代写代考 SWEN90016 Software Processes and Project Management -2- Cost Estimation

School of Computing and Information Systems The University of Melbourne
Copyright University of Melbourne 2018 – 2022
2022 – Semester 1 Lecture Week 6

Software Processes & Project Management
Function points (in depth example)

SWEN90016 Software Processes and Project Management -2- Cost Estimation

Function Points (FP)
• Is used to express the amount of functionality in a software system, as seen by the user
• A higher number of function points indicates more functionality
– Empirical evidence demonstrates that there is a positive correlation
between function points and the complexity of the system
• Typically used to:
– Estimate the cost and effort required to design, code and test a software system
– Predict the number of errors
– Predict the number of components
– Measure productivity
• Function points are computed from the Software Requirements Specification (SRS)
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Software Requirements
• Software Requirements Specification (SRS)
– A document that specifies what is expected of a software
system; referred to as the requirements of the system – It contains:
• Functional Requirements:
– Specify the functions that are required in the system
• Non-functional Requirements:
– Specify requirements that are not directly functions, such as performance (quality requirements)
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FP Computation Steps
1. Categorize requirements
2. Estimate a
complexity value
for each category or function
3. Compute count total from Complexity
4. Estimate value adjustment factors
5. Compute total function point count
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Example: Automated Trading System
Automated Trading System: Functional Requirements
Read the previous day’s trading information (high price, low price, opening price, closing price) from a third-party-server.
Save a complete “price history” in a database.
Based on the trends in prices for commodities, decide which commodities to bid for, and which to try to sell.
Send information to an external e-trading account which places the bid/ask for each commodity.
When the bid/ask is either accepted or expires, record the result in a “transaction history” database.
At the end of the day, produce a report that summaries the transactions of the day along with the following information: profit/loss for the day; number of trades of each commodity; average market price of all commodities; account summary.
At anytime the user can request a transaction history for a period which gives: transaction IDs; commodity type; bid/ask; price.
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FP Computation – Step 1
1. Categorize Requirements
Data Functions
Data Functions:
Function (Requirement)
Transaction Functions
• Concerned with maintenance of the data for the application –
Internal Logical Files (ILF), External Interface Files (EIF)
Transaction Functions:
• Concerned with information being passes to and from the system –
External Inputs (EI), External Output (EO), External Inquiries/Queries (EQ)
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FP Computation – Step 1
1. Categorize Requirements (five categories) Data Functions
Internal Logical File (ILF)
• A logical grouping of data that the system maintains over a period of time, and is modified using external inputs
examples – tables in a relational database, files containing user setting
External Interface File (EIF)
• A logical grouping of data that is maintained external to the system, but which may be used by the system.
examples – are the same as ILFs, except that the data is maintained outside the system, such as data hosted on a third- party servers, or data structures holding information about system state
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FP Computation – Step 1
Transaction Functions
External Input (EI)
• An input to the system from a user or another application, which is used to control the flow of the system, or provide data. External inputs generally modify internal logic files
examples – data fields populated by users, inputs files (e.g. program source code to a compiler), and file feeds from an external application.
External outputs (EO)
• An output to the user that provides information about the state of the system
examples – screens, error messages, and reports that are shown to the user. Individual data fields in these are grouped as one external output
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FP Computation – Step 1
External Inquiries/Queries (EQ)
• the input is not used to update an internal logic file, but is used to query the internal logic file and provide an output; the output is retrieved directly, with no derived data included
examples – reading a user setting, or reading a record from a database table
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Example: Functional Requirements
Automated Trading System
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FP Computation – Step 1
EIs EOs EQs
Application Being Counted
Feeds (out) Reports
Other outputs
Other Inputs (online)
Data Feeds
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Example: Automated Trading System
Automated Trading System: Function Categories
Read the previous day’s trading information (high price, low price, opening price, closing price) from a third-party-server.
Save a complete “price history” in a database.
Based on the trends in prices for commodities, decide which commodities to bid for, and which to try to sell.
Send information to an external e-trading account which places the bid/ask for each commodity.
When the bid/ask is either accepted or expires, record the result in a “transaction history” database.
At the end of the day, produce a report that summaries the transactions of the day along with the following information: profit/loss for the day; number of trades of each commodity; average market price of all commodities; account summary.
At anytime the user can request a transaction history for a period which gives: transaction IDs; commodity type; bid/ask; price.
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FP Computation – Step 2
2. Estimate a complexity value for each category or function
– Complexity is ranked either simple, average or complex
– Normally assigned for a category rather than for each requirement – rather crude
– A technique commonly used is based on Data Element Types (DETs), Record Element Types (RETs), and File Type References (FTRs):
Data Element Types (DETs)
A unique, user-recognizable, non- repeated data field in a system
Record Element Types (RETs)
A user-recognizable subgroup of data elements in an ILF or EIF
File Type References (FTRs)
A file (ILF, EIF) referenced by a transaction
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FP Computation – Step 2
Relationship between DETs, RETs, FTRs, and the function categories
Internal Logical Files (ILFs)
External Interface Files (EIFs)
External Inputs (EIs)
External Outputs (EOs)
External Inquiries (EQs)
Complexity table for Data Functions Complexity table for Transaction Functions
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Example: Automated Trading System
Automated Trading System: Function Categories
Complexity
high price, low price, opening price, closing price, date
commodity name, high price, low price, opening price, closing price, date
Commodity, bid/asking price, buy/sell
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FP Computation – Step 3
3. Compute count total from Complexity
• Using count and complexity estimates compute total count
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Example: Automated Trading System
Automated Trading System: Computing Count Total
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FP Computation – Step 4
4. Compute value adjustment factors
• is computed based on 14 characteristics
• each of the characteristics is ranked on a scale of 0-5;
0 not important and 5 critical
• Data Communications
• Distributed Data Processing
• Performance
• Heavily Used Configuration
• Transaction Rate
• Online Data Entry
• End-User Efficiency
• Online Update
• Complex Processing
• Reusability
• Installation Ease
• Operational Ease
• Multiple Sites
• Facilitate Change
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Example: Automated Trading System
Automated Trading System: Value Adjustment Factors
• Data Communications – 2
• Distributed Data Processing – 4
• Performance – 5
• Heavily Used Configuration – 2
• Transaction Rate – 4
• Online Data Entry – 2
• End-User Efficiency – 5
Assume the rating for all other features is 2
Value Adjustment = 2*5 + 4*2 + 10*2 = 38
• Online Update – 2
• Complex Processing – 2
• Reusability – 2
• Installation Ease – 2
• Operational Ease – 2
• Multiple Sites – 2
• Facilitate Change – 2
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FP Computation – Step 5
5. Compute total function point
Count total and value adjustment factors are then plugged-in to the following formula to estimate the total point count
𝐹𝑃=𝑐𝑜𝑢𝑛𝑡𝑡𝑜𝑡𝑎𝑙 ×(0.65 +0.01 × σ14 𝐹) 𝑖=1 𝑖
Fi – VAF corresponding to the i-th VAF question
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Example: Automated Trading System
Automated Trading System: Compute total function point count
𝐹𝑃=𝑐𝑜𝑢𝑛𝑡𝑡𝑜𝑡𝑎𝑙 ×(0.65 +0.01 × σ14 𝐹) 𝑖=1 𝑖
FP = 29 x(0.65 + 0.01*38) = 29 x1.03
More information and examples of FPs can be found at https://alvinalexander.com/FunctionPoints/FunctionPoints.shtml
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Function Points
• Advantages of Function Points
– Measures the size of the solution instead of the size of the
– Requirements are the only thing needed for function points count
– Can be estimated early in analysis and design
– Is independent of technology
– Is independent of programming languages
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Function Points
• Disadvantages of Function Points
– A well defined requirements specification is necessary
– Gaining proficiency is not easy, the learning curve is quite long – Could be quite time-consuming thus could be costly
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Molkken, Kjetil and Jrgensen, , Kjetil and Jrgensen, Magne
References
1. B. Boehm, C. Abts, W. Brown, S. Chulani, B. Clark, E. Horowitz, R. Madachy, D. Reifer, and B. Steece. Software Cost Estimation with
Cocomo II. , 2000.
2. R. S. Pressman. Software Engineering: A Practitioner’s Approach. McGraw Hill, seventh edition, 2009.
3. I Somerville. Software Engineering, Addison- , ninth edition, 2010.
4. K. Molkken and M. Jrgensen, A Review of Surveys on Software Effort Estimation, Proceedings of the 2003 International Symposium on Empirical Software Engineering
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References
Molkken, Kjetil and Jrgensen, Magne
5. -Cong and De Tran-Cao, A review of effort estimation studies in agile, iterative and incremental software development, The 2013 RIVF International Conference on Computing Communication Technologies – Research, Innovation, and Vision for Future (RIVF)
6. M. Usman, E, Mendes and F. Weidt and R. Britto, Effort Estimation in Agile Software Development: A Systematic Literature Review, Proceedings of the 10th International Conference on Predictive Models in Software Engineering, 2014
7. PMI’s PULSE of the PROFESSION -https://www.pmi.org/learning/thought- leadership/pulse/pulse-of-the-profession-2017
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References
1. B. Boehm, C. Abts, W. Brown, S. Chulani, B. Clark, E. Horowitz, R. Madachy, D. Reifer, and B. Steece. Software Cost Estimation with
Cocomo II. , 2000.
2. R. S. Pressman. Software Engineering: A Practitioner’s Approach. McGraw Hill, seventh edition, 2009.
3. I Somerville. Software Engineering, Addison- , ninth edition, 2010.
4. A Review of Surveys on Software Effort Estimation
5. A review of effort estimation studies in agile, iterative and incremental software development, The 2013 RIVF International Conference on Computing Communication Technologies – Research, Innovation, and Vision for Future (RIVF)
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