This presentation shows the way the functional size measurement method COSMIC can be used to measure the functional size of mobile apps.

1. Measure the functional size
of a mobile app
Harold van Heeringen & Edwin van Gorp

2. |
Measure the functional size
of a mobile app
Using the COSMIC functional size measurement method
Harold van Heeringen
Senior consultant software metrics
Department Sizing, Estimating & Control
Sogeti Nederland B.V.
harold.van.heeringen@sogeti.nl
@haroldveendam Rotterdam, October 6th, 2014
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3. |
Overview
 Reasons for this paper/presentation;
 Mobile apps – why are they different?;
 Why measure apps using COSMIC?;
 Short COSMIC overview;
 The proposed approximate method;
 Conclusions.
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4. |
Beware!
 This is a technical paper/presentation!
 Knowledge of the COSMIC method is required!
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5. |
Reasons for this paper/presentation
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6. |
Why?
 IT industry is changing – new types of applications and
ways to interact with software arise, for example:
 Cloud computing;
 Google glass;
 Mobile apps.
 Software sizing, estimation and benchmarking
challenges:
 Fixed price/fixed date app development.
 Need for methods and guidelines to apply standards
to sizing, estimating and benchmarking.
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7. |
Mobile apps
 Do I really have to introduce these?
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8. |
Some characteristics
 Downloaded on a mobile device, like phone or tablet;
 Connects to the internet (Wi-Fi/cellular);
 Many different application types;
 Touch screen;
 Use of GPS: content and functionality change,
depending on location;
 Use of motion sensor: motion of device can result in
different display;
 Content updates automatically;
 Functionality may be updated periodically.
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9. |
Mobile apps – why are they different?
 More ways of user interaction:
 Changing position of device: toggling;
 Voice input, e.g. Siri;
 Reaction to real-time events:
 Reach a certain location: message ‘flasher’;
 Unclear where data is stored:
 On device/on backend/in cloud;
 Functionality to handle disruptions:
 E.g. an incoming call;
 Specific non-functional requirements:
 Security, performance, data traffic, battery use.
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10. |
Why measure apps using COSMIC?
 Measuring mobile apps with the IFPUG method has
already been published (the IFPUG guide to IT and
software measurement).
 Using COSMIC may produce even better results:
 More accurate measurement due to ratio scale;
 Concepts of layers and peer components fits
mobile app architectures;
 Lack of knowledge of the data model is no show
stopper for COSMIC.
 Objective: create an approximate method to
accurately size mobile apps using COSMIC.
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11. |
Short COSMIC overview
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12. |
Entries  functional process
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Triggering
event
is sensed
by
Triggering
Entry
Functional
Boundary
user
Functional
process

13. |
Functional processes and data movements
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Functional User
Requirements
Functional
processes
Sub-processes
Software
Data movement Data manipulation

14. |
COSMIC overview
Users Functional process Data
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W
E
X R

15. |
The proposed approximate method
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16. |
Basic assumptions
 A mobile app is an application layer, developed on
top of one ore more data layers:
 The physical location of the data layer is irrelevant;
 Logically, no persistent data is stored in the application
layer:
 No Reads/Writes are measured, only Entries/eXits;
 The app can use certain process data that is
spontaneously present:
 E.g. date + time and GPS location;
 Mobile apps are considered business applications:
 One eXit for all (error) messages;
 (Error) messages come from data layer: 1 Entry.
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17. |
Measurement strategy
 Equal to ‘standard’ COSMIC measurements, identify:
 Purpose, e.g. estimate realisation phase;
 Scope, e.g. a set of functional requirements;
 Functional users, e.g. the end users that download
the app from the app store;
 Level of granularity, e.g. functional process level.
 Keep basic assumptions in mind when doing so.
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18. |
Mapping phase
 Equal to ‘standard’ COSMIC measurements, identify:
 Functional processes;
 Objects of interest;
 Data groups.
 Keep basic assumptions in mind when doing so.
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19. Measurement phase: approximate method
|
 Two steps:
1. Indentify the type of functional process;
2. Quantify the parameters involved.
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20. |
Functional process types
 Looking at the primary intent of a functional process:
1. View functionality;
2. Data manipulation (add, change, delete);
3. Enquiry (before update);
4. User supporting functionality, e.g. list box, selection
screen, pop-up function);
5. Special functionality:
• Dynamically generated menus;
• Log in/log out functionality;
• Help functionality;
• Invoking external functionality.
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21. |
View functionality
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22. |
View functionality
 Basic view functional process: 6 CFP;
 1 OOI/1 data group:
 For each additional OOI/data group:
 For each calculated/derived data group: 1 eXit.
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E Start entry
X Question for information to the data layer
E Receiving data
E Receiving application error messages
X Show data
X Show application error messages
E Receiving data
X Show data

23. Data Layer
|
View functional process
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Application layer
E
X
E
X
6 CFP
X
E
OOI / data group
Messages

24. Measurement phase: approximate method
|
 For each functional process with primary intent to
present data to at least one of the functional users:
4 CFP
+ (2 CFP * number of data groups derived from the
data layer)
+ (1 CFP * number of data groups with calculated
and/or determined data)
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25. |
Data manipulation functionality
 Basic add/change/delete functional process: 4 CFP:
 For each additional OOI/data group manipulated:
 For each data group shown to the user:
X Question for information to the data layer
E Receiving data
X Show data
 For each validation for which referential data is needed:
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E Start entry
X Providing information to the data layer
E Receiving application error messages
X Show application error messages
E Entering data
X Providing information to the data layer
X Questions for information to the data layer
E Receiving data

26. Measurement phase: approximate method
|
 For each functional process with primary intent to
manipulate data for at least one of the functional
users:
2 CFP
+ (2 CFP * number of data groups manipulated)
+ (3 CFP * number of displayed data groups)
+ (2 CFP * number of validations with referential data)
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27. |
Enquiry / user supporting functionality
 Enquiry functionality (before update):
 Identical to view functionality.
 User supporting functionality (non mandatory):
 Identical to view functionality.
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28. |
Special functionality - help
 One functional process per help functionality type;
 Identical to view functionality.
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4 occurrences of the same
output-type

29. |
Special functionality – Login / Logout
 Standard log in: 5 CFP.
 Log status is process data spontaneously present in all
functional processes.
 Standard Log out: 2 CFP.
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E Start entry
X Providing credentials to the data layer
E Receiving log status
E Receiving application error messages
X Show application error messages
E Start entry
X Show application error messages

30. |
Conclusions
 This approximate method is intended to be a guideline
to apply the COSMIC FSM quickly and correctly when
measuring mobile apps;
 Based on a few simple steps, the size measurement
can be easily generated:
1. Indentify the type of functional process;
2. Quantifying the parameters involved.
 Please read the paper if you are interested in a more
detailed explanation of the method.
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31. Thank you for your attention.

32. Harold van Heeringen
Senior Consultant Software Metrics /Software Cost Engineer
Sogeti Sizing, Estimating & Control (SEC)
@haroldveendam
harold.van.heeringen@sogeti.nl
President ISBSG (International Software Benchmarking Standards Group
(www.isbsg.org))
Board member NESMA (Netherlands Software Metrics Association (www.nesma.org))
IAC member COSMIC (www.cosmicon.com)