1. requirements Validation

   1. early error detection - no bad things

   2. insure good quality - some good things

   3. error types - omission, incorrect facts, inconsistency, ambiguity

      1. percentages vary from project to project

      2. the classification itself is important to capture statistics

   4. requirement reviews

      1. stakeholder reviews - client, developers, lawyers, ...

      2. single group or multi-group reviews

      3. review formality

      4. review aids - check lists, questions, previous statistics

      5. reviews are effective at catching errors

   5. other review techniques

      1. automated cross referencing and general feature extraction

         1. checks small scale, internal details - terms defined before use

         2. applicable to structure-generating analysis techniques

         3. effective

      2. reading - the classic textual review

      3. scenarios - using the spec to answer questions about possible uses

      4. prototyping - use the spec to build a prototype

2. requirements metrics

   1. measure characteristics of the requirements process and document

      1. more accurately predict the current project

      2. improve the process model in general

   2. size metrics - a shakey relation between the size of the specification and the size of the project

      1. text measurements - paragraphs, pages

      2. function points

         1. oriented towards information systems

         2. five i-o types, each weighted by complexity

         3. unadjusted (raw) function points (ufp) - weighted sum of i-o types

         4. complexity adjustment factor (caf) measures environmental complexity

            1. 14 characteristics, each weighted by one of six levels, summed to get N

            2. caf = 0.65 + 0.01N

         5. delivered function points (dfp) = caf*ufp

         6. reasonably accurate estimator of project size and cost

            1. one dfp equals 100 lines of cobol or 80 lines of pl1

         7. active work to extend fp to other types of systems

      3. bang metric - dfd based, measures bits of data per transform

   3. quality metrics - how good is the specification

      1. srd error count

         1. compare with historical data to measure goodness

         2. determine latent errors

      2. change request frequency - both within and after the specification process

      3. quality attributes - highly suspect, but they're numbers

         1. ambiguity measurements, cross-product numbers

This page last modified on 15 March 2000.