dfd components

8/8/2019 Dfd Components

1/9

Assignment : DFD COMPONENTS

1. Input : Number of New Components bought (number)

Season for sales taken into consideration (season)

Sales Condition (sales)

Output : Wastage of Components (wastage)

IF season == Poor Summers AND sales == Low Sales

IF number == 0 THEN wastage = 0; END-IF




ELSE IF season == Fair Summers AND sales == Reasonable Sales



IF number == 1000 THEN wastage =15; END-IF


ELSE IF season == Good Summers AND sales == Good Sales





ELSE IF season == Very Good Summers AND sales == Very High Sales





END-IF


2/9

2. Decision Table

Action / Condition Retail Customer Wholesale Customer

Insufficient

Inventory

Sufficient

Inventory

Insufficient

Inventory

Sufficient

Inventory

Back Order Required Y N Y N

Ordered

Specified

Quantity

Ordered

Below

Specified

Quantity

Discount Allowed N Y N

Have Sales Tax

Exception

Form

Have No Sales

Tax Exception

Form

Sales Tax Levied Y Y N

Payment

Received

Payment On

Delivery

Payment

Received

Payment On

Delivery

Bill Shipped Y N Y N

3. Decision Trees

A decision tree is a decision support tool that uses a tree-like graph or model of decisions and their

possible consequences, including chance event outcomes, resource costs, and utility.

Decision Trees are an alternative to Decision Tables.It employs a tree structure that show conditions

and actions within a problem.It is easier to understand and there is no need for special training.

Decision Tree Structure incorporates,

Root of tree -> name of process

Nodes -> conditions

Leaves -> actions to be performed

A decision tree is a graphic tool that represents conditions and their resulting actions. It consists of a

directed acyclic graph (rooted tree) in which the non-terminal edges represent a set of conditions

evaluated sequentially from the root. A node is a decision point where a condition is evaluated. The

terminal edges (leaves) represent actions.

Decision trees are a useful tool for expressing complex decision variables in a format conducive to

human visualization.

In order to Design a Decision Tree, the analyst needs to identify the,

a. Decisions in consideration

b. Uncertain Events


3/9

c. Chances of outcomes based on Decision Taken and Events occurred

d. Outcomes finally achieved

5. Well Digging

70% Successful

20% Successful

Drill Further

Drill Well To 25 mtr 80%

20 mtr Not Successful

30% Not Successful

Do NotDrill Further

Do Not Drill Well

A Drill Well or Not To Drill Well

1 Chances are that some might drill further to 25 mtr and some might not

2 Chances are that drilling further to 25 mtr, 20% it would be successful

It would be appropriate for the Analyst to either drill the well up till 20 feet, since it has 70%

chances of success.

But then again, in case of negative results, need not drill further, since there are more chances

of failure than success, and simply buy water for Rs 15000.

And incase the analyst advises not to take any chances, it would be better to buy water than

spending Rs 10000 and not succeeding, hence spending Rs 15000 further to buy water.

A 1

Cost = Rs 10000

Investment

2

Cost = Rs 12500

Investment

Cost = Rs 12500

+ Rs 15000

To Buy Water

Cost = Rs 15000

To Buy Water

Cost = Rs 10000

+ Rs 15000

To Buy Water


4/9

6. Decision Table for Upgrading or Shutting Down the Business Unit.

Shutdown

and Sell the

Site

Continue as Before Up gradation OF Business

Deluxe Type Standard Type

Good

Results

Poor

Results

Good

Results

Poor

ResultsReturns Over the

Period of Ten Years

Sold For Rs

15 Million

Rs 2 Million in the next

year and reducing by

10% every consecutive

year

Rs 40

Million

Rs 20

Million

Rs 25

Million

Rs 10

Million

Positive Test Result Negative Test Result

Chances of Good Response 85% 10%

Chances of Poor Response 15% 90%

Up gradation Suggested Deluxe Standard

7. Decision Tree Organization

A decision making tree is essentially a diagram that represents, in a specially organized way, the

decisions, the main external or other events that introduce uncertainty, as well as possible

outcomes of all those decisions and events.

Here is a schematic example that illustrates the basic elements of decision trees.


5/9

Squares represent decisions you can make. The lines that come out of each square on its right show

all the available distinct options that can be selected at that decision analysis point.

Circles show various circumstances that have uncertain outcomes (For example, some types of

events that may affect you on a given path). The lines that come out of each circle denote possible

outcomes of that uncontrollable circumstance. Write down above each such line in the decision tree

your best guesses for probabilities (for example, 80% or 0.8) of those different outcomes.

Each path that can be followed along the decision tree, from left to right, leads to some specific

outcome. You need to describe those end results in terms of your main criteria for judging the

results of your decisions. Ideally, you will assign each end outcome a quantitative measure of the

overall total benefit you will receive from that outcome (you can express it as a perceived monetary

value).

Now you have a complete decision making tree with specific numbers for both the probabilities of

the uncertain events and the benefit measures (desirability) of each end result. At this stage the treecan give you more specific recommendation on what would be your best choices.

In particular, for each choice that you control (at the decision points shown by squares), you can

calculate the overall desirability of that choice. Just sum the benefit measures of all the end

outcomes that can be traced back to that choice (via one path or another), weighted by the

probabilities of the corresponding paths. This will show you the preferred choice (the one with the

highest overall desirability).

If you have more than one decision point, you need to do that calculation for the decisions that are

at the latest stages first. Identify the choice that gives the highest overall desirability and leave onlythat branch (removing the decision point). Do the same with the remaining squares, working your

way to the left (to the first decision point in the sequence).


6/9

8. Decision Tree depicting the cost of Accepting or Rejecting a lot of Production

60%

Chance 10% Defective

Defective Lot

Defect 40%

Detected Non Defective Chance 4% Defective

Lot

Reject a Proper

Set OF Lot

Defect Not

Detected Accept a Lot

With Defective Lot

Accept a Proper

Set of Lot

A Testing of2 sample pieces of the Entire Lot

1 Accepting The Entire Lot

2 Rejecting The Entire Lot

As portrayed in the figure, the cost of testing is based on,

a. Whether the sample tested has turned out to be defective or not

b. Accordingly if it is accepted as a whole lot or not.

For instance, the cost varies with large margin incase of,

a. A defective lot being accepted based on Positive result of the sample Test

b. A Good lot being rejected based on Negative result of the Sample Testing

A

1

2

Cost = Rs 2000

Cost = Rs 2000

Cost = Rs 4000

Cost = Rs 22000

Cost = Rs 2000


7/9

9. To book rooms for lectures in FLORA School

INPUT : Course Details

Time Slot

Student Strength

Facilities Required

OUPUT : Valid / Invalid Input

Classroom Booked / Details

a. Accept User Input Details

b. Validate Input

y IF Input Details Incomplete

THEN Throw Alert INVALID INPUT

GO TO a

END-IF

c. Initialize

y AvailableRoom.No = NULL ;

y AvailableRoom.Strength = 99;

y Count = 0;

d. LOOP

y IF (input.Time Slot == Room[count].TimeSlot) AND

(input.Student Strength == Room[count].Strength) AND

(input.Facilities == Room[count].Facilities) AND

Room[count].Status == Available

THENIF AvailableRoom.Strength > Room[count].Strength

THEN AvailableRoom.No = count;

END-IF

END-IF

y count = count + 1

e. IF AvailableRoom.No == NULL

THEN Alert No Room Available

ELSE Alert Room Number Available is : + AvailableRoom.No

Room.Status = Booked

END-IF


8/9

10. Multiple Decision Tables

Conditions 1 2 3 4 5 6

Reservation

Done

X X X X

ReservationGuaranteed X X

Rooms

Available

X X X

Actions

Allot Room

in Hotel

N Y N N Y Y

Allot Room

in INN on

Hotel

Expenses

N N N Y N N

Condition 1 2 3 4

Initial Deposit

With Credit Card

X X

Initial Deposit

With Cash

X X

Final Payment

With Credit Card

X X

Final Payment

With Cash

X X

Actions

Make Registration

Card During

Check-in

Y Y Y Y

Settle Whole

Amount During

Check-out

Y Y N N

Settle Remaining

Amount During

Check-out

N N Y Y


9/9

11. Penalty Determining Process For Grapes Contract

Condition 1 2 3 4 5 6 7 8

Grapes do not exceed

minimum required

ripeness level

X X X X

Grapes are not

disease or damage

free

X X X X

Lot contains Material

other than grapes

X X X X

Contract up for

Renewal

X X X

Actions

Terminate Contract N N N Y N Y N Y N Y N

Consider for possible

rejection

N N N Y Y Y Y N

Levy 20% Penalty Y Y Y N N N N N

Accept Lot Y Y Y Y Y Y N Y

dfd components

Documents