Docstoc

Software Requirements

Document Sample
Software Requirements Powered By Docstoc
					Software Requirements

  Requirements for Actuarial Model Outcome
  Optimal Fit (AMOOF)


            Team Leader:      Daniel Hanson

            Lead Developer:   Matthew Miller

            Q.A. Manager:     Jon Swenson

            Lead Tester:      Edward Badgley
Table of Contents



       INTRODUCTION................................................................................................................................. 1
       PROJECT OVERVIEW...................................................................................................................... 2
       OPERATION, DEVELOPMENT, AND MAINTENANCE ENVIRONMENTS ..................... 3
       SYSTEM MODEL ................................................................................................................................ 4
       FUNCTIONAL REQUIREMENTS .................................................................................................. 5
          RUN CALCULATIONS ........................................................................................................................... 5
          REQUEST PLOTS ................................................................................................................................... 6
          ENTER DATA ........................................................................................................................................ 7
          EDIT OPTIONS ...................................................................................................................................... 7
          SAVE WORKSPACE............................................................................................................................... 7
          OPEN WORKSPACE .............................................................................................................................. 7
       NONFUNCTIONAL REQUIREMENTS ......................................................................................... 8
          ACCURACY........................................................................................................................................... 8
          DATA SETS ........................................................................................................................................... 8
          RESOURCE CONSTRAINTS.................................................................................................................... 8
          USER INTERFACE ................................................................................................................................. 8
       FEASIBILITY ....................................................................................................................................... 9
         MINIMUM SYSTEM............................................................................................................................... 9
         PLANNED SYSTEM ............................................................................................................................. 10
         IDEAL SYSTEM ................................................................................................................................... 10
       APPENDIX A: GLOSSARY ............................................................................................................. 12

       APPENDIX B: USE-CASES ............................................................................................................. 14

       APPENDIX C: DATA FLOW DIAGRAM OF CALCULATIONS .......................................... 27
Introduction

       Current statistical software packages on the market can often fit the data to standard
       probability distributions, but none we have encountered include the mixed distributions
       commonly used in the actuarial field. The software solution we will create, Actuarial Model
       Outcome Optimal Fit (AMOOF), will find the best first standard probability distribution, then
       determine if a mixed distribution is needed; if a mixed distribution is required the software
       package will find the best fit mixed distribution. The idea for this project comes from a
       paper by our client, Dr. Yvonne Chueh, which can be found at:

       http://www.actuaries.ca/meetings/stochasticsymposium/Papers/Yvonne%20Chueh.pdf.

       Dr. Chueh is a Professor in the Mathematics department of Central Washington
       University. Actuarial Science and Insurance Modeling, areas in which Dr. Chueh
       specializes, can benefit from software that can fit data to mixed distributions. Dr. Chueh
       would like to be able to market this software, and in that case the program may be used by
       anyone who practices or researches Actuarial Science, in addition to our client.

       This document covers the requirements of the proposed software solution to this problem.
       This document is for the use of the client, developers, project managers and testers. The
       sections that follow are:

          Project Overview: covers the factors dictating this project.

          Development, Operation and Maintenance Environments: details of the hardware and
           software environments required for these three phases of the program.

          System Model: describes the major components of the system.

          User Interaction: covers the user’s view of the proposed program’s capabilities.

          Functional Requirements: explains the necessary abilities of the program.

       1. Nonfunctional Requirements: describes restrictions on the program not related to the
          specific functions of the system.

          Feasibility: describes the probability of completing this project with our resources, the
           minimum system that fulfills our requirements, and the system we would prefer to
           develop.

          Appendices: contains all diagrams referred to in this document as well as a glossary
           of lesser known terms.




                                                     1
Project Overview

       The purpose of AMOOF is to find a parametric probability model that best describes a set
       of data. This model, or probability distribution, can then be used to make predictions based
       on the data. This model must be as accurate as possible because, for example,
       companies may use this information to decide the allocation of resources.

       To describe a data set AMOOF will use a probability distribution. When AMOOF
       calculates the best fit distribution it will first look for a best fit standard probability
       distribution, or probability density function (PDF). AMOOF will determine if a mixed
       distribution is needed by comparing the statistics of the data to the parameters of the best
       fit PDF. AMOOF will then determine if a mixed distribution is needed. When mixed
       distributions are determined to be necessary, AMOOF will find the best fit distribution of
       the weighted average of two PDFs.

       It is not feasible to find optimal probability distributions without software aid as data sets
       can include thousands, or even millions, of points. There are software packages on the
       market that fit to standard distributions, but not mixed distributions that describe the data
       more accurately. Currently an actuary could use a spreadsheet program to optimize each
       probability distribution they want to test for a data set, and then determine the best fit
       distribution based on their spreadsheets. This process would require the creation of a new
       spreadsheet for each distribution and manual entry of each equation. AMOOF will reduce
       the time and knowledge needed to make predictions based on a given data set.

       AMOOF will allow the user to find the optimal model of their data with a straight forward
       interface. The user will be able to enter data into a spreadsheet or import data from a file.
       When the data has been entered, the user will be able to find the best fit probability
       distribution with the click of a button. A report will be generated after an optimal fit
       distribution has been found giving statistics of the original data set compared to the
       parameters of the distribution function. AMOOF will also allow the user to view the data
       and the distribution graphically with multiple graphing options available.

       During the development of AMOOF, there are several important constraints to be
       considered. AMOOF must be accurate and robust due to the importance of the decisions
       that may be made based on this program’s output. The resources allotted to the
       development of the software is a limiting factor as well, because the development team,
       composed of four CWU students, has less than three months to work on it in addition to
       their studies.




                                                     2
Operation, Development, and Maintenance Environments

       There are a few constraints on the Operation environment that will be used by AMOOF.
       The operation environment of the program’s target platform is the Microsoft Windows
       2000 or XP operating systems. In addition, AMOOF will require Microsoft Excel and the
       .NET Framework to execute. The computer must have 256mb ram and be a 1 GHz IBM
       compatible. Therefore, the operation environment is at a level in which users will need a
       current version of Windows running on a newer computer.

       Our package will be interacting with the Windows Operating System. The two main
       interactions will be with the Windows clipboard and the Windows file system. These
       interactions will allow the user to cut and paste from the clipboard and save and open data
       from files.

       To develop and maintain AMOOF will require a computer running Microsoft Windows XP.
       Microsoft Visual Studio .NET and Microsoft Excel will be used in developing the software
       package. The maintenance of our package will require the same environment as
       development. Therefore, the development and maintenance environments will only
       require Visual Studio .NET and Windows XP on a computer that meets the hardware
       requirements for running Windows XP and Visual Studio .NET.




                                                   3
System Model

      Two components of the System Model are calculations and plotting. The calculations are:
      data statistics, Maximum Likelihood Estimate (MLE) for the 22 probability density functions
      (PDF), and determining the best fit distribution. The plots are of the histogram of the data,
      the curve of the best fit probability distribution, and the histogram with best fit distribution
      function.

      Calculating the data statistics is straightforward. The statistics that are going to be
      calculated are mean, standard deviation, and six other moments of the data. We use the
      statistics when calculating the MLE.

      On the other hand, calculating the MLE is more difficult. To calculate the maximized MLE
      the statistics are used as a starting point. From there, an optimization to maximize the
      output of the likelihood function is performed. The program does these calculations for
      each of the 22 PDFs and each of the mixed distributions, if required.

      From the MLE calculations on each of the probability distributions, we compare the
      moments for each distribution to the moments of the data to find the relative error in the
      moments. The best fit probability distribution is the distribution with the least-relative error.
      The Data Flow Diagram in Appendix C describes the flow of data for calculating the best fit
      distribution.

      Creating the plots should not be overly difficult. The histogram will be based on the data
      set and the best fit probability distribution plot will be based on the best fit distribution.
      Once we program the individual plots, putting them together should be an easy process.

      There are three ways to enter data. The first is entering data directly into the spreadsheet.
      A second is to cut and paste the data into the spreadsheet. The last option is to import the
      data from a tab-delimitated file.

      Most users would like to save their calculations for future use. Our save workspace allows
      the user to save their work. If the calculations have been finished and the best fit
      probability distribution chosen, then these settings will save to the workspace as well.




                                                     4
 Functional Requirements

         A system provides functionality or services, these are the functional requirements. The
         functional requirements of this project are

            Run Calculations

            Request Plots

            Enter Data

            Edit Options

            Save Workspace

            Open Workspace

Run Calculations

         The run calculations requirement is the most involved of the requirements. There are two
         sets of calculations to be computed: calculation of the data statistics and calculation of the
         best fit distribution. The data statistic calculations will be simple to develop.

         The statistics of the data set input by the user are as follows. These calculations are the
         average, median, variance, and moments. Calculating the average is done by summing
         the data points and dividing by the number of data points. In mathematical notation the
         average is

                             n

                          x         i
             m1  X        i 1
                                         .
                                 n

         Closely related to the average is the median. The median is more of a choice of a data
         point than a calculation. To calculate the median the data set is put in order and the middle
         data point is selected. If the number of elements is even then the average of the two
         middle data points is used as the median. In a normal distribution, the average is equal to
         the median.

         Variance is the amount of difference in the data. A sum is produced by squaring the
         differences between each data point and the mean and adding the products. This sum
         divided by the number of elements creates the average sum of products. The
         mathematical equation is

                                 n

                            (X  x )            i
                                                     2


             m2   2       i 1
                                                         .
                                             n




                                                             5
         The moments have a form similar to the variance. It is different in that the number of the
         moment is the power used for the difference in the variance. Therefore, the equation for
              th
         the k moment is

                      n

                     (X  x )  i
                                    k


              mk    i 1
                                        .
                            n

         AMOOF will use the above data statistic calculations in the more challenging calculations.
         The more complicated calculations are to find the best fit probability distribution using the
         likelihood functions for each of the 22 PDFs, and the mixed distributions, the conditional
         tale expectation, and the KS tests.

         The likelihood function is the product of functions which use the value of the data at each
         of the data points to determine the probability that it came from the given distribution. The
         likelihood function returns a number based on the PDF, the data point, and the parameters
         of the distribution function denoted as theta (Θ). Running an optimization on Θ to
         maximize the likelihood function will find the best fit of the current PDF. The moments of
         the data are used to guesstimate the initial value for the parameters. In turn, each of the
         maximized likelihood functions for the 22 PDFs will be calculated.

         When the best fit PDF has been determined, AMOOF will decide if a mixed distribution is
         required. The program will find the relative error between the first four positive and
         negative moments of the best fit distribution and the data set. AMOOF will also run a KS
         test and a Chi Square test to determine the accuracy of the PDF. The PDF is considered
         good enough if the relative error and the results of the tests are within the bounds set by
         the user. Default bounds will exist, but have yet to be determined. If the best fit PDF is not
         good enough, AMOOF will move on to find the best fit mixed distribution.

         Mixed distributions are distributions that use more than one PDF to describe a distribution.
         AMOOF will only consider weighted averages of two PDFs of the same class for mixed
         distributions. The technique for finding the best mixed distribution is much like the process
         for finding the best PDF, but there are twice as many parameters to optimize as well as
         the weights for each PDF. There are 22 available mixed distributions to consider.

         When the calculations are finished AMOOF will produce a report. The report will include
         the statistics of the data, the best fit distribution and its parameters. In addition, the report
         will include the conditional tail expectation (CTE) that gives statistics of the distribution one
         would get by only considering the data points a predetermined distance from the mean
         (the distance from the mean will be determined by the user).

Request Plots

         Three different plots will be available. The plots are histogram, best fit probability
         distribution, and a combination showing both the histogram with the best fit PDF. The
         histogram plot displays a plot of the data set. The best fit probability distribution displays a
         plot of the curve that is fitted to the data set. The combination plot displays both a
         histogram of the data and the best fit probability distribution. This will allow the user to see
         how close the distribution fits the data set.




                                                        6
Enter Data

         To enter data there are going to be three methods: data entry, cut and paste, and
         importation from a tab-delimitated file.

         Data entry is the simplest entry method. This is done with a standard spreadsheet that has
         two columns, one for values and one for the frequency of the values.

         Cut and paste options are going to be available to move data to and from the Windows
         clipboard. This function will work the same as cut and paste in most other programs.

         The program will read data from a file. Data within the file will be tab-delimitated, meaning
         it will have a tab between each of the data points.

Edit Options

         Many options will be available; however, we don’t have an exhaustive list of the options
         that will be available at this time. One option will allow the user to specify the x range of the
         graph. It will be possible to choose to search for only singular or mixed distributions. In
         addition the user will have the ability to change the parameters that determine if a
         distribution is good enough.




Save Workspace

         Save workspace will save the data, statistics, and best fit probability distribution to a file.

Open Workspace

         Open workspace will load data into the spreadsheet, initialize variables with the statistics,
         and load the selected best fit probability distribution.




                                                         7
 Nonfunctional Requirements

            Nonfunctional Requirements are those that affect the development of AMOOF but are not
            features provided in the program. The nonfunctional requirements of AMOOF are:

               Accuracy

               Data Sets

               Resource Constraints

               User interface

Accuracy

            AMOOF must be accurate and robust due to the importance of the decisions that could be
            made based on this program’s output. For example, if a company bases its rates on a
            distribution function and there was an error in the calculation of that distribution, there may
            be financial repercussions. Thus, accuracy is of utmost importance to AMOOF. To ensure
            accuracy, the development and testing of AMOOF must strictly follow the guidelines of our
            Quality Assurance plan.

Data Sets

            AMOOF should handle large data sets common in the actuarial field. A company may
            have more then a million data points to work with. While a random sample of data points
            will give a good approximation of the whole data set, the more points that can be included
            in the calculations the better the distribution function will approximate the data.

            The feasibility of working with a million data points has not yet been tested yet. Therefore,
            the minimum number of data points AMOOF will work with is ten thousand, and if
            resources allow this number will be raised to one hundred thousand.

Resource Constraints

            Resources for the development of AMOOF are in short supply. The deadline for delivery
            of the final project is in mid-March, approximately three months from the creation of this
            document. As students, the members of the development team for AMOOF have a limited
            amount of time to devote to the project each week. This creates a tight schedule under the
            best of conditions.

User Interface

            The target users of AMOOF are those in the Actuarial Science field who frequently use
            standard office applications. To make AMOOF accessible to its intended users it must
            mimic an office application whenever possible. To accomplish this goal the user interface
            will be developed in Visual Studio .NET and standard Windows™ functionality will be used
            for all features. Standard Windows functionality includes tool tips, a menu bar and
            toolbars, among others.



                                                          8
Feasibility

        The deadline to have AMOOF delivered by the end of winter quarter puts constraints on
        our development process. The need to have the program completed in three months
        means that a minimum version of the system must be designed and then expanded upon
        as time allows. This section details the minimum version of AMOOF that delivers only the
        essential features followed by the planned version of AMOOF the development team
        hopes to deliver. In addition, an ideal version of AMOOF with everything that has been
        suggested is detailed, though it is highly unlikely there will be time to develop it.

Minimum System

        This minimum version of AMOOF only provides the essential features for accomplishing
        the main goal of this program, to fit data to mixed distributions. The development team is
        confident it can produce this version of AMOOF at the very least. The features are:

             Data will be able to be imported from a tab delimitated file.

             Manual entry will be available via a spreadsheet.

             The maximum size of a data set will be ten thousand data points.

             A summary of the statistics of the data set will be available.

             Finding the best fit distribution:

                 The best fit PDF will be determined using the MLE and MME techniques.

                 The program will decide if a mixed distribution is required based on the CTE, KS
                  Test and the relative error of the moments of the best fit PDF compared to those
                  of the data.

                 The best fit mixed distribution of a weighted average of two PDFs of the same
                  class will be determined.

                 A report giving the statistics of the data as well as the parameters of the best fit
                  distribution and details on the goodness of fit.

             The report will be able to be copied for pasting into other applications.

             Data and all calculated statistics will be able to be saved to, and opened from, a file.

             Three graphs will be available:

                 A histogram of the data.

                 The best-fit distribution curve.

                 A combination of the histogram and distribution curve.




                                                        9
              Options will allow the user to:

                  Specify the x range of the graph.

                  Choose to look for only singular or mixed distributions.

                  Change the parameters that determine if a standard distribution is good enough.

              Program will run on Microsoft Windows 2000 and XP with Microsoft Excel and the
               .NET Framework installed.

              Help menu links to User Manual.

Planned System

         This is an upgrade from the minimum system version of AMOOF, including the
         nonessential features that are of the highest priority. The development team plans to
         deliver this version of the system. The additional features are:

              The ability to copy graphs.

              The ability to print the report, graphs and data sets.

              Maximum size of the data set will be fifty thousand.

              Ability to paste data from Excel.

              Program will run on Microsoft Windows 98 or later with Microsoft Excel and the .NET
               Framework installed.

              Help menu that links to an online searchable reference library including the User
               Manual.

Ideal System

         This is a further upgrade from the planned system version of AMOOF, including features
         that are considered unnecessary, but would be nice to have. Features from the ideal
         system are not expected to make it into the delivered system. The additional features are:

              Add trial capability with trial available online.

              The ability to find mixed distributions using a weighted average of three or more
               PDFs.

              More columns for multiple data sets.

              The ability to find mixed distributions by partitioning the data set.

              Find statistics for the segment of the distribution.

              Program will run on Microsoft Windows 95 or greater.



                                                           10
   Program will run on a System with 64mb of RAM or greater.

   Maximum size of the data set one hundred thousand.

   Option to show Chi Square output in the report.

   Ability to import from Excel files.




                                           11
Appendix A

   Glossary




              12
Actuarial Science
   The science of probability and statistics applied to insurance and company modeling; the science
   of evaluating the likelihood of future contingencies.

AMOOF
  Actuarial Model Outcome Optimal Fit; the program this document is written for.

Conditional Tail Expectation
   Distribution statistics based on the tail alone.

CTE
  Conditional tail expectation.

KS Test
   The Kolmogorov-Smirnov Tests if the data set is from that probability distribution.

Likelihood Function
   Determines the probability a data set came from a particular distribution.

Maximum Likelihood Estimate
  Technique for finding an optimal fit probability distribution for a data set.

Methods of Moment Estimate
   Technique to estimate parameters of a distribution, used in this project to determine initial values of
   parameters for optimization.

Mixed Distribution
   A distribution including more then one PDF, for the purposes of this project mixed distributions are
   weighted averages of two PDFs from the same class.

MLE
  Maximum likelihood estimate.

MME
  Methods of Moment Estimate.

Model
  Refers to a model of the data, or a distribution function.

.NET Framework
   Software required to run programs developed in Visual Studio .NET, a free update for Windows 98,
   2000 and XP.

PDF
   Probability density function.

Probability Density Function
   Describes continuous probability distributions.

Probability Distribution
   Gives the relative frequencies of all the possible outcomes of the random variable.

                                                           13
Appendix B

   Use-Cases




               14
VISIO USE CASE DIAGRAM GOES HERE.




                                15
   Use Case Name        Start Program

       Actor            Actuary

      Summary           The actuary requests to run the program.

   Pre-Conditions       Program is installed on the computer

Normal Flow of Events   1.   User clicks on program icon
                        2.   Program displays splash screen
                        3.   Program loads
  Error Conditions      1a. User does not have access to run program
                        3a. Not enough memory
Concurrent Activities   1.   Program displays splash screen
                        2.   Program loads
   Post-Conditions      Program is loaded and ready to be used

       Author           Daniel Hanson and Matthew Miller




                             16
   Use Case Name        Import Data

       Actor            Actuary

      Summary           The actuary imports the data by selecting the import option from
                        the file menu.
   Pre-Conditions       1.   User has data in a comma delimited file
                        2.   User knows location of the file
                        3.   Program is running
Normal Flow of Events   1.   User requests importation of data
                        2.   User browses to folder containing data file
                        3.   User selects data file
                        4.   Verify data file format
                        5.   Load data into spreadsheet
  Error Conditions      2a. Location is inaccessible
                        3a. Requested file does not exist
                        3b. Error reading file
                        4a. File format is incorrect
                        5a. Data set too large for program
                        5b. Individual numbers too large
Concurrent Activities   None

   Post-Conditions      Data is loaded into workspace

       Author           Daniel Hanson and Matthew Miller




                             17
   Use Case Name        Enter Data

       Actor            Actuary

      Summary           The actuary enters the data by entering data into spreadsheet.

   Pre-Conditions       1.   User has data
                        2.   Program is running
Normal Flow of Events   1.   Set focus to spreadsheet
                        2.   User enters or pastes data
  Error Conditions      1a. Spreadsheet not available
                        2a. User enters non-numeric data
                        2b. Data in clipboard is formatted incorrectly
Concurrent Activities   None

   Post-Conditions      Data is entered into workspace

       Author           Daniel Hanson and Matthew Miller




                             18
   Use Case Name        Open Workspace

       Actor            Actuary

      Summary           The actuary requests to open an existing workspace.

   Pre-Conditions       1.   Program is running
                        2.   A workspace file already exists
                        3.   User knows location of file
                        4.   Not Performing Calculations
Normal Flow of Events   1.   User requests to open an existing workspace
                        2.   User browses to location
                        3.   User selects file
                        4.   User initializes open
                        5.   Program reads in data
                        6.   Program initializes variables and sets up spreadsheet
  Error Conditions      2a. Location inaccessible
                        4a. File access errors
                        5a. File not correct file format
                        5b. Data corrupt
Concurrent Activities   None

   Post-Conditions      Data and statistics are loaded into the program

       Author           Daniel Hanson and Matthew Miller




                             19
   Use Case Name        Edit Options

       Actor            Actuary

      Summary           The actuary requests to edit program options

   Pre-Conditions       1.   Program is running

Normal Flow of Events   1.   User requests to edit options
                        2.   Program displays options menu
                        3.   User selects and changes option(s)
                        4.   Program sets option(s) as specified
  Error Conditions      3a. Conflicting options

Concurrent Activities   None

   Post-Conditions      Program option(s) set

       Author           Daniel Hanson and Matthew Miller




                             20
   Use Case Name        Get Data Statistics

       Actor            Actuary

      Summary           The actuary requests data statistics

   Pre-Conditions       1.   Data has been input
                        2.   Program is running
Normal Flow of Events   2.   User requests data statistics
                        3.   Program calculates statistics
                        4.   Program opens a new window
                        5.   Program displays statistics
  Error Conditions      2a. Probabilities don’t add up to 1
                        2b. Truncation error
Concurrent Activities   None

   Post-Conditions      1.   Statistics calculated
                        2.   Statistics displayed in new window
       Author           Daniel Hanson and Matthew Miller




                             21
   Use Case Name        Run Calculations

       Actor            Actuary

      Summary           The actuary selects start calculations from the file menu.

   Pre-Conditions       1.   Data has been input
                        2.   Program is running
Normal Flow of Events   1.   User indicates to run calculations
                        2.   Program validates data
                        3.   Program calculates statistics
                        4.   Program calculates a Maximum Likelihood Estimate
                             (MLE) for each of the 22 PDFs
                        5.   Program determines if mixed distributions are going to be
                             used
                        6.   Program finds MLE for mixed distributions if needed
                        7.   Program decides best PDF or mixed distribution
                        8.   Program displays distribution statistics
  Error Conditions      2a. Sum of probabilities does not equal one
                        3a. Truncation error
                        4a. Truncation error
                        4b. Numbers get too large
                        6a. Truncation error
                        6b. Numbers get too large
Concurrent Activities   None

   Post-Conditions      1.   A best fit PDF
                        2.   Distribution statistics
       Author           Daniel Hanson and Matthew Miller




                             22
   Use Case Name        Request Plots

       Actor            Actuary

      Summary           The actuary requests to see the histogram and/or best fit plot.

   Pre-Conditions       1.   Program is running
                        2.   Not Performing Calculations
Normal Flow of Events   1.   User requests a plot of the data
                        2.   Program prompts for plot type(s)
                        3.   User enters plot type(s)
                        4.   Program creates a new window
                        5.   Program displays histogram and/or plot
  Error Conditions      3a. No data in spreadsheet
                        3b. User selects unavailable plot type
Concurrent Activities   None

   Post-Conditions      A graphical display of the histogram and best fit plot

       Author           Daniel Hanson and Matthew Miller




                             23
   Use Case Name        Save Workspace As

       Actor            Actuary

      Summary           The actuary requests to save workspace as another file or file
                        type.
   Pre-Conditions       1.   Program is running
                        2.   Not Performing Calculations
Normal Flow of Events   1.   User requests Save As
                        2.   User browses to location
                        3.   User enters new filename
                        4.   User initializes save
                        5.   Program saves data, calculations, options and windows
                             locations to file
  Error Conditions      2a. Location is inaccessible
                        3a. User enters incorrect filename
                        4a. Filename in use
Concurrent Activities   None

   Post-Conditions      Workspace is saved to a file

       Author           Daniel Hanson and Matthew Miller




                             24
   Use Case Name        Save Workspace

       Actor            Actuary

      Summary           The actuary requests to save workspace to a file.

   Pre-Conditions       1.   Program is running
                        2.   Not Performing Calculations
Normal Flow of Events   1.   User requests Save
                        2.   If program not previously saved, calls Save Workspace As
                        3.   Program saves data, calculations, options and windows
                             locations to file
  Error Conditions      2a. Location is inaccessible

Concurrent Activities   None

   Post-Conditions      Workspace is saved to a file

       Author           Daniel Hanson and Matthew Miller




                             25
   Use Case Name        End Program

       Actor            Actuary

      Summary           The actuary requests to exit the program.

   Pre-Conditions       1.   Program is running

Normal Flow of Events   1.   User requests to exit program
                        2.   Program checks to see if the workspace has been saved
                        3.   Program prompts user to save if applicable
                        4.   Program calls Save Workspace if applicable
                        5.   Program closes
  Error Conditions      None

Concurrent Activities   None

   Post-Conditions      Program is closed

       Author           Daniel Hanson and Matthew Miller




                             26
Appendix C

   Data Flow Diagram of Calculations




                       27
DATA FLOW DIAGRAM GOES HERE




                              28

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:9
posted:8/25/2011
language:English
pages:30