faculty coach: professor martinez justin mahar chris baum greg schmitz adam abdelhamed

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Faculty Coach: Professor Martinez Justin Mahar Chris Baum Greg Schmitz Adam Abdelhamed

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Page 1: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Faculty Coach: Professor Martinez

Justin MaharChris BaumGreg SchmitzAdam Abdelhamed

Page 2: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Project Summary Process

SEEM Current Reflections

Website CVS

Product Progress Research Prototype

Future Plans Questions

Page 3: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 4: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

A self contained computer system that allows input from multimedia devices and uses a touch screen monitor to receive input from the user.

Customers use this device to print Kodak quality images from their digital media.

They can edit images, create collages, and photobooks.

Page 5: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

A collage is a collection of images placed on a single page.

The images are assorted in a pleasing manner.

The collage may also contain text.

A photobook is a collection of collages bound together into a book.

Page 6: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

An improved collage layout component. New features Improved collage output

Windows demo application. Demonstrates improvements Proof-of-concept using Web Forms

Page 7: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Performance The new algorithm must run in equal or

better time than the current one. The new algorithm must produce a

better collage than the current one.Platform/Language

C# code to be run on a Windows XP embeddded system.

Web Forms (ASP.NET)

Page 8: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Software Engineering Effectiveness Model (SEEM)

Created by former RIT Software Engineering professor Tom Bullinger

Built on best practices of eXtreme Programming and the Rational Unified Process

Waterfall-like model

Page 9: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 10: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 11: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 12: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 13: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 14: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 15: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Immaturity in SEEM Process

Separation of our product from Kodak’s

Team Development Performing

Communication with Coach

Page 16: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Task Time Estimation vs. Actual Where is time being spent?

Bugs Bugs per line Time to fix bugs

Page 17: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Dreamweaver for design

Page 18: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Housed in CVS repository

Updated regularly from CVS

Latest deliverables readily available to sponsors

RSS Feed, PHP, Meeting Agenda, Dynamic Linking, and Password Protection

Page 19: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 20: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Simulated Annealing Algorithm provided by Kodak

Collage Layout Properties

Kodak’s current Kiosk workflow

ASP.NET for application implementation

Page 21: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Solid understanding of existing algorithm

Identified areas where improvements can be made

Identified some implementation risks

Page 22: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Layout properties are used to determine the quality associated with the collage

Examples: White Space, Alignment, Separation, Balance etc.

The more properties used in calculations, the better the calculation of the collage’s quality

Page 23: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Used as a basis for the workflow in our application Allows for easy migration to Kiosk

Small changes must be made to better suit our application Ex. More transitioning between states

Page 24: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Allows our application to run on the kiosk as well as web-based platforms

Algorithm updates can easily be made

Allows our application to run on a local client as well as remote clients

Page 25: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Prototype

Page 26: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Assumptions are bad

Complex Algorithm▪ Performance▪ Layout Output Quality

Page 27: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Simulated Annealing – low risk at a high level Team has identified two classes of high risk

components Random layout generation algorithms Energy (quality) factor analysis algorithms

Page 28: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

• Value to the project– Provides the ability to quickly “test drive”

prototyped implementations of risky components• Algorithm Tracing• Visual Feedback• Tabular Feedback–Configuration Capture– Performance Data– Layout Quality

– Minimizes uncertainty and risk– Helps team determine which components

make it into production– Demonstrates progress to sponsor/coach

Page 29: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 30: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 31: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 32: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 33: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 34: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed
Page 35: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Solution Design in the next two weeks Based on our Problem Analysis Includes Interface Prototypes and

Interface SpecificationContinue prototype development on

the Algorithm Used as proof-of-concept Possible use in final implementation

Page 36: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed

Implement Solution Phase (Starts 2/29/2008) Includes User Documentation and

Acceptance TestsDeploy Product (Ends 4/25/2008)

Metrics Report Acceptance Test Results Project Reflection

Stretch goals (if time allows)

Page 37: Faculty Coach: Professor Martinez  Justin Mahar  Chris Baum  Greg Schmitz  Adam Abdelhamed