Function Point Training

Transcription

1 Function Point Training Instructor: David Longstreet tel. or fax. 112 Two Day Schedule Day One - Function Points Concepts, Questions and Exercises Day Two - Exercises and Case Studies 113

2 Some of My Metrics Over 2 million frequent flyer miles. Consulted on every continent except Antarctica. Presented papers at conferences in USA, Europe, Middle East, Asia, and Australia. Written and published articles in American Programmer, Software Development Magazine and Journal of Information Systems Management. 114 Clients Clients include Banking & Finance, Aerospace, Retailers, Animal Food, Telephony, Consulting Companies, Medical Research, Defense Contractors, Automotive, Universities, Government Agencies and others Some clients: MasterCard, Saudi American Bank, Ralston Purina, Sprint, Lockheed, The GAP, Nissan, Biologic, and Andersen Consulting. 115

3 Worst Practices No historical data Failure to monitor and report status Creating analysis documentation after coding Excessive and irrational schedule pressures Failure to establish clear acceptance criteria Reduce testing time to make schedule 116 Software Past, Present, Future 117

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6 122 What is a Function Point? Function Points are a unit of measure Like a hour is to measuring time Or a inch is to measuring distance A unit is important to understanding and communicating such metrics as Average Cost. 123

7 Function Points Analysis Is a structured technique of classifying components of a system. Is a method to break systems into smaller components, so they can be better understood and analyzed. Measures software by quantifying its functionality provided to the user based primarily on the logical design. Logical functionality from a sophisticated user view rather than a physical view. A standard method for measuring software development from the customers point of view 124 Estimate the Surface Area of a A can of diet coke 125

8 Function Points? 126 Average Maximum Temperature Kansas City, MO Fahrenheit Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Celsius 127

9 Components of Function Point Analysis Transactional Function Types External Inputs (EI) External Outputs (EO) External Inquiries (EQ) Data Function Types Internal Logical Files (ILF) External Interface Files (EIF) 128 Size of Largest Projects Since ,000 Function Points 20,000 15,000 10,000 5, Years 129

10 Hours/FP Hours/FP Since 1970 (Unit Cost) Hours Per Function Point By Size Size v. Effort Hours Per FP ,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000 Size in Function Points 9,000 10,000 11,000 12,000 13,000 14,000 15,

11 Large Projects Increasing Marginal Cost As size increases unit cost rise. Any large engineering or construction project follows the same economic model. 132 Problems with LOC Metrics Higher level languages produce less LOC Better programmers produce less LOC Actual LOC are known too late to be used for estimating No consistent method to count LOC especially between languages 133

12 Benefits to Measurement Understand Costs Understand Schedule Understand Quality Levels Understand Productivity Levels Increased Control 134 Problems with Measurements Difficult to quantify anything disorganized Time consuming Benefits are not immediate Consistency 135

13 Motivation of Metrics 1. Stabilizing Processes 2. Data for Estimating 3. Improve Quality 4. Cost Reduction 5. Schedule Reduction 6. Compare Methods 7. Compare Organizations 8. Better Controls 136 Measurement/Goals Measurements need to support the goals of the organization Measurement should not drive goals Management should drive goals 137

14 Characteristics of Effective Measurement Programs Aligned with business objectives Integrated with continuous process Tied to decision making Balanced metrics Focused on measuring processes Viewed as mission critical 138 Productivity The output-input ratio within a time period with due consideration for quality. Productivity = outputs/inputs 139

15 Effectiveness v. Efficiency Effectiveness is the achievement of objectives Efficiency is the achievement of the ends with least amount of resources. 140 Understanding Potential Scope Creep A project will grow at 1 percent per month during the entire development schedule. FP Analysis allows the ability to compare project size at the end of requirements, analysis, design, and implementation. 141

16 Examples of Project Growth A project that is schedule for 12 months will grow over 12 percent. A project that is scheduled for 48 months will grow over 48 percent. 142 Calculating Function Points Three types of calculations Development Enhancement Application or Baseline 143

17 Benefits of Function Point Analysis can be used to size software applications accurately. can be counted by different people, at different times, to obtain the same measure within a reasonable margin of error. are easily understood by the non technical user. can be used to determine whether a tool, a language, an environment, is more productive when compared with others. 144 Objectives of Function Point Analysis Measures functionality that the user requests and receives. Measures software development and maintenance independently of technology used for implementation. Simple enough to minimize measurement costs A consistent measure 145

18 Function Points Analysis Is a structured technique of classifying components of a system. Is a method to break systems into smaller components, so they can be better understood and analyzed. Measures software by quantifying its functionality provided to the user based primarily on the logical design. Logical functionality from a sophisticated user view rather than a physical view. A standard method for measuring software development from the customers point of view 146 Sophisticated User Defines Requirements Participates in Acceptance Testing Understands flow of Information Subject Matter Experts (SMEs) 147

19 Issues of Function Point Analysis Does not accurately size heavy algorithm applications Hard to understand and to use Developed for MIS Type applications Does not take into account many other factors 148 Counting Procedures Step 1 -- Determine Type of Count Step 2 -- Establish the Boundary Step 3 -- Identify and Rate Transactional Function Types (assume an average value) Step 4 -- Identify and Rate Data Function Types (assume an average value) Step 5 -- Determine the Value Adjustment Factor (assume a value of 1) Step 6 -- Determine Adjusted Function Point Count 149

20 Determine type of Count Identify Boundary Count Transactional Function Types Count Data Function Types Determine Unadjusted Function Point Count Determine Adjusted Function Point Count 150 User Domain Boundary External Inputs (EI) External Outputs (EO) External Inquiries (EQ) Internal Logical Files (ILF) EQ EI EO External Interface Files (EIF) Application Boundary Other Applications 151

21 EI Boundary EQ Other Applications ILF B EIF ILF A ILF C EO EI 152 Components of Function Point Analysis Transactional Function Types External Inputs (EI) External Outputs (EO) External Inquiries (EQ) Data Function Types Internal Logical Files (ILF) External Interface Files (EIF) 153

22 Function Point Calculation Table Functional Complexity External Inputs External Outputs External Inquiries Internal Logical Files External Interface Files Low Average High Total x 3 = x 4 = x 6 = x 4 = x 5 = x 7 = x 3 = x 4 = x 6 = x 7 = x 10 = x 15= x 5 = x 7 = x 10 = Unadjusted Function Points Multiplied by Value Adjustment Factor Adjusted Function Points 154 High Level FPA Process Application Documentation Application Experts FPA Rules FPA FP FPA FPA Major Processes FPA for Transactional Function Types FPA for Data Function Types FPA for GSCs 155

23 Function Point Domain EIs, EOs and EQs Transactions Rating is dependent on transactions and files Files ILFs and EIFs Rating is independent of transactions 156 FPA for Transactional Function Types Application Documentation Transaction Model Data Model FPA Rules Transaction Rules T1. Identify Transaction T2. Type of Transaction (EO, EI, EQ) T3. Determine DET s & FTR s T4. Classify as Low, Average or High Functional Complexity Tables of Weight T5. Values Determined T6. All Transactions are summed to obtain UFP for Transactional Function Types. 157

24 EI EI ILF A ILF C ILF B EQ EO EI EI EQ EO ILF A ILF B ILF C ========== 3 ILF s (FTR s) 2 EI s, 1 EQ, 1 EO 158 FPA for Data Function Types Application Documentation Transaction Model F1. Identify logical groupings of information Data Model FPA Rules File Rules F2. Determine if ILF or EIF F3. Determine RET s & DET s F4. Low, Average or High Functional Complexity F5. Values Determined Tables of Weight F6. All Files are summed to obtain UFP for Data Function Types. 159

25 Rating Components Component RET s FTR s DET s External Inputs External Outputs External Inquiries Internal Logical Files External Interface Files 160 Identifying RET s, DET s and FTR s Record Element Type (RET): A RET is user recognizable sub group of data elements within a ILF or an EIF. It is best to look at logical groupings of data to help identify them. Data Element Type (DET): A DET is a unique user recognizable, nonrecursive field. File Type Referenced (FTR): A FTR is a file type referenced by a transaction. An FTR must also be a internal logical file or an external interface file. 161

26 Function Point Calculation Table Functional Complexity External Inputs External Outputs External Inquiries Internal Logical Files External Interface Files Low Average High Total x 3 = x 4 = x 6 = x 4 = x 5 = x 7 = x 3 = x 4 = x 6 = x 7 = x 10 = x 15= x 5 = x 7 = x 10 = Unadjusted Function Points Multiplied by Value Adjustment Factor Adjusted Function Points 162 Data Elements Types (DET s) Transactional Functional Types -- data input fields, error messages, buttons, data fields on reports, and calculated values. Data Function Types -- unique user recognizable, non recursive fields (columns of information) 163

27 Inventory Report University MousePads Inc. Item Description Quantity Hawk Pad University of Iowa MousePad 1,250 JayPad University of Kansas MousePad 500 HuskerPad University of Nebraska MousPad 3,000 Total MousePads 4, Inventory Report University MousePads Inc. 1 3 Item Description Quantity Hawk Pad University of Iowa MousePad 1,250 JayPad University of Kansas MousePad 500 HuskerPad University of Nebraska MousPad 3,000 2 Total MousePads 4,

28 Data Element Types for GUI s Radio Buttons Check Boxes Command Buttons Result of a Pick List Box Sound Bytes Photographic Images 166 Data Element Types for Real Time and Embedded Systems Temperature Lamp (on / off) Channel Pressure Units (psi / mbar) Polarity (Normal / Reverse) Pressure Type (Pressure / Vacuum) 167

29 External Inputs Defined Is an elementary process in which data or control information crosses the boundary from outside to inside. The data may come from a data input screen or an other application. The data is used to maintain one or more internal logical files. Maintain means to add, change or delete information. An external input is rated based upon the number of data elements types (DET s) and the number of files referenced (FTR). 168 EI EI ILF A ILF B EI & 1 FTR (ILF) EI & 1 FTR (ILF) EI & 1 FTR (ILF) 3 EI s, 3 ILF s ILF C EI 169

30 ILF B ILF A ILF C EI 1 EI and 2 FTR 170 EI ILF B ILF A ILF C 1 EI and 2 FTR 171

31 Control EI EI ILF B ILF A ILF C 1 EI and 0 FTR 172 Control EI ILF B EO ILF A ILF C 1 EI and 0 FTR 173

32 What Makes External Inputs Unique? Unique Processing Logic Different ILFs and EIFs updated and referenced Different Calculations and/or Algorithms Data Elements identified are different from other external inputs for the application. 174 Examples of External Inputs Business Data: customer name, address, phone, so on and so forth that updates an internal logical file (ILF). Control Data: sort sequence, printer port, number of copies may or may not update an ILF. Rules Data: number of days before customer is placed for collection, updates an ILF. 175

33 Examples of External Inputs Real Time Systems Hardware to Software states Operator Controls Volume Controls Sensor Readings Radio Frequencies Standard and Limit Settings (Alarm Settings) Other Subsystems Outputs Initialization Files (control input) 176 Examples of Invalid External Inputs Log on Screens -- counted as an external inquiry Menus -- impacts usability not functionality Navigational Screens -- impacts usability not functionality Reference Information -- counted as external interface file 177

34 Rating External Inputs File Type Referenced (FTR s) Data Elements (DET s) Greater than 15 Less than 2 Low Low Average 2 Low Average High More than 2 Average High High 178 Examples of Data Elements for an External Input Data Input Fields: customer name and other business information GUI: Radio buttons and check boxes Calculated Values that are stored Error Messages: a transaction was not completed 179

35 Identification Rules for an EI Data is received from outside the application boundary. The data in an ILF is maintained though an elementary process. The process is self contained and leaves the business of the application being counted in a consistent state. Processing Logic must be unique. 180 External Outputs Defined An elementary process in which derived data passes across the boundary from inside to outside. The data creates reports or output files sent to other applications. These reports and files are created from one or more internal logical files and/or external interface files. Derived Data is data that is processed beyond direct retrieval and editing of information from internal logical file or external interface files. Derived data is usually the result of Edits, Algorithms, or calculations. 181

36 What Makes an External Output Unique? Processing Logic Different Different ILF s and EIF s read and referenced Unique Set of Calculations 182 A/B = C EO ILF A Derived Data ILF B A * B = D (A,B) =X External Output (EO) and 2 FTR s 183

37 Examples of External Outputs EO s almost always contain business data Notification Messages are considered EO s. A notification message is the result of some business logic processing. Textual Reports Graphical Reports Reports produced on different media Electronic Outputs to other applications 184 EO ILF A Derived Data ILF B External Output (EO) and 2 FTR s 185

38 Examples of Data Elements for an External Output Error Messages Calculated values on a report Values on a report that are read from a ILF or EIF Non recursive values Generally, do not count report headings (literals) as data elements unless they are dynamic. 186 ILF A ILF B EO EO ILF C 2 EO s 187

39 Alarms External Outputs Real Time Systems Displays to Operator Panels Communication sent to Hardware Devices Electronic transmission to other sub-systems Graphical displays 188 EO ILF A Derived Data Error Message ILF B 4 DET s (Blue, Yellow, Green, & Error Message) 1 EO, 2 FTR s & 4 DET s 189

40 Rating External Outputs File Type Referenced (FTR s) Data Elements (DET s) Greater than 19 Less than 2 Low Low Average 2 or 3 Low Average High More than 3 Average High High 190 Examples of Invalid External Outputs Error Messages Reports that do not contain derived data Output side of an inquiry Undefined Ad-Hoc reports Confirmation Message 191

41 Identification Rules for EO s The process sends data or control information external to the application s boundary. The data or control information is sent via an elementary process. The process is self contained and leaves the business of the application in a consistent state. Processing logic must be unique. 192 External Inquiries Defined An elementary process with both input and output components that result in data retrieval from one or more internal logical files and/or external interface files. The input process does not maintain any internal logical files. The output side does not contain derived data. Unique processing logic from other EQ s (edits, a reference to or use of an ILF or EIF). 193

42 Examples of External Inquiries Log On screens Request for a specific record Help request and answer Listing of information 194 EQ ILF A ILF B (A,B) =X 195

43 ILF C EQ ILF A or ILF B (A,B) =X 1 EQ s, 3 FTR s & 3 DET s 196 Examples of External Inquiries Real Time Systems Request Current Parameter Settings Request Current Hardware State Display of Stored Data Current Standards and Limits 197

44 Searching EQ ILF A Request (input side) ILF B Searching = 1 DET (input side) (A,B) =X 198 Not Found EQ Request (input side) ILF A ILF B (A,B) =X Not Found = 1 DET (output side) 199

45 Searching ILF A Not Found EQ Request (input side) ILF B (A,B) =X Total DET s = 4 DET (input + output side) 200 Examples of Data Elements for an External Inquiry Input Side a customer name to search on a click of the on a scroll bar Output Side a listing of customers by name display of a particular customer 201

46 Examples of Invalid External Inquires Screen data that contains derived data Navigational Screens Error/Confirmation Messages 202 Identification Rules for an EQ An input request enters the application boundary. Output results exist the boundary. Data is retrieved. The data retrieved does not contain derived data. The input request and output results together make up a process that is considered an elementary process. Process does not maintain or update an ILF. Must be unique from other EQ s. 203

47 New Customer Exercise

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49 Internal Logical Files Defined A user identifiable group of logically related data or control information that resides entirely within the applications boundary and is maintained through External Inputs. 208 Examples of Internal Logical Files Business Data (customer name, tax id, address) Control Data (color, copies, printer port) Rules Based Data (meta data, payment criteria, tax zones) 209

50 Examples of Internal Logical Files Real Time Systems Log Files Diagnostic Files Hardware Parameter Settings Initialization Files Data Files 210 Rating Internal Logical Files Record Element Types (RET s) Data Elements (DET s) Greater than 50 1 Low Low Average 2 to 5 Low Average High More than 5 Average High High 211

51 ILF Identification Rules Group of data or control information is logical, user identifiable, and fulfills specific user requirements. Data is maintained within the application boundary. Data is modified via an elementary process (one or more EI s). Has not been counted as an EIF for the application. 212 Examples of Record Elements A RET is user recognizable sub group of data elements within a ILF or an EIF. It is best to look at logical groupings of data to help identify them. Groupings can be either optional or mandatory 213

52 1 ILF, 2 RET 2 ILF, 1 RET each 214 EI Temporary ILF 1 EI and 1 ILF 215

53 Cache? ILF B EQ 1 EQ 1 EO ILF C EO 216 Examples of External Interface Files Reference Information Edit data Control Information Information that does not update an internal logical file 217

54 Examples of External Interface Files Real Time Systems Other systems hardware state Data that belongs to another system or application Control Information Information that is used but that does not update any internal logical file 218 Application A Application B ILF B ILF A EIF ILF C EO 1 ILF 1 EIF 1 EO, 2 FTR 219

55 EI Application B ILF EI ILF ILF EI 220 Rating External Interface Files Record Element Types (RET s) Data Elements (DET s) Greater than 50 1 Low Low Average 2 to 5 Low Average High More than 5 Average High High 221

56 Function Point Calculation Table Functional Complexity Low Average High Total External Inputs x 3 = x 4 = x 6 = External Outputs x 4 = x 5 = x 7 = External Inquiries x 3 = x 4 = x 6 = Internal Logical Files x 7 = x 10 = x 15= External Interface Files x 5 = x 7 = x 10 = Unadjusted Function Points Multiplied by Value Adjustment Factor X 1.0 Adjusted Function Points 222 External Interface Files Defined A user identifiable group of logically related data that resides entirely outside the applications boundary and is not maintained by the application. An external interface file is an internal logical file for another application. 223

57 EIF Identification Rules Group of data or control information is a logical, user identifiable, and fulfills specific user requirements. Group of data is referenced by, and external to, the application being counted. Group of data has not been counted as an ILF by the application. 224 General System Characteristics There are 14 general system characteristics (GSC s) that rate the general functionality of the application being counted. Each characteristic has associated descriptions that help determine the degrees of influence of the characteristics. 225

58 User Domain Boundary External Inputs (EI) External Outputs (EO) External Inquiries (EQ) Internal Logical Files (ILF) EQ EI EO External Interface Files (EIF) Application Boundary Other Applications 226 Sophisticated User Defines Requirements Participates in Acceptance Testing Understands flow of Information Subject Matter Experts (SMEs) 227

59 Determine type of Count Identify Boundary Count Transactional Function Types Count Data Function Types Determine Unadjusted Function Point Count Determine Adjusted Function Point Count 228 Calculating Adjusted FP Count Development DFP = (UFP + CFP) * VAF Where: DFP is development function point count UFP is unadjusted function point count CFP is the function point count added by the conversion unadjusted function point count VAF is the value adjustment factor (assume = 1) 229

60 Calculating Adjusted Function Point Count Enhancement Project Function Point Calculations EFP = [(ADD + CHGA + CFP) * VAFA] + (DEL* VAFB) EFP is the enhancement project function point count. ADD is the unadjusted function point count of those functions that were added by the enhancement project. CHGA is the unadjusted function point count of those functions that were modified by the enhancement project. This number reflects the functions after the modifications. CFP is the function point count added by the conversion VAFA is the value adjustment factor of the application after the enhancement project. DEL is the unadjusted function point count of those functions that were deleted by the enhancement project. VAFB is the value adjustment factor of the application before the enhancement project. 230 EFP Simplified EFP = [(ADD + CHGA + CFP) * VAFA] + (DEL*VAFB) Assume that CFP = 0 and VAFA=VAFB=1 Hence, EFP s = (ADD + CHGA+DEL) 231

61 Application After Enhancement Project AFP = [(UFPB + ADD + CHGA) - (CHGB + DEL)] * VAFA or AFP = (UFPB+ADD + CHGA-CHGB - DEL)* VAFA Where UFPB = Unadjusted Function Points Before ADD = Added Function Points CHGA = Change After CHGB = Change Before DEL = Deleted VAFA = Value Adjustment Factor After Enhancement (assume = 1.0) 232 AFP Simplified AFP = (UFPB+ADD + CHGA-CHGB - DEL)* VAFA Assume, CHGA = CHGB, DEL = 0 Then AFP s = (UFPB +ADD) * VAFA 233

62 Application Function Point Count AFP = ADD * VAF Where: AFP is the initial application function point count. ADD is the unadjusted function point count of those functions that were installed by the development project. VAF is the value adjustment factor of the application (assume = 1). 234