Process



1. Review my comments on the previous iteration (in class)
2. See if you can get any missing information by talking to some one, reading something, or looking on the web.
3. Make changes to your Project Scope.
4. Explode/Refine the Context DFD into a fish eye level-0 DFD See [ p1DFD0.gif ] for an example level 0 fish-eye DFD expanding on the previous [ p1DFD.gif ] context DFD.
5. Provide details on one Data Flow in your DFDs.
6. Do a Cost-Benefit Analysis:
   
   1. List of Benefit/Cost + Value(Intangible or Money) + When(+Periodic or once).
   2. A spreadsheet of costs and benefits vs time discounting future cash flows.
      Table

      Time	Cost	Benefit	Cash-flow	Discount	Present Value
      0	c	b	b-c	1	b-c
      ...
      Net PV	-	-	-	-	???

      
      (Close Table)
      
   
   Note: assume you've got 10 person weeks of free programming.
7. What do you estimate the ROI and the break even point to be?
8. Then rethink your project: how can it be developed? How to make sure it has a good ROI? Revise the spreadsheet...

9. Work in same teams.
10. Start in class, finish ready for next class.
11. Spend time in class planning in detail who does what, where, when, and possibly how.

12. Deliverable: List of costs and benefits with guesstimated values. Due at the start of the next class. Also present to next class one slide/page DFD. Hand in paper copy with team names and detailed cost/benefit analysis and DFDs.

    Note: you can include 10 weeks of programming/testing/implementation by each member of the team with about 4 hours per week at zero cost (CSci375).




Deliverables



1. Cover sheet with project name and names of people on team
2. A Copy of the Cost-Benefit analysis and ROI
3. A Fish eye DFD of context and Level 0 DFD [ a4.html ] Here you show a single process and its environment and THEN describe some of idea of how to construct it -- or how it works. Don't forget to label data flows.
4. Hand in one detailed description of an important data flow. Provide at least the following meta-data that would be in a data dictionary:
   • Label/Name on DFD
   • Description
   • Aliases (if any)
   • Origin
   • Destination
   • Record Structure (name + the fields and data elements)
   • Volume and Frequency: how much, how often?

. . . . . . . . . ( end of section Project Iteration 2 -- More details) <<Contents | End>>

Abbreviations