My Version Of Testing Rocket Science V4
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A selection of three of my utilities that have helped me make sense of I.T. Projects (and Programmes') from a testing perspective! DocIndex InternetMiner
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Editor's Notes
- The techniques presented here are available in many different guises! Obviously, there are numerous high-powered, corporate-level amalgamation and assimilation tools that do exactly what I’m achieving here (but they are rather expensive) but this is a glimpse into my own practical productivity tools that I use in my testing arena. My tools have evolved from years ago. They started as a simple (IBM) JCL Decompositer. The Decompositer grew from extracting simple JCL Job Decks, and mapping those internal/external file dependencies into two-dimensional tables to this suite of tools. DocIndex – extracts textual info from Word Documents into two-dimensional tables. It parses the Word object model into two tables to form a Table of Contents and text body repository of all paragraphs in a Word document. InternetMiner – does a similar job to DocIndex by extracting HTML data from URLs on the Internet, Intranet or Extranet into two-dimensional tables. It parses the Internet Explorer object model into two tables to form a table of contents and text body repository of all text data on the web page. It also maintains details of all Hyperlinks and scripts executed on each web page. VisioDecompositer – does a similar job to both DocIndex and InternetMiner by extracting (properly formed) Visio diagram information into a two-dimensional table. It parses the Visio object model into one table to form a two-dimensional view of boxes and lines on a page. The common theme outlined here is that decomposition takes place into two-dimensional tables. Common search words or phrases that are meaningful to a project, or programme or an organisation are quickly linked across one (or more) KeyDoc repositories. The natural and logical organisation of Word documents, Visio diagrams and internet/intranet web pages allows sentences and paragraphs of text data to be stored “in context” with one another – this facilitates a far more powerful search facility than can be achieved by conventional means. This presentation shows how