decision trees.
Book by II AC on 4/8/04 if available else book by II AC on
5/8/04.If both not available book by sleeper on 4/8/04 if available
else book on
5/8/04 by sleeper.If none available return.
V. Rajaraman
M6/LU5/V1/2004
1
EXAMPLE – DECISION
TREE TO BOOK TRAIN TICKET
Book II AC
Y
C1
N
Book II AC
Y
C2
Book sleeper
Y
N
C3
Book ticket
Y
N
C4
N
Return
V. Rajaraman
M6/LU5/V1/2004
2
EXAMPLE – DECISION
TREE TO BOOK TRAIN TICKET
•
•
•
•
•
C1: Is II AC ticket available on 4/8/04
C2: Is II AC ticket available on 5/8/04
C3: Is sleeper available on 4/8/04
C4: Is sleeper available on 5/8/04
Observe in the tree sequencing of conditions which is
important in this example
V. Rajaraman
M6/LU5/V1/2004
3
DECISION TREES
Decision trees are drawn left to right
Circles used for conditions
Conditions labelled and annotation below tree
Conditions need not be binary
For example:
C1
>=60
GRADE A
>=50
GRADE B
>=40
GRADE C
else
GRADE F
Sometimes Decision trees are more appropriate to
explain to a user how decisions are taken
V. Rajaraman
M6/LU5/V1/2004
4
DECISION TREES
Decision tree for decision table of 6.2.9 [Slide number 25]
Discount=7.5%
YES
C3
A
B
C2
C
Discount=5%
YES
Discount=10%
NO
Discount=7.5%
C3
1
C1
NO
Discount=6%
2
V. Rajaraman
Discount=5%
M6/LU5/V1/2004
5
DECISION TREES
• C1 : PRODUCT CODE
• C2 : CUSTOMER CODE
• C3 : ORDER AMOUNT >500?
• Observe that the 3 alternatives for connection C2 shown as
three branching lines
• SOME PEOPLE FIND DECISION TREE EASIER TO
UNDERSTAND
V. Rajaraman
M6/LU5/V1/2004
6
DECISION TREES
Decision tree equivalent of structured English procedure of 6.3.7
(SLIDE 37) is given below
NO
Grade 7
C1
Grade 8
YES
C1
NO
YES
C1
Grade 9
NO
YES
Grade 10
V. Rajaraman
M6/LU5/V1/2004
7
DECISION TREES
• C1 : Carbon < 0.7
• C2 : Rockwell hardness > 50
• C3: Tensile strength > 3000
•
Observe incompleteness evident in the equivalent Decision
Table is not evident in the Decision tree
• If the testing sequence is specified and is to be strictly
followed the Decision tree is simple to understand.
V. Rajaraman
M6/LU5/V1/2004
8
COMPARISON OF
STRUCTURED ENGLISH,
DECISION TABLES AND DECISION TREES
CRITERION
FOR
COMPARISON
STRUCTURE
D
ENGLISH
ISOLATING
CONDITIONS
& ACTIONS
NOT GOOD
SEQUENCING
CONDITIONS
BY PRIORITY
GOOD
CHECKING FOR
COMPLETENES
S,
CONTRADICTIO
N&
AMBIGUITIES
V. Rajaraman
DECISION
TABLES
BEST
NOT
GOOD
NOT GOOD
BEST
M6/LU5/V1/2004
DECISION
TREES
GOOD
BEST
GOOD
9
WHEN TO USE
STRUCTURED ENGLISH,
DECISION TABLES AND DECISION TREES
Use Structured English if there are many loops and actions
are complex
Use Decision tables when there are a large number of
conditions to check and logic is complex
Use Decision trees when sequencing of conditions is important
and if there are not many conditions to be tested
V. Rajaraman
M6/LU5/V1/2004
10
Prof. V.Rajaraman
SUMMARY OF MODULE 6
1.
Procedures are used to transform input data into processed results.
2.
Procedure can be described in natural English. Such a description is often
ambiguous due to impreciseness of natural English.
Structured English attempts to describe verbal statements made in natural
English more precisely.
Precision is obtained by using ideas of logic and block structuring as in
programming languages.
Decision tables are more appropriate when a large number of conditions are to
be checked in arriving at a set of actions.
In structured English a number of key words are used for representing commonly
used operations. Some important keywords are; search, retrieve, if, then, else,
do, case, while, for.
The important control structures used to describe a process are: Selection
structure (using if then else or case), loop structure (using for, while and repeat
unitl).
3.
4.
5.
6.
7.
8.
Decision tables specify actions to be performed for each combination of results
obtained by testing a set of conditions relevant in a problem.
9.
Decision tables are used for communicating and documenting complex decision
procedures.
10.
In order to obtain a decision table from a word statement, we first isolate in each
sentence a part which specifies the conditions and another part which specifies
the actions to be performed, based on the result of testing the conditions.
Conditions are then grouped in one or more table and the rules are formulated.
11.
It is not advisable to have more than four or five conditions per decision table. If
there are many conditions they are grouped and a set of tables are formulated and
linked.
12.
Limited Entry Decision Tables (LEDT) use only Y or N answers to conditions.
13.
In Extended Entry Decision Tables (EEDT) conditions are formed by combining
the statement in the condition stub with that in the condition entry part of the
decision table. EEDTs are more concise.
Prof. V.Rajaraman
14.
A decision table is said to be complete if it has all possible distinct elementary
rules. If any rule is missing it is incomplete.
15.
If no values can be assigned to the condition variables leading to the missing
rules then the decision table is said to be apparently incomplete. Otherwise it is
really incomplete.
16.
If an elementary rule has more than one action specified, then the decision table
is said to be ambiguous. If the elementary rule is logically impossible, then the
ambiguity is apparent; otherwise, it is real.
17.
A decision table with real ambiguity or incompleteness has a logical error which
should be corrected.
18.
Incompleteness and ambiguity are easily specified by using a two-dimensional
diagram onto which a decision table is mapped. The diagram is called a
Karnaugh may (K-map).
19.
K-maps are also useful to detect redundant rules.
20.
Using basic ideas of Boolean algebra and K-maps, unnecessary conditions and
unnecessary rules are eliminated. The number of conditions to be tested in each
rule can also be minimized by using K-maps.
21.
Pre-processors are available to automatically convert decision tables to program
in a programming language.
22.
Decision trees are used when sequencing of conditions is important and
conditions are to be tested in order of their priority.
23.
Structures English is appropriate when a problem has complex actions and many
loops. Decision tables are appropriate when there are a large number of
conditions to be tested and the logic is complex. Decisiion trees ae preferred
when sequencing of conditions is important.
Prof. V.Rajaraman
Worked Examples
WORKED EXAMPLES
6.1 A bank has the following policy on deposits: On deposits of Rs. 5000 and
above and for three years or above the interest is 12%. On the same deposit
for a period less than 3 years it is 10%. On deposits below Rs. 5000 the
interest is 8% regardless of the period of deposit. Write the above process
using
(i) Structured English
(ii) A decision table
(i) for each deposit do
if deposit >=5000
then if period >= 3 years
then interest =12%
else interest =10%
end if
else interest =8%
end if
end for
(ii)
Deposit >= 5000
Y Y
Period >= 3 years
Y N
Interest
12
10
N
–
8
6.2 An organization maintains an employee file in which each record has
following data:
{ Employee No., employee name, employee gross pay}.
It has been decided to increase the pay as per the following formula:
For pay of Rs. 1000 or less increase 15%.
For pay of more than Rs. 1000 but up to Rs. 2500 increase 10%.
For pay over Rs. 2500 increase 5%.
(i) Write a structured English processing rule corresponding to the above
policies.
(ii) Express the policies as a decision table.
(i)
While employee records left in file do
Read Number, name , gross pay
if gross pay <=1000
then increase = gross pay * 0.15
else if gross pay <= 2500
then increase = gross pay * 0.1
else increase = gross pay * .05
//V1/June 04/1
Prof. V.Rajaraman
Worked Examples
end if
end if
Gross pay = gross pay + increase
Write Number, name, gross pay
end while
(ii) While employee records left in file do
Read Number, name, gross pay
do Table
Gross pay <= 1000
Gross pay <= 2500
Percent increase
Y
–
N
Y
N
N
15
10
5
end table
Gross pay = gross pay*(1+percent increase/100)
Write Number, name, gross pay
end while
6.3 An offshore gas company bills its customers according to the following rate
schedule:
First 500 litres Rs. 10 (flat)
Next 300 litres Rs. 1.25 per 100 litres
Next 30,000 litres Rs. 1.20 per 100 litres
Next 100,000 litres Rs. 1.10 per 100 litres
Above this Re. 1.00 per 100 litres
The input record has customer identification, name and address, meter
reading, past and present. Write a structured English procedure to obtain a
bill for the customer.
While record left in customer file do
Read customer id, name, address, past meter reading, new meter reading
Consumption = new meter reading – old meter reading
if consumption <= 500 then charge =10
else if consumption <=800
then charge = 10 + (consumption – 500) * 0.0125
else
if consumption <= 30800
then charge = 13.75
+(consumption – 800) * 0.012
else
if consumption <=130800
then charge = 373.75 + (consumption – 30800) * 0.011
else charge = 1473.75 + (consumption – 130800) * 0.01
end if
//V1/June 04/2
Prof. V.Rajaraman
Worked Examples
end if
end if
end if
write customer id, name, address, past meter reading, new meter reading,
consumption, charge
end while
6.4 Refer to users requirements stated in exercise 6.4 of Question bank. Develop
the processing rules in structured English for the stores process shown in Fig.
5.8.
for each customer requisition do
if (qty. requested < qty. in stock ) then
{
qty. issued = qty. requested.
qty. in stock = qty. in stock – qty. issued
send( customer id , qty. issued ) to accounts process}
end if
if (qty. in stock <= reorder level) then
send reorder request to purchase.
end if
if (qty. requested = qty. in stock) then
{
qty. issued = qty. requested
qty in stock = 0;
send (customer id, qty issued) to accounts
send reorder request to purchase }
end if
if (qty. requested > qty. in stock) then
if (partial qty. acceptable)
then {
qty issued = qty. requested
qty in stock = 0;
send (customer id , qty issued) to accounts
send reorder request to purchase.
write (customer id, (qty. requested – qty. issued ))
in file}
else
{qty. issued = 0;
send reorder request to purchase
write (customer id, qty requested) in back order file }
end if
end if
end for
//V1/June 04/3
Prof. V.Rajaraman
Worked Examples
for each item (with specified item code and qty. accepted note) received from
inspection do
qty. in stock ( item code)
= qty. in stock ( item code) + qty. accepted
end for
6.5 Refer to Exercise 6.4 in Question Bank. Develop the processing rules in
structured English for the purchase process of Fig. 5.9.
for each discrepancy note received from the receiving office do
{ intimate specified vendor
enter discrepancy in the discrepancy file }
end for
for each goods rejected note received from the inspection office do
{ intimate specified vendor
enter rejected items note in items rejected file }
end for
for each reorder advice or new requisition received for an item from stores do
{ Refer to item file to find vendor details and order qty.
send order to specified vendor
enter order in order file }
end for
6.6. State the processing rules in structured English for the various processes in
the data flow diagram for the hostel DFD described in Module 5
Mess Process
for each absence note do
Read student charge record from student charge file (using student number
as key)
Add absence days to absence field
Write student charge record in student charge file
end for
for each extras note do
Read student charge record
Append extras code and quantity to record
Write student charge in student charge file
end for
Billing Process
While student charge records left in student charge file do
Read student charge record from student charge file
No. of days to charge = no. of days in a month – no. of days absent.
Monthly charge = no. of days to charge * daily rate
Total extras charge = 0
for each extra item do
//V1/June 04/4
Prof. V.Rajaraman
Worked Examples
extras charge (code) = extra qty. * charge (code)
end for
Add extra charge to total extra charge
Amount to be billed = no. of days to charge * daily rate + total extras
charge
Student bill record = student charge record + daily rate, no. of days
charged, monthly charge, extras charge (code) , total extras charge ,
grand total to pay
Write student bill record
end while
(Note: It is assumed that the daily rate, no. of days in a month and extras charge
for each extras code is stored in the billing process as an internal data record.)
Payment Reconciliation Process
for each student Bill record do
Store student Bill record in Bill file
end for
for each payment received do
Read bill record of student from Bill file
if amount paid = grand total to pay
then balance due = 0
else balance due = (grand total to pay – amount paid)
Store bill record in unpaid bill file
end if
end for
On payment due date, (due date + 10), (due date + 20) do
While records left in unpaid Bill file do
if balance due > 0
then send overdue notice,
end if
end while
On (payment due date + 30) do
While records left in unpaid bill file do
if balance due > 0
then send message to warden
end if
end while
6.7
The policy followed by a company to process customer orders is given by the
following rules:
(i) If the customer order <= that in stock and his credit is OK, supply his
requirement.
(ii) If the customer credit is not OK do not supply. Send him an intimation.
//V1/June 04/5
Prof. V.Rajaraman
Worked Examples
(iii) If the customer credit is OK but items in stock are less than his order,
supply what is in stock. Enter balance to be sent in back-order file.
Obtain a decision table for above policy
Order <= stock
Credit OK
Y
Y
Y
N
N
Y
N
N
Supply order
Credit not OK
Do not supply
Supply stock
Enter (order – stock)
In back Order file
X
–
–
–
–
–
X
–
–
X
X
–
–
–
X
–
Observe that the last rule is not specified in the statement of rules. This has been
added to complete the table.
6.8 Obtain a decision table to decide whether on a given date an employee in an
organization has completed one year’s service or not.
Let date of joining be DJ/MJ/YJ (Day/Month/Year)
Let today’s date be DT/MT/YT (Day/Month/Year)
If (YT – YJ)
If (MT – MJ)
>1
–
=1
>0
=1
=0
If (DT – DJ)
–
–
>= 0
E
L
S
E
Yes
Yes
No
One year’s service Yes
6.9 Obtain a decision table corresponding to the structured English procedure given
in worked example 6.4of decision table
for each customer requisition do decision table
decision table
//V1/June 04/6
Prof. V.Rajaraman
Worked Examples
qty requested < qty in stock
qty requested = qty in stock
qty requested > qty in stock
(qty in stock – qty requested)
<= reorder level
Partial order OK?
Y
–
–
Y
–
Y
–
–
–
–
Y
–
–
–
Y
–
Y
–
–
N
–
–
N
Y
–
qty issued = qty requested
qty issued = qty in stock
qty in stock = (qty in stock – qty issued)
qty in stock = 0
Send customer id,qty issued to account process
qty issued = 0
Send reorder request to purchase process
Write (customer id, qty requested – qty issued)
in back order file
Write (customer id, qty requested) in back
order file
X
–
X
–
X
–
X
X
–
–
–
– –
X –
X –
– X
X X
–
X
–
X
X
–
X
X
–
X
–
X
–
–
–
–
–
X
–
–
–
X
–
–
for each item with specified item code and qty accepted note
received from inspection do
qty in stock ( item code) =
qty in stock ( item code) + qty. accepted
end for
6.10 Obtain a decision table for an automatic stamp vending machine with the
following specifications:
(i) To dispense 20, 15, 10, 5 paise stamps
(ii) To accept 50, 25, 10, 5 paise coins
(iii) Do not return change if it is necessary to return more than two coins of
the same denomination. In such a case return the customer’s coin and
turn on “no change” light.
The machine should dispense a stamp, the right amount of change tendered,
no stamp available, no change available, etc.
Table 1: Select Stamp
Amount tendered
Stamp requested available?
Amount insufficient
< Stamp cost = Stamp cost > Stamp cost
–
Y
Y
X
–
–
–
N
–
//V1/June 04/7
Prof. V.Rajaraman
Return amount
‘No stamp’ light on
Dispense stamp
Go to Table 2
Stop
X
–
–
–
X
Worked Examples
–
–
X
–
X
–
–
X
X
–
X
X
–
–
X
Table 2: Make Change
Amount tendered
Stamp cost
25 ps. Available?
10 ps. Available?
5 ps. Available
No of 25 ps. Returned
Dispense stamp
No. change light on
Return amount
Stop
50
20
>=1
–
>=1
50
20
–
>=2
>=2
50
15
>=1
>=1
–
50
15
>=1
–
>=2
1
–
1
X
–
–
X
–
2
2
X
–
–
X
1
1
–
X
–
–
X
1
–
2
X
–
–
X
50 50 50 25 25
10
5
5 20 15
>=1 >=1 >=1 – –
>=1 >= 2 >=1 – >=1
>=1 – >=2 >=1 –
1
1
1
X
–
–
X
1
2
–
X
–
–
X
1
1
2
X
–
–
X
–
–
1
X
–
–
X
–
1
–
X
–
–
X
25
15
–
–
>=2
25
10
–
>=1
>=1
25
5
–
>=2
–
25
5
–
>=1
>=2
10
5
–
–
>=1
E
L
S
E
–
–
2
X
–
–
X
–
1
1
X
–
–
X
–
2
–
X
–
–
X
–
1
2
X
–
–
X
–
–
1
X
–
–
X
–
–
–
–
X
X
X
6.11 Obtain the decision table to be used by a person to enter the office of a manager.
The conditions to be checked are:
Door open? Ring sign on? Enter sign on? Door locked?
The actions a person takes are:
Ring bell, enter, wait, leave.
After obtaining the decision table, ensure that it has no logical errors and
that it is in minimal form.
C1: Door open?
C2: Ring sign on?
C3: Enter sign on?
C4: Door locked?
Ring bell
R1
N
N
N
N
R2
N
N
N
Y
–
–
R3
N
N
Y
N
R4
N
N
Y
Y
R5
N
Y
N
N
R6
N
Y
N
Y
– – X –
R7
N
Y
Y
N
R8
N
Y
Y
Y
R9
Y
N
N
N
X
–
–
R10 R11 R12 R13 R14 R15
Y Y Y Y Y Y
N N N Y Y Y
N Y Y N N Y
Y N Y N Y N
?
–
?
X
?
X
R16
Y
Y
Y
Y
?
//V1/June 04/8
Prof. V.Rajaraman
Enter
Wait
Leave
–
–
X
A1
–
–
X
A1
X – – –
– – X –
– X – X
A2 A1 A3 A1
X
–
–
A4
–
–
X
A1
Worked Examples
– ? X ? – ? X
– ? – ? X ? –
X ? – ? – ? –
A1
A2
A3
A4
?
?
?
Rules R10, R12, R14, R16 have conditions “Door open” and “Door locked”
simultaneously true. These rules are thus impossible. Observe these are four
distinct actions. The table is mapped on a K-map (Fig. S6.11)
NN
NY
YY
YN
NN
A1
A3
A3
A1
NY
A1
A1
YY
A1
A1
YN
A2
A4
A4
A2
Fig S6.11 k-map for solution 6.11
Decision table with redundancies removed
Decision Table with removed (Condition C1 redundant)
C2: Ring on?
C3: Enter on?
C4: Door locked?
–
–
Y
N
N
–
N
Y
N
Y
N
N
Y
Y
N
Ring bell
Enter
Wait
Leave
–
–
–
X
A1
–
–
–
X
A1
–
X
–
–
A2
X
–
X
–
A3
X
X
–
–
A4
6.12 In installment buying where payments are made on a weekly basis the action taken on
“an account goes into arrears” is a crucial aspect of the operation. Table
S6.12 illustrates a simplified arrears procedure. Answer the following
questions:
(i) Are all elementary rules logically possible?
//V1/June 04/9
Prof. V.Rajaraman
(ii)
(iii)
(iv)
(v)
(vi)
Worked Examples
Is the table complete?
Has the table any ambiguities?
Are there logical errors in the table? If yes, point them out.
Use reasonable assumptions and correct the table.
Remove any redundancies in the corrected table (Table S6.12).
Table S6.12 A Simplified Arrears Procedure
C1: This week’s cash > weekly rate
C2: This week’s cash > 0
C3: Any cash during last month
C4: Arrears . >2 * weekly rate
C5: Arrears >4 * weekly rate
Y
–
–
–
N
Y
–
–
–
Y
N
Y
–
Y
N
N
Y
–
N
–
–
–
N
–
N
–
–
N
–
Y
–
N
Y
N
–
–
N
Y
Y
N
–
N
Y
–
Y
Send arrears letter A
Send arrears letter B
Send arrears letter C
Send arrears letter D
Notify accounts
Take special action
–
–
–
–
X
–
X
–
–
–
–
–
–
X
–
–
–
–
–
–
–
–
X
–
–
–
X
–
–
–
–
–
–
–
–
X
–
–
–
–
X
–
–
–
–
X
–
–
–
–
–
–
–
X
A1 A2 A3 A1 A4 A5 A1 A6 A5
K-map for the decision table
C1C2
C1C2
YY
NN NY
A4
A1
A4
A4
A3
A4
A6
A3
YN
A1
C3C4
NN
NY
YY
A1
A4
A1
A4
A1
A1
C3C4
YN
NN
NY
YY
A5
A5
A5
?
A2
A5
A2
YN
NN
NY
YY
A1
YN
C5 = N
C5=Y
Fig S6.12
Assume weekly rate >0
Impossible rule: C1 = Y
C2 = N
Impossible rule: C4 = N
C5 = Y
K- map (Fig. S 9.10) has incompleteness marked by ?
C1
C2
C3
C4
C5
//V1/June 04/10
Prof. V.Rajaraman
N
Y
Y
Y
Worked Examples
Y
Logically contradictory rules
C1
C2
C3
C4
C5
N
N
Y
Y
Y
Y
Y
Y
Y
Y
N
N
N
N
N
N
Y
N
Y
Y
N
N
N
N
Y
If in all these cases we take action to notify accounts (Action A1) then the K- map becomes the
one shown in Fig. S9.11
A1 = C3. C4 + C1 . C5 + C2 . C3 . C5 + C1 . C3 + C1 . C2 . C3 . C5
A2 = C1 . C3 . C5
A3 = C1 . C2 . C3 . C4 . C5
A4 = C2 . C3 . C5
A5 = C1 . C3 . C5 + C2 . C4 . C5
A6 = C2 . C3 . C4 . C5
C1C2
C3C4
NN
NY
YY
YN
NN
NY
YY
A4
A1
A1
A4
A1
A1
A6
A1
A3
A1
YN
A1
A1
C5=N
Fig S.6.13
C1C2
NN
C3C4
NY
YY
YN
NN
NY
YY
//V1/June 04/11
Prof. V.Rajaraman
A5
A5
A1
A5
A1
A2
Worked Examples
C5=Y
FigS6.14
C1: This week’s cash > weekly rate
C2: This week’s cash > 0
C3: Any cash during last month
C4: Arrears . > 2 * weekly rate
C5: Arrears > 4 * weekly rate
–
–
Y
N
–
Y
–
–
–
N
–
Y
N
–
N
Y
–
N
–
–
N
Y
Y
–
Y
Y
–
Y
–
Y
N
Y
Y
Y
N
–
N
N
–
N
N
–
N
–
Y
–
N
–
Y
Y
–
N
Y
Y
N
Notify accounts
Take special action
–
–
–
–
X
–
–
–
–
–
X
–
–
–
–
–
X
–
–
–
–
–
X
–
–
–
–
–
X
–
X
–
–
–
–
–
–
X
–
–
–
–
–
–
X
–
–
–
–
–
–
–
–
X
–
–
–
–
–
X
–
–
–
X
–
–
6.13 The policy followed by a company to process customer orders is given by the
following rules:
(i)
If the customer order ≤ that in stock and his credit is OK, supply his
requirement.
(ii)
If the customer credit is not OK do not supply. Send him an intimation.
(iii) If the customer credit is OK but items in stock are less than his order, supply
what is in stock. Enter the balance to be sent in a back-order file.
Obtain a decision table for the above policy.
C1 : Customer order <= Item in the stock
C2 : Customer credit ok
Y
Supply requirement
//V1/June 04/12
Prof. V.Rajaraman
Worked Examples
C2
Y
Do not supply send intimation
N
C1
N
Supply what is in the stock. Enter balance in
the back order file
Y
N
C2
Do not supply send intimation
6.14 Obtain a decision tree to be used by a person to enter the office of a manager.
After obtaining the decision table, ensure that it has no logical errors and that it is
in minimal form.
C1 : Door open
C2 : Ring sign on
C3 : Enter sign on
C4 : Door locked
Y
Ring bell and enter
C3
Y
N
N
N
Y
C2
Y
C1
N
C3
N
C4
Y
Ring bell and wait
Enter
Leave
Leave
Observe that C1 is not relevant and not clear in the Decision tree
//V1/June 04/13
Prof. V.Rajaraman
Worked Examples
6.15 A University has the following rules for a student to qualify for a degree with
Physics as the main subject and Mathematics as the subsidiary subject:
(i)
he should get 50% or more marks in Physics and 40% or more marks in
Mathematics.
(ii)
If he gets < 50% marks in Physics, he should get 50% or more marks in
Mathematics. He should, however, get at least 40% marks in Physics.
(iii) If he gets < 40% marks in Mathematics and 60% or more marks in Physics,
he is allowed to reappear in Mathematics examination only so that he can
qualify.
Obtain a decision tree for the above problem
Pass
Y
C2
Y
N
C1
C4
Appear in mathematics
Y
N
N
Y
C3
Fail
C5
Y
Pass
N
Fail
N
Fail
//V1/June 04/14
Prof. V.Rajaraman
Worked Examples
Pass
>=50
>=50
C2
>=40
Pass
< 40
Repeat math
C1
>=40
>=60
< 40
Fail
(An incorrect tree. This is not correct as rule ii not correctly interpreted)
C1 : Physics Marks
C2 : Math marks
C3 : Math marks >=50%
CORRECTED DECISION TREE
>=50
C1
Pass
Fail
C2
>=40
Pass
C3
Fail
>=60
C2
<40
Pass
Repeat math
Fail
//V1/June 04/15
Prof. V.Rajaraman
Worked Examples
6.16 You want to go to Delhi from Bangalore. There are three flights per day; early
morning, late morning and evening. You would like to go on 21.4.04 by early
morning flight. If it is not available you will take the late morning flight or evening
flight in that order. If neither is available you are willing to take any flight on
22.4.04 but prefer early and late morning flights., Obtain a decision tree for this
word statement. Is decision table suitable for this problem? If not why?
Book ticket
C1
N
Y
Book ticket
Y
C2
Book ticket
N
Y
C3
Book ticket
N
Y
C4
Book ticket
N
Y
C5
Book ticket
N
Y
C6
N
No ticket available
C1 : Is ticket available on early morning flight on 21/4/04
C2 : Is ticket available on late morning flight on 21/4/04
C3 : Is ticket available on evening flight on 21/4/04
C4 : Is ticket available on early morning flight on 22/4/04
C5 : Is ticket available on late morning flight on 22/4/04
C6 : Is ticket available on evening flight on 22/4/04
//V1/June 04/16
Prof. V.Rajaraman
System Analysis and Design/Structured Systems Analysis and Design Multiple Choice Questions
6.1
Structured English is used to describe
a. how programs are to be written
b. processes in a DFD in a reasonably precise manner
c. how DFDs are used in data processing
d. data flows in DFD
6.2
Structured English is a
a. structured programming language
b. description of processes in simple English
c. method of describing computational procedures reasonably precisely
in English
d. natural language based algorithmic language
6.3
The objective of using structured English is to
a. describe computational procedures reasonably precisely which can be
understood by any user
b.
expand a DFD so that a user can understand it
c. develop algorithms corresponding to processes in a DFD
d. ease writing programs for DFDs
6.4
Structured English description of processes
(i) should be understandable to a user of a computer based system
(ii) should be understandable to a programmer
(iii) can be descriptive in nature
(iv) should be translatable by a compiler
a. i and iii
b. ii and iv
c. i, ii and iv
d. i and ii
6.5
A decision table is
a. a truth table
b. a table which facilitates taking decisions
c. a table listing conditions and actions to be taken based on the testing of
conditions
M6/V1/July 04/1
Prof. V.Rajaraman
d. a table in a Decision Support System
6.6
A decision table
a. has a structured English equivalent representation
b. cannot be represented using structured English
c. does not have an equivalent algorithmic representation
d. cannot be used to represent processes in a DFD
6.7
A decision table is preferable when the number of
a. conditions to be checked in a procedure is small
b. conditions to be checked in a procedure is large
c. actions to be carried out are large
d. actions to be carried out are small
6.8
Select from the following list which are appropriate to use in structured
English
description
of
a
process
(i)process inventory records
(ii)find the sum of outstanding billed amounts
(iii)check if outstanding amount >= Rs. 5000
(iv)check if stock is low
a. i and ii
b. i and iii
c. iii and iv
d. ii and iii
6.9
Structured English statements must be
a. short and clear
b. specified quantitatively
c. specified qualitatively
d. detailed and descriptive
6.10 Select statements from the following list which may be used in structured
English
(i)if marks are too low fail student
(ii)if marks >=60 enter first class
(iii)if average height select candidate
M6/V1/July 04/2
Prof. V.Rajaraman
(iv)if weight < 40 kg. reject candidate
a. i and ii
b. ii and iii
c. iii and iv
d. ii and iv
6.11 Select
correct
decision
structures
from
the
following
(i)if total marks>=75
then enter distinction in student record
end if
(ii) if
total marks >=50
then enter pass in student record
else enter fail in student record
end if
(iii) if
total marks >=60
then enter first class in student record
else if total marks>= 50
then enter second class in student record
else
enter fail in student record
end if
end if
(iv) if
attendance <30%
then
do not admit in examination
else
a. ii and iii
b. i and ii
c. iii and iv
d. i and iv
M6/V1/July 04/3
Prof. V.Rajaraman
6.12 The following structured English procedure is incorrect because
if balance in account <=0
then
{issue exception note to dept.
mark “stop future issues” in
departments record}
else
if balance in account <minimum balance
then
{ issue item to dept.
issue warning to dept.}
end if
end if
a. end if in second if is not needed
b. nesting of ifs is not correct
c. no action is specified when balance in account >=minimum balance
d. the value of minimum balance is not specified
6.13 The
following
structural
English
is
incorrect
because
case (income slab)
Income slab =1 :
tax= 10%
Income slab =2 or 3 :
Income slab =5 :
tax= 20%
tax= 30%
end case
a. no action is specified for income slab of 4
b. income slab has to be rupees
c. income slab =2 or 3 is wrong
d. number of cases is too small
M6/V1/July 04/4
Prof. V.Rajaraman
6.14
The following structured English procedure is incorrect because
case (code)
Code=2 : if purchase amount >=5000
then discount=5%
Code=1 :discount=2%
Code=3 :if purchase amount >=4000
then discount =2%
else if code=4
then discount =5%
end if
None of the above codes : discount=0
end case
a. code=2 should appear after code=1
b. if statement cannot be used within a case
c. code=4 should not be used in the action for code=3
d. The statement is correct
6.15 The
following
while
structure
is
wrong
because
balance =500
while balance <=1000 do
Write (amount due – balance)
Read next record
end while
a. read must appear before write
b. this loop will never terminate
c. no read allowed in a loop
d. the contents of next record is not known
6.16 Structured English description of data processing is a
a. non-procedural specification
b. procedural specification
M6/V1/July 04/5
Prof. V.Rajaraman
c. purely descriptive specification
d. very imprecise specification
6.17 Decision table description of data processing is
a. non-procedural specification
b. procedural specification
c. purely descriptive specification
d. very imprecise specification
6.18 In the following word statement the conditions are:“if a student gets 50
marks or more in mathematics and 40 marks or more in English he
passes the examination, otherwise he fails”
a. student passes the examination
b. student fails the examination
c.
student gets 50 marks or more in mathematics
d. student mathematics marks >= 50 and student English marks
6.19 In the following word statement the actions are“if a student gets 50 marks
or more in mathematics and 40 marks or more in English he passes the
examination,
otherwise
he
fails”
(i)student passes the examination
(ii)student fails the examination
(iii)student gets 50 marks or more in mathematics
(iv)student mathematics marks >= 50 and student English
marks >= 40
a. i and ii
b. i and iii
c. ii and iii
d. iii and iv
6.20 In a limited entry decision table the condition stub
a. lists X or – corresponding to actions to be executed
b. lists the conditions to be tested
c. has Y or N or – entries
d. lists the actions to be taken
M6/V1/July 04/6
Prof. V.Rajaraman
6.21 In a limited entry decision table the condition entries
a. list X or – corresponding to actions to be executed
b. list the conditions to be tested
c. have Y or N or – entries
d. list the actions to be taken
6.22 In a limited entry decision table the action stub
a. lists X or – corresponding to actions to be executed
b. lists the conditions to be tested
c. has Y or N or – entries
d. lists the actions to be taken
6.23 In a limited entry decision table the action entries
a. list X or – corresponding to actions to be executed
b. list the conditions to be tested
c. have Y or N or – entries
d. list the actions to be taken
6.24 In a limited entry decision table the condition entries may be
a. Y or N only
b. Y, N or –
c. A binary digit
d. Any integer
6.25 In a limited entry decision table a—entry against a condition signifies
that
a. the outcome of testing the condition is irrelevant
b. it is an important condition
c. the condition should be tested
d. the condition is a Boolean condition
6.26 A rule in a limited entry decision table is a
a. row of the table consisting of condition entries
b. row of the table consisting of action entries
c. column of the table consisting of condition entries and the
corresponding action entries
M6/V1/July 04/7
Prof. V.Rajaraman
d. columns of the tables consisting of conditions of the stub
6.27 The conditions in the condition stub of a limited entry decision table
a. must be in sequential order
b. must be in the order in which they are to be tested
c. may be in any order
d. must be in the order in which they are to be executed
6.28 The actions in the action stub of a limited entry decision table
a. must be in sequential order
b. must be in the order in which they are to be tested
c. may be in any order
d. must be in the order in which they are to be executed
6.29 A X against an action in an action row signifies that the
a. action is not to be taken
b. action is to be taken
c. action is important
d. action is not important
6.30 A—against an action in an action row signifies that the
a. action is not to be taken
b. action is to be taken
c. action is important
d. action is not important
6.31 An extended entry decision table has
a. only Y, N or – entries
b. entries which extend the condition
c. questions asked extended into the condition entry part of the table
d. only numerical entries
6.32 An extended entry decision table
a. has no limited entry equivalent
b. cannot be replaced by a table with only Y, or – entries
c. may have Yes, No answers to conditions
d. can always be converted to an equivalent limited entry decision tabl
M6/V1/July 04/8
Prof. V.Rajaraman
6.33 An extended entry decision table is
a. very difficult to understand
b. quite concise compared to a limited entry decision table developed for
the same task
c. large compared to a limited entry table developed for the same task
d. is not very often used
6.34 A mixed entry decision table
a. may have some conditions with Y, N, or – entries
b. may not have any Y, N, or – entry
c. may have only non-numerical entries
d. may
mix
numerical
and
non-numerical
entries
Given a decision table “test” shown below
R1
R2
R3
C1
Y
N
Y
C2
N
–
Y
A1
X
––
A2
–
X
–
A3
X
–
X
Decision table–“test”
Answer the following questions:
6.35 Rule R1 is interpreted as follows:
a. If C1 is TRUE and C2 is FALSE then perform action A2
b. If C1 is TRUE and C2 is FALSE then perform action A1 and then
action A2
c. If C1 is TRUE and C2 is FALSE then perform action A3 and then
action A1
d. If C1 is TRUE and C2 is FALSE then perform action A1 and then
action A3
6.36 Rule R3 is interpreted as follows:
M6/V1/July 04/9
Prof. V.Rajaraman
a. If C1 is TRUE and C2 is TRUE then perform action A1 and A
b. If C1 is TRUE or C2 is TRUE then perform action A3
c. If C1 is TRUE and C2 is TRUE then perform action A1 or A2
d. If C1 is TRUE and C2 is TRUE then perform action A3
6.37 Structured English equivalent of the decision table “test” are given below
(i) if C1 TRUE
then if C2 TRUE
then do A3
else do A1 and A3
end if
else do A2
end if
(ii) if C1 FALSE
then do A2
else if C2 TRUE
then do A3
else do A1 and A3
end if
end if
(iii)if C2 TRUE
then if C1 TRUE
then do A3
else do A2
end if
else do A1 and A3
end if
(iv)if C2 FALSE
then if C1 TRUE
then do A1 and A3
M6/V1/July 04/10
Prof. V.Rajaraman
else do A2
end if
else do A3
end if
Which of the following are correct?
a. i and iii
b. i and ii
c. iii and iv
d. ii and iv
6.38 Structured English equivalents of decision table “test” are given below.
Pick the right one
(i)if C1 TRUE and C2 FALSE then R=1 end if
if C1 FALSE then R=2 end if
if C1 TRUE and C2 TRUE then R=3 end if
case (R)
R=1; perform actions A1 and A3
R=2; perform action A2
R=3; perform action A3
end case
(ii)if C1 TRUE and C2 FALSE then perform actions A1,
A3 end if
if C1 FALSE then perform action A2 end if
if C1 TRUE and C2 TRUE then perform action A3 end
if
(iii)case (C1 TRUE and C2 FALSE) Rule R1
case (C1 FALSE) Rule R2
case (C1 TRUE and C2 TRUE) Rule R3
end case
(iv)if C1 TRUE and C2 TRUE then do Rule R3 end if
M6/V1/July 04/11
Prof. V.Rajaraman
if C1 TRUE and C2 FALSE then do Rule R1 end if
if C1 TRUE then do Rule R2 end if
a. i and ii
b. i and iii
c. ii and iii
d. iii and iv
a.
The Elementary Rule Decision Table equivalent of decision table “test” is
C1
Y
N
Y
C2
N
N
Y
A1
X
–
–
A2
–
X
–
A3
X–
b.C1 Y
c.
X
N
Y
C2
N
Y
Y
A1
X
–
–
A2
–
X
–
A3
X
–
X
C1
Y
N
N
Y
C2
N
N
Y
Y
A1
X
–
–
–
A2
–
X
X
–
X–
–
X
A3
M6/V1/July 04/12
Prof. V.Rajaraman
d. C1
Y
N
N Y
C2
N
N
Y
Y
A1
X
–
–
–
A2
–
X
–
–
A3
X
–
X
X
6.39 The decision table “test” is
a. ambiguous
b. contradictory
c. incomplete
d. complete
Answer the following referring to the decision table “test2”
R1
R2
C1 : x <= 50
N
–
C2 : x >= 70
–
N
A1
X
–
A2
–
X
Decision Table: “test2”
6.40 Decision table “test2” is
a. really incomplete
b. complete
c. apparently incomplete
d. apparently complete
6.41 Decision table “test2”
a. has a real ambiguity
b. has an apparent ambiguity
c. is logically correct
M6/V1/July 04/13
Prof. V.Rajaraman
d. is incomplete
C1
N
–
C2
–
N
A1
Y
–
A2
Y
DECISION TABLE “testing”–
6.42 Decision
table
“testing”
can
be
made
complete
(i)by putting an ELSE rule
(ii)is as it is complete and does not need any more rules
(iii)by specifying actions when C1 = Y and C2 = Y
(iv)by specifying actions when C1 = N and C2 = N
a. (i), (ii)
b. (i), (iii)
c. (ii), (iii)
d. (ii), (iv)
6.43 The
K-map
equivalent
of
C1
a.
C2
table
“test2”
is
C1
Y
Y
N
decision
A2
N
C2
Y
N
A1
Y
A1
A2
A1
N
A2
A1
b.
M6/V1/July 04/14
Prof. V.Rajaraman
c.
d.
C1
Y
C1
N
Y
C2
N
C2
Y
N
A2
A1
Y
A1,A2
N
6.44
The
following
structured
if
A1
A2
decision
English
table
A2
equivalent
statement
of
the
is
C2 TRUE
then if
C1
TRUE
then do
A3
else
do
A2
do
A1 and A3
end if
else
end if
a.
b.
C1
Y
Y
N
C2
Y
N
–
A1
–
–
X
A2
–
X
–
A3
X
–
X
C2
Y
Y
N
M6/V1/July 04/15
Prof. V.Rajaraman
c.
d. C1
6.45
C1
Y
N
N
A1
–
–
X
A2
–
X
–
A3
X
–
X
C1
Y
N
–
C2
Y
Y
N
A1
–
–
X
A2
–
X
–
A3
X
–
X
Y
N
Y
C2
Y
Y
N
A1
–
–
X
A2
–
X
–
A3
X
–
X
The decision table equivalent of the following structured English
statement
if
is
balance in account <=0
then{issue exception note to dept. and mark “stop future issues”}
else if balance in account <min. balance
then {issue item to dept.
issue warning to dept.}
M6/V1/July 04/16
Prof. V.Rajaraman
else {issue item to dept.}
end if
end if
C1=balance in account <=0;
C2=balance in account < min. balance
A1=issue exception note and mark “no future issues”
A2=issue item to dept
A3=issue warning to dept.
a.
b.
c.
C1
Y
N
N
C2
–
Y
N
A1
X
–
–
A2
–
X
X
A3
–
X
–
C1
Y
N
N
Y
C2
N
Y
N
Y
A1
X
–
–
–
A2
–
X
X
X
A3
–
X
–
–
C1
N
N
N
C2
–
Y
N
A1
X
–
–
A2
–
X
X
A3
–
X
–
M6/V1/July 04/17
Prof. V.Rajaraman
d.
C1
Y
N
Y
C2
N
Y
N
A1
X
–
–
A2
–
X
X
A3
–
X –
6.46 The decision table given in answer (a) of question 9.4.3 is
a. incomplete
b. apparently ambiguous
c. has contradictory specifications
d. logically complete
6.47 The rule C1=Y, C2=Y in the decision table given in answer (a) of
question 6.3.7 is
e. logically impossible
f. logically possible
g. has no action specified
h. has multiple actions specified
6.48 If min. balance > 0 then the rule C1=Y, C2= – in the decision table given
in answer (a) of question 6.3.7 may be replaced by the rule
i. C1=Y, C2=N
j. C1=Y, C2=Y
k. C1= –, C2=Y
l. C1= –, C2=N
6.49 The actions of a decision table are mapped on a K-map shown be
The boxes marked X denote impossible rules
C1C2
C3
NN
NY
YY
Y
A1
A1
A2
N
A1
A2
A2
YN
M6/V1/July 04/18
Prof. V.Rajaraman
The rule for action A1 may be represented by the following minimal
Boolean expression
a. C1.C2 + C1.C2.C3
b. C1.C2.C3 + C1.C3
c. C1.C3 + C2
d. C1.C3 + C2.C1
6.50
The following decision table may be replaced by its best equivalent
shown
a.
b.
below:
C1
N
C2
N
N
Y
Y
Y
Y
N
N
C3
Y
N
N
Y
Y
N
N
Y
A1
X
–
–
X
–
–
X
X
A2
–
X
X
–
X
X
X
X
C1
N
N
Y
Y
C2
–
–
Y
N
C3
Y
N
–
–
A1
X
–
–
X
A2
–
X
X
X
C1
–
Y
N
Y
C2
–
–
–
N
C3
N
–
Y
–
A1
–
–
X
X
N
N
N
Y
Y
Y
Y
M6/V1/July 04/19
Prof. V.Rajaraman
c.
d.
A2
X
X
–
X
C1
N
–
Y
N
Y
C2
–
Y
Y
–
N
C3
N
N
–
Y
–
A1
–
–
–
X
X
A2
X
X
X
–
X
C1
Y
N
N
Y
C2
–
–
–
N
C3
–
N
Y
–
A1
–
–
X
X
A2
X
X
–
X
6.51 The following decision table may be replaced by its best equivalent shown
below:
a.
C1
N
C2
N
N
Y
Y
Y
Y
N
N
C3
Y
N
N
Y
Y
N
N
Y
A1
X
–
–
X
–
–
X
X
A2
–
X
X
–
X
X
X
X
C1
N
N
Y
Y
C2
–
–
Y
N
C3
Y
N
–
–
A1
X
–
–
X
A2
–
X
X
X
N
N
N
Y
Y
Y
Y
M6/V1/July 04/20
Prof. V.Rajaraman
b.
c.
d.
6.52
C1
–
Y
N
Y
C2
–
–
–
N
C3
N
–
Y
–
A1
–
–
X
X
A2
X
X
–
X
C1
N
–
Y
N
Y
C2
–
Y
Y
–
N
C3
N
N
–
Y
–
A1
–
–
–
X
X
A2
X
X
X
–
X
C1
Y
N
N
Y
C2
–
–
–
N
C3
–
N
Y
–
A1
–
–
X
X
A2
X
X
–
C1
N
N
C2
N
N
Y
Y
Y
Y
N
N
C3
Y
N
N
Y
Y
N
N
Y
A1
X
–
–
X
–
–
X
X
N
N
X
Y
Y
Y
Y
M6/V1/July 04/21
Prof. V.Rajaraman
a.
b.
c.
d.
A2
–
X
X
–
C1
N
N
Y
Y
C2
–
–
Y
N
C3
Y
N
–
–
A1
X
–
–
X
A2
–
X
X
X
C1
–
Y
N
Y
C2
–
–
–
N
C3
N
–
Y
–
A1
–
–
X
X
A2
X
X
–
X
C1
N
–
Y
N
Y
C2
–
Y
Y
–
N
C3
N
N
–
Y
–
A1
–
–
–
X
X
A2
X
X
X
–
X
C1
Y
N
N
Y
C2
–
–
–
N
C3
–
N
Y
–
X
X
X
X
M6/V1/July 04/22
Prof. V.Rajaraman
A1
6.53
–
–
X
X
A2
X
X
–
Given the
R1
X
decision table “test 3”answer the following questions:
R2
R3
R4
R5
R6
R7
x>=20
Y
Y
Y
Y
N
N
N
N
x<=30
Y
Y
N
N
Y
Y
N
N
y>=x
Y
N
Y
N
Y
N
Y
N
A1
X
X
X
X
–
–
–
–
A2
–
–
–
–
X
X
–
–
A3
–
–
–
–
–
–
X
X
R8
a. Rules R7, R8 are logically impossible
b. Rules R5, R6 are logically impossible
c. Rules R3, R4 are logically impossible
d. Rules R1, R2 are logically impossible
6.54 Pick the correct equivalent of “test 3”
a. C1 Y N
b.
A1
X
–
A2
–
X
Y
N
N
C2
–
Y
N
A1
X
–
–
A2
–
X
–
A3
–
–
X
C1
Y
N
N
C2
–
Y
N
c. C1
Y
Y
N
N
C3
N
Y
N
Y
C2
–
–
–
–
A1
X
X
–
–
A1
X
–
–
A2
–
–
X
X
A2
–
X
–
d.
C1
M6/V1/July 04/23
Prof. V.Rajaraman
A3
–
–
X
6.55 The decision table “test 3“ is
a. Incomplete
b. Ambiguous
c. Incorrect
d. .has redundancies
6.56
The decision table equivalent of the following Boolean expression is
A1= C3.C1.C2 + C2.C3.C1
A2= C1.C3 + C3.C2.C1+ C1.C2.C3
a. C1
Y
Y
Y
N
N
C2
Y
N
–
N
N
C3
N
Y
Y
Y
N
A1
X
X
–
–
–
A2
–
–
X
X
X
b. C1
Y
Y
Y
N
N
C2
Y
N
N
N
N
C3
Y
Y
–
Y
N
A1
X
X
–
–
–
A2
–
–
X
X
X
M6/V1/July 04/24
Prof. V.Rajaraman
c. C2
Y
Y
Y
N
N
C1
Y
N
–
N
N
C3
N
Y
Y
Y
N
A1
X
X
–
–
–
A2
–
–
X
X
X
d. C1
Y
Y
Y
N
N
C2
Y
N
–
N
N
C3
N
Y
Y
Y
N
A1
X
X
–
–
–
A2
X
X
X
X
X
6.57
A decision table “test 4” is given below
C1
Y
Y
N
–
–
N
Y
N
C2
Y
–
N
Y
–
N
N
–
C3
Y
Y
Y
–
Y
N
N
N
C4
–
Y
–
Y
N
–
–
N
A1
X
X
X
–
–
–
–
–
A2
–
–
–
X
X
–
–
–
A3
–
–
–
–
–
X
X
–
?
–
–
–
–
–
–
–
I
where I indicates impossible rule
The contradictory rules are
a. YYYY, NYYY, NNYY
M6/V1/July 04/25
Prof. V.Rajaraman
b. YYYN, NYYN, NNYN
c. YYYY, YYYN, NNYN
d. There are no contradictory rules
6.58
a.
In “test 4” the contradictory actions are:
A1, A3
b. A1, A2
c. A2, A3
d. A2, I
6.59
In “test 4” missing rule is:
e. NYNN
f.
NYYN
g. YYNN
h.
YNYN
6.60
If in “test 4” the rules where the contradictory actions or
unspecified actions are present, the action is replaced by A2 only, the
reduced decision table using impossible rules also for reduction is:
a.
b.
C1
–
–
–
–
–
N
C2
N
–
Y
Y
–
N
C3
Y
Y
–
Y
N
N
C4
Y
N
Y
–
N
–
A1
X
–
–
–
–
–
A2
–
X
X
X
–
–
A3
–
–
–
–
X
X
C1
N
Y
–
–
–
N
N
M6/V1/July 04/26
Prof. V.Rajaraman
c.
d .
C2
N
N
Y
Y
–
–
N
C3
Y
Y
N
Y
Y
N
N
C4
Y
Y
Y
–
N
N
–
A1
X
X
–
–
–
–
–
A2
–
–
X
X
X
–
–
A3
–
–
–
–
–
X
X
C1
–
–
–
–
N
C2
N
–
Y
–
N
C3
Y
Y
–
N
N
C4
Y
N
Y
N
–
A1
X
–
–
–
–
A2
–
X
X
–
–
A3
–
–
–
X
X
C2
N
Y
–
N
C3
Y
–
Y
N
C4
Y
–
N
–
A1
X
–
–
–
A2
–
X
X
–
A3
–
–
–
X
6.61 Decision Trees are preferred when
a. Too many conditions need to be tested
b. Sequencing of testing conditions is important
c.
When there are many loops to be performed
d.
When too many actions are to be taken
M6/V1/July 04/27
Prof. V.Rajaraman
6.62
Decision Tables are preferred when
a. Too many conditions need to be tested
c. When there are many loops to be performed
d. When too many actions are to be taken
6.63 Structured English is preferred when
a. any conditions need to be tested
c. When there are many loops to be performed
d. When too many actions are to be taken
6.64
The objective of using decision trees is to
a. Expand a DFD so that a user can understand it
b. To specify sequence of conditions to be tested and actions to be taken
c.
Describe a computational procedure that can be easily understood by a
person
d.
6.65
Use it as a tool in decision support system
Decision trees are superior to decision tables when
a. The number of conditions to be tested is very large
b.
When sequence of testing conditions is not particularly important
c. When sequence of testing conditions is not particularly important
d.
6.66
When a large number of actions are to be specified
Logical correctness of a specifications can be systematically checked by
a. Using decision trees
b.
Using structured English
c. Using DFD’s
d.
6.67
Using decision tables
The decision tree equivalent of the following structured English is
if C2 then
if C1
then A3
M6/V1/July 04/28
Prof. V.Rajaraman
else A2
endif
else A1,A3
endif
A3
Y
C2
Y
a.
N
A2
C1
N
A1, A3
Y
b.
A3
C1
Y
A2
N
C2
A1
Y
N
C1
A3
N
Y
Y
c.
C1
A3
N
A2
C2
N
A1, A3
M6/V1/July 04/29
Prof. V.Rajaraman
A2
C1
d.
A3
C2
A1A3
6.68 Decision tables are better then Decision trees when
a. Conditions are to be isolated from actions in a word statement
b.
Condition sequences are to be found from a word statement
c. Logical correctness of a word statement is to be established
d.
Large number of actions is to be performed
6.69 The decision table equivalent of the Decision tree of choice (a) of 6.5.7 is
a.
C2
C1
Y
N
N
Y
N
N
Y
Y
A1
A2
A3
X
X
X
-
X
X
-
X
b.
C1
C2
Y
Y
Y
N
N
-
A1
A2
A3
X
X
-
X
X
c.
C1
C2
Y
Y
Y
N
A1
A2
A3
X
X
-
N
Y
X
X
M6/V1/July 04/30
Prof. V.Rajaraman
d.
C1
C2
Y
Y
Y
N
A1
A2
A3
X
X
-
N
Y
X
X
Error
M6/V1/July 04/31
Prof. V.Rajaraman
Key to Objective Questions
6.1
b
6.2
c
6.7
b
6.8
d
6.9
b
6.10
6.13
a
6.14
c
6.15
b
6.16
b
6.17
a
6.18
a
6.20
6.21
c
6.22
d
6.23
a
6.24
6.19
6.3
b
a
6.4
d
6.5
d
c
6.11
6.6
a
a
6.12
6.25
a
6.26
c
6.27
c
6.28
d
6.29
b
6.30
6.31
c
6.32
d
6.33
b
6.34
a
6.35 d
6.36
6.37
b
6.38
a
6.39
c
6.40
d
6.41
c
6.43
6.49
b
b
c
d
b
a
d
6.42
a
6.44
c
6.45
c
6.46
a
6.47
d
6.48
b
6.50
c
6.51
a
6.52
b
6.53
a
6.54
a
a
6.57
c
6.58
b
6.59
6.55
d
6.56
6.61
b
6.62
a
6.63
c
6.67
c
6.68
c
6.69
b
6.64
b
6.65
c
c
6.60
6.66
d
d
M6/V1/July 04/32
Prof. V.Rajaraman
System Analysis and Design / Structured Systems Analysis and Design
Question Bank
QUESTION BANK – MODULE 6
6.1
A bank has the following policy on deposits: On deposits of Rs.5000 and above
and for three years or above the interest is 12%. On the same deposit for a
period less than 3 years it is 10%. On deposits below Rs.5000 the interest is 8%
regardless of the period of deposit. Write the above process using
i.
Structured English
ii.
A decision table
6.2
An organization maintains an employee file in which each record has the
following data:
(Employee No., employee name, employee gross pay).
It has been decided to increase the pay as per the following formula:
For pay of Rs.1000 or less increase 15%
For pay of more than Rs.1000 but up to Rs.2500 increase 10%.
For pay over Rs.2500 increase 5%.
i.
Write a structured English processing rule corresponding to the above
policies
ii.
Express the policies as a decision table.
6.3
An offshore gas company bills its customer according to the following rate
schedule:
First 500 litres Rs. 10 (flat)
Next 300 litres Rs.1.25 per 100 litres
Next 30,000 litres Rs.1.20 per 100 litres
Next 100,000 litres Rs.1.10 per 100 litres
Above this Rs.1.00 per 100 litres.
The input record has customer identification, name and address, meter reading,
past and present. Write a structured English procedure to obtain a bill for the
customer.
6.4
A narrative of a user’s requirements in an organization is given below:
"Our company receives a number of items from many vendors and they are
received at the receiving office. As we receive over 1000 items a day it is now
virtually impossible for the receiving office to check whether the vendor has
supplied items against an order, or sent a wrong item and inform the purchase
office. We are also not able to find out if there are excesses or deficiencies in
delivery and whether the vendor adhered to the delivery schedule as per the
order. The items received at the receiving office are sent for physical inspection.
The physical inspection consists of checking whether the quantities stated in the
delivery note agree with the physical count, whether the item is the correct one
ordered, and a check on the quality of item. We would like to keep a record of
rejections due to bad quality, incorrect items, excess/deficient supply etc.,
determined during inspection. This will enable us to assess vendors' reliability to
guide us in placing orders in the future, besides keeping track of supplies. Items
cleared by the inspection office are taken into the inventory by the stores office
which keeps a ledger of items stocked and quantity available of each item.
Customers send requisitions to the stores. The stores fulfill the requests based
on availability and update the ledger. Currently we are not able to meet some of
our customers' requests. We would like to incorporate automatic reordering by
our purchase office if the inventory level of an item is low. We would also like
to keep track of unfulfilled requests and meet them when items reach the store.
Currently we are not able to pay our vendors promptly due to delays in payment
M6/V1/July 04/1
Prof. V.Rajaraman
6.5
6.6
6.7
6.8
6.9
Question Bank
order reaching our accounts office. We would like to rectify this. We would
also like to bill our customers promptly and keep track of customers' payments"
Develop the processing rules in structured English for the office receiving the
goods specified in the user’s requirements.
Develop the processing rules in Structured English for the inspection process of
the user’s requirements stated in Exercise 6.4
Develop the processing rules in Structured English for the purchase process of
the user’s requirements stated in Exercise 6.4.
Develop the processing rules in Structured English for the accounting process
stated in Exercise 6.4
Develop the processing rules in Structured English for the stores process stated
in Exercise 6.4
The policy followed by a company to process customer orders is given by the
following rules:
(i)
If the customer order ≤ that in stock and his credit is OK, supply his
requirement.
(ii)
If the customer credit is not OK do not supply. Send him an intimation.
(iii) If the customer credit is OK but items in stock are less than his order,
supply what is in stock. Enter the balance to be sent in a back-order file.
Obtain a decision table for the above policy.
M6/V1/July 04/2
Prof. V.Rajaraman
Question Bank
6.10 Obtain a decision table to decide whether on a given date an employee in an
organization has completed one year's service or not.
6.11 Obtain a decision table for an automatic stamps vending machine with the
following specifications:
(i)
To dispense 20, 15, 10, 5 paise stamps
(ii)
To accept 50, 25, 10, 5 paise coins
(iii) Do not return change if it is necessary to return more than two coins of the
same denomination. In such a case return the customer's coin and turn on
"no change" light.
The machine should dispense a stamp, the right amount of change, no stamp
available, no change available signals etc.
6.12 Obtain a decision table to be used by a person to enter the office of a manager.
After obtaining the decision table, ensure that it has no logical errors and that it is
in minimal form.
6.13 A University has the following rules for a student to qualify for a degree with
Physics as the main subject and Mathematics as the subsidiary subject:
(i)
he should get 50% or more marks in Physics and 40% or more marks in
Mathematics.
(ii)
If he gets < 50% marks in Physics, he should get 50% or more marks in
Mathematics. He should, however, get at least 40% marks in Physics.
(iii) If he gets < 40% marks in Mathematics and 60% or more marks in Physics,
he is allowed to reappear in Mathematics examination only so that he can
qualify.
(a) obtain an EEDT for the rules
(b) obtain an LEDT for the rules
check the logical correctness of the decision table
6.14 In instalment buying where payments are make on a weekly basis the action taken
on "an account goes into arrears" is a crucial aspect of the operaiton. Table P6.14
illustrates a simplified arrears procedure. Answer the following questions:
(i)
Are all elementary rules logically possible?
(ii)
Is the table complete?
(iii) Has the table any ambiguities?
(iv)
Are there logical errors in the table? If yes, point them out.
(v)
Use reasonable assumptions and correct the table.
(vi)
Remove any redundancies in the corrected table (Table 6.)
6.15 Obtain a decision tree for Exercise 6.9.
6.16 Obtain a decision tree for exercise 6.13. Is it possible to find out missing rules if
any in a decision tree representation.
6.17 Obtain a decision tree for Exercise 6.12.
6.18 Explain in what types of problems you will use a decision tree approach rather
than a decision table approach.
6.19 You want to go to Delhi from Bangalore. There are three flights per day; early
M6/V1/July 04/3
Prof. V.Rajaraman
Question Bank
morning, late morning and evening. You would like to go on 21.4.04 by early
morning flight. If it is not available you will take the late morning flight. If neither
is available you are willing to take any flight on 22.4.04 but prefer early and late
morning flights., Obtain a decision tree for this word statement. Is decisiont able
suitable for this problem? If not why?
6.20 Explain in what types of problemsyou will prefer Structured English process
specification rather than decision tree.
Table P.6.14 A simplified Arrears Procedure
C1: This week's cash > weekly Y
Y
N
N
−
−
−
−
−
rate
C2: This week's cash > 0
Y
Y
N
N
N
−
−
−
−
C3: Any cash during last month −
N
N
Y
Y
Y
−
−
−
Y
N
N
Y
−
−
−
−
−
N
Y
N
N
Y
N
Y
−
−
Notify accounts
Take special action
−
−
−
−
X
−
A1
X
−
−
−
−
−
A2
−
X
−
−
−
−
A3
−
−
−
−
X
−
A1
−
−
X
−
−
−
A4
−
−
−
−
−
X
A5
−
−
−
−
X
−
A1
−
−
−
X
−
−
A6
−
−
−
−
−
X
A5
M6/V1/July 04/4
Prof. V.Rajaraman
Pointers
References
1. V.Rajaraman, “Analysis and Design of Information Systems”, 2nd Edition, Prentice
Hall of India, New Delhi, 2002. Most of the material in this module is based on
Chapter 8 and 9 of the above book. The book is perhaps the only one which has
extensive discussion on error detection in Decision Tables.
2. K.E. Kendall and J.E.Kendall, “Systems Analysis and Design”, 5th Edition, Pearson
Education Asia, Delhi, 2003. Has a brief discussion of structured English, Decision
Tables and Decision Trees (pages 353 to 369). Website www.prenhall.com/kendall
has a lot of support material and case study for students.
3. J.A.Hoffer, J.F.George, J.S.Velacich, “Modern Systems Analysis and Design”, Third
Edition, Pearson Education Asia, 2002. Chapter 7 (pages 282 to 303) cover the
topics in this module. The book has a number of interesting case studies and a good
problem set. The web site http://prenhall.com/hoffer has material to assist students
who use this text book.
4. E.Yourdon “Modern Structured Analysis”, Prentice Hall of India, 1996. Chapter 11
(pages 203 to 232) describes structured English and Decision Tables. There is a
larger set of exercises at the end of the chapter.
M6/V1/July 04/1