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PMS System FP Analysis. Step-1: Type of FP Count Development project FP count.

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Presentation on theme: "PMS System FP Analysis. Step-1: Type of FP Count Development project FP count."— Presentation transcript:

1 PMS System FP Analysis

2 Step-1: Type of FP Count Development project FP count

3 Step-2: Identification of Application Boundary Party System PMS NAB

4 Parliament Members Father Spouse property Party System NAB System PMS System

5 –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

6 Step-3: Identification of ILF’s ILFRETDETFunctional Complexity Parliament Members 315Low EIFRETDETFunctional Complexity Party System16Low NAB System316Low

7 Step-4: Identification of Transaction functions and their complexity EIFTRDETFunctional Complexity Add Data115Low Update Data115Low Delete Data115Low EOFTRDETFunctional Complexity Property Info14Low Member Assessment 22Low EQFTRDETFunctional Complexity Member w.r.t. Political Party 218Average Member Party Info 13Low List of Charges13Low Election Expenses 12Low Tax Details14Low

8 Step-5: Calculate Unadjusted FP Function Type Functional Complexity Complexity Total Function Types ILF1LowX 77 0AverageX 100 0HighX 1507 EIF2LowX 510 0AverageX 70 0HighX 10010 EI3LowX 39 0AverageX 40 0HighX 609 EO2LowX 48 0AverageX 50 0HighX 708 EQ4LowX 312 1AverageX 44 0HighX 6016 UFP 50

9 Step-6: Calculate Value Adjustment Factor General System CharacteristicsValue Data Communication1 Distributed Data Processing0 Performance 5 Heavily used configuration 0 Transaction Rate 4 On-line data entry 2 End-user efficiency 5 On-line update3 Complex Processing0 Reusability 0 Installation Ease2 Operational Ease5 Multiple sites 5 Facilitate change 2 Total Degree of Influence (TDI)35

10 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

11 Automated Courier System FP Analysis

12 Type of FP Count Development FP count

13 Bank Courier service system m Customer Location Area City Office 1 m 1 Office Personnel Agent Admin Employee m 1 Order 1 1 Shipment System Boundary

14 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

15 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

16 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

17 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

18 Contribution of ILFs and EIFs ILF –Low8x 7 =56 –Avg0x10= 0 –High0x15= 0 EIF –Low1x 5 =5 –Avg0x7= 0 –High0x10= 0 Total = 61

19 Identification of EI’s, EO’s, EQ’s Use CaseTransaction Type FTRsDETsComplexity Add Customer infoEICustomer> 5Low Delete Customer infoEICustomer> 5Low View Customer infoEQCustomer<19Average Create orderEICustomer, order>16High Add orderEICustomer, order>16High View orderEOOrder<20Low Inquire orderEQOrder<20Low Add employee infoEIPersonnel<16Low Update employee infoEIPersonnel<16Low Delete employee infoEIPersonnel<16Low View employee infoEOPersonnel<20Low Inquire employee infoEQPersonnel<20Low

20 Identification of EI’s, EO’s, EQ’s… Add city,areEILocation, Office<16Low DeleteEILocation, Office<16Low UpdateEILocation, Office<16Low ViewEOLocation, Office<20Low InquireEQLocation, Office<20Low View main pageEOCustomer<16Low Place orderEICustomer, order, shipment > 5High PaymentEICustomer, order, shipment > 5High View paymentEOBank, order<19Low View locationEOLocation<19Low View shipmentEOShipment, order>6Average Inquire city etcEQLocation, office>6Average FTR’s Trans TypecomplexityDET’s Use case

21 Contribution of transaction functions EI Low8x 3 =24 Avg0x4= 0 High4x6=24 EQ Low6x 3 =18 Avg1x4= 4 High0x6= 0 EO Low3x 4 =12 Avg2x5= 10 High0x7= 0 Total = 88

22 Unadjusted function point count Total count = 88 + 61 = 149

23 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

24 Value Adjustment Factor General System Characteristics Data Communication Score = 1 Distributed Data Processing Score = 4, Distributed processing and data transfer are online and in both directions Performance Score = 3, Response time of the system is critical during all business hours Heavily Used Configuration Score = 5, There are special constraints on the application in the distributed components of the system. Transaction Rate Score = 0, there is no peak transaction period. Online Data Entry Score = 4, as more than 20 percent of transactions are interactive data entry. End User Efficiency Score = 2, four of the defined factors are a part of the design, which includes pre-assigned functions keys, Mouse interfaces Online Update Score = 3, nearly all the internal logic files are updated regularly over the Internet and the Intranet. Complex Processing Score = 2, at some points in application logical processing is extensive. Reusability Score = 1, reusable code is used with in the application Installation Ease Score = 1, there are no special considerations, but a setup will be required for installation. Operational Ease Score = 2, The application will minimize the use of tape mounts and paper handling. Multiple Sites Score = 1, User requirements require the consideration of needs of more than one installation site. Facilitate Change Score = 3, flexible query and report facility is provided that can handle complex requests.

25 Total Degree of Influence – TDI Can influence the FP count by ± 35% Value Adjustment Factor – VAF VAF = (TDI * 0.01) + 0.65 Adjusted FP Count – AFP AFP = UFP * VAF

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