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PMS System
FP Analysis
Step-1: Type of FP Count
Development project FP count
Step-2: Identification of Application Boundary
Party System PMS NAB
Parliament Members
Father
Spouse
property
Party System
NAB System
PMS System
PMS System– NIC– Member name– Date of birth– Qualification– Experience– No. of times in Parliament
Spouse– Spouse name
– Spouse property
– Spouse income Father
– Father’s name
– Father’s property
– Father’s income
Party System– ID– NIC– Political Party– Date Joined Party– Membership Info– Status
NAB System NAB Case
– ID– NIC– Case ID– Case Description– Start Date– Closing Date– Charges
Property Financial information
– Year– Income– Tax/year– Campaign Expense
Step-3: Identification of ILF’s
ILF RET DET Functional Complexity
Parliament Members
3 15 Low
EIF RET DET Functional Complexity
Party System 1 6 Low
NAB System 3 16 Low
Step-4: Identification of Transaction functions and their complexity
EI FTR DET Functional Complexity
Add Data 1 15 Low
Update Data 1 15 Low
Delete Data 1 15 Low
EO FTR DET Functional Complexity
Property Info 1 4 Low
Member Assessment
2 2 Low
EQ FTR DET Functional Complexity
Member w.r.t. Political Party
2 18 Average
Member Party Info
1 3 Low
List of Charges 1 3 Low
Election Expenses
1 2 Low
Tax Details 1 4 Low
Step-5: Calculate Unadjusted FPFunction
TypeFunctional Complexity
Complexity Total
Function Types
ILF 1 Low X 7 7
0 Average X 10 0
0 High X 15 0 7
EIF 2 Low X 5 10
0 Average X 7 0
0 High X 10 0 10
EI 3 Low X 3 9
0 Average X 4 0
0 High X 6 0 9
EO 2 Low X 4 8
0 Average X 5 0
0 High X 7 0 8
EQ 4 Low X 3 12
1 Average X 4 4
0 High X 6 0 16
UFP 50
Step-6: Calculate Value Adjustment Factor
General System Characteristics Value
Data Communication 1
Distributed Data Processing 0
Performance
5
Heavily used configuration
0
Transaction Rate
4
On-line data entry
2
End-user efficiency
5
On-line update 3
Complex Processing 0
Reusability
0
Installation Ease 2
Operational Ease 5
Multiple sites
5
Facilitate change
2
Total Degree of Influence (TDI) 35
Step-7: Calculate adjusted FP
VAF = (TDI x 0.01) + 0.65 VAF = (35 x 0.01) + 0.65 VAF = 1
Adjusted FP = UFP x VAF
50 x 1 = 50
Automated Courier System
FP Analysis
Type of FP Count
Development FP count
Bank
Courier service system
m
Customer
Location
Area
City
Office
1
m
1
Office Personnel
Agent
Admin
Employee
m
11
Order
1
1
Shipment
System Boundary
Customer– C_id,name,SSN,address,email,phone
ORDER– C_id, order_id,payment mode,destination address, expected delivery date
OFFICE PERONNEL– ID, name, SSN, address, office id, email, phone
EMPLOYEE– Hiredate, login, pwd
ADMIN– Authorization level, login, pwd
AGENT– Location
OFFICE– Id, location,type(head/local)
SHIPMENT– Order_id,agent_id,shipment_status
LOCATION– City code, city name
– Area code,area name
Calculation of ILFs and EIFs
ILFs– Customer
• No subgroup– Number of RETs = 1– Number of DETs <20
• 1 RETs, <20 DETs Complexity = Low
– Order• No subgroup
– Number of RETs = 1– Number of DETs <20
• 1 RETs, <20 DETs Complexity = Low
Calculation of ILFs and EIFs….
– Shipment• No subgroup
– Number of RETs = 1– Number of DETs <20
• 1 RETs, <20 DETs Complexity = Low
– Office Personnel• Three subgroups (personnel + agent),
(personnel+admin),(personnel+employee)– Number of RETs = 3– Number of DETs <20
• 3 RETs, <20 DETs Complexity = Low
Calculation of ILFs and EIFs…
– Location• Two sub groups
– Number of RETs = 2– Number of DETs <20
• 2 RETs, <20 DETs Complexity = Low
EIFs– Bank
• Complexity: low
Contribution of ILFs and EIFs
Contribution of ILFs and EIFs ILF
–Low 8 x 7 = 56
–Avg 0 x 10 = 0
–High 0 x 15 = 0
EIF–Low 1 x 5 = 5
–Avg 0 x 7 = 0
–High 0 x 10 = 0
Total = 61
Identification of EI’s, EO’s, EQ’sUse Case Transactio
n TypeFTRs DET
sComplexit
y
Add Customer info EI Customer > 5 Low
Delete Customer info EI Customer > 5 Low
View Customer info EQ Customer <19 Average
Create order EI Customer, order >16 High
Add order EI Customer, order >16 High
View order EO Order <20 Low
Inquire order EQ Order <20 Low
Add employee info EI Personnel <16 Low
Update employee info EI Personnel <16 Low
Delete employee info EI Personnel <16 Low
View employee info EO Personnel <20 Low
Inquire employee info EQ Personnel <20 Low
Identification of EI’s, EO’s, EQ’s…
Add city,are EI Location, Office <16 Low
Delete EI Location, Office <16 Low
Update EI Location, Office <16 Low
View EO Location, Office <20 Low
Inquire EQ Location, Office <20 Low
View main page EO Customer <16 Low
Place order EI Customer, order, shipment
> 5 High
Payment EI Customer, order, shipment
> 5 High
View payment EO Bank, order <19 Low
View location EO Location <19 Low
View shipment EO Shipment, order >6 Average
Inquire city etc EQ Location, office >6 Average
FTR’s Trans Type complexityDET’sUse case
Contribution of transaction functions EI
Low 8 x 3 = 24Avg 0 x 4 = 0High 4 x 6 = 24
EQLow 6 x 3 = 18Avg 1 x 4 = 4High 0 x 6 = 0
EOLow 3 x 4 = 12Avg 2 x 5 = 10High 0 x 7 = 0
Total = 88
Unadjusted function point count
Total count = 88 + 61 = 149
General System Characteristics
1. Data Communication
2. Distributed Data Processing
3. Performance
4. Heavily used configuration
5. Transaction Rate
6. On-line data entry
7. End-user efficiency
8. On-line update
9. Complex Processing
10. Reusability
11. Installation Ease
12. Operational Ease
13. Multiple sites
14. Facilitate change
•Value Adjustment FactorGeneral System Characteristics•Data CommunicationScore = 1•Distributed Data ProcessingScore = 4, Distributed processing and data transfer are online and in both directions•PerformanceScore = 3, Response time of the system is critical during all business hours•Heavily Used ConfigurationScore = 5, There are special constraints on the application in the distributed components of the system.•Transaction RateScore = 0, there is no peak transaction period. •Online Data EntryScore = 4, as more than 20 percent of transactions are interactive data entry.•End User EfficiencyScore = 2, four of the defined factors are a part of the design, which includes pre-assigned functions keys, Mouse interfaces•Online UpdateScore = 3, nearly all the internal logic files are updated regularly over the Internet and the Intranet.•Complex ProcessingScore = 2, at some points in application logical processing is extensive.•ReusabilityScore = 1, reusable code is used with in the application•Installation EaseScore = 1, there are no special considerations, but a setup will be required for installation.•Operational EaseScore = 2, The application will minimize the use of tape mounts and paper handling.•Multiple SitesScore = 1, User requirements require the consideration of needs of more than one installation site.•Facilitate ChangeScore = 3, flexible query and report facility is provided that can handle complex requests.
Total Degree of Influence – TDICan influence the FP count by ± 35%
Value Adjustment Factor – VAF
VAF = (TDI * 0.01) + 0.65
Adjusted FP Count – AFP
AFP = UFP * VAF