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SEng 5861: Software Architecture

SEng 5861: Software Architecture. Lecture 7 Dr. Michael Whalen Fall 2011. Topics for Today. Questions / Comments from Last Week Midterm review & expectations Information view Midterm. Updates. Grades posted for Project Phase II Nice job, folks! You obviously worked hard at them.

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SEng 5861: Software Architecture

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  1. SEng 5861: Software Architecture Lecture 7 Dr. Michael Whalen Fall 2011 SEng 5861 - Mike Whalen

  2. Topics for Today • Questions / Comments from Last Week • Midterm review & expectations • Information view • Midterm SEng 5861 - Mike Whalen

  3. Updates • Grades posted for Project Phase II • Nice job, folks! You obviously worked hard at them. • Schedule finally updated • For Phase III, I have a document template from R&W (in Word and .pdf) to use • It will be posted to the class web page today • Nothing radical; just outlines the sections of the document described in R&W Ch. 13. SEng 5861 - Mike Whalen

  4. Midterm Review • Your questions go here SEng 5861 - Mike Whalen

  5. Information viewpoint SEng 5861 - Mike Whalen

  6. Information Viewpoint • How do we organize (and manage) large volumes of data • Static views: Entity Relationship Diagram • You know these from SEng5702! • Lifecycle • Quality • Accuracy • Timeliness • Ownership SEng 5861 - Mike Whalen

  7. Information Flow Modeling • Where is data created and destroyed? • How do data items change as they flow through the system? • Concern can also be addressed (somewhat) using scenarios, but that is not their primary focus SEng 5861 - Mike Whalen

  8. Data Ownership • Is data item owned by exactly one process? • If multiple copies exist, • Is one the master? • Is data synchronized? • How often? • What are consequences of “stale” data? SEng 5861 - Mike Whalen

  9. Data Ownership Grids • Mapping data ownership to systems • Relationships: Owner, Creator, Updater, Deleter, Reader, Copy, Validator • Shows possible conflicts in data ownership Catalog and Purchasing both may modify product SEng 5861 - Mike Whalen

  10. Data Lifecycle and Retention • Data lifecycle: what is the process for creating, modifying, archiving, and deleting data • For many industries, lifecycle may be regulated • Financial transactions must be stored for NNN years • Patient-identifying data for a study must be disposed of within XXX days. • Archiving data • Cannot usually store data on disk indefinitely • Must be archived to more permanent storange • This may affect availability • Induces requirements on disk size SEng 5861 - Mike Whalen

  11. Information Lifecycle Models • Possible to represent as UML Statecharts or Entity Life Histories SEng 5861 - Mike Whalen Slide from: Eoin Woods, Viewpoints and Perspectives, SATURN 2008 (www.eoinwoods.info)

  12. Pitfalls • Data incompatibilities • Units, representation (e.g. endianness), text format (ASCII vs. Unicode) • Poor data quality • Assess risk! • How do we know data is bad? • Scenarios for ‘bad’ user input • What are fixup procedures? Manual? Automated? • Information degradation • Inadequate capacity • What is expected data load? • What are amounts of data that can be supported by OS, Database • Time to load, move, batch data SEng 5861 - Mike Whalen

  13. What Have We Learned? • A bit about the information viewpoint • Data quality, lifecycle issues • Security, regulation, and data retention SEng 5861 - Mike Whalen

  14. MIDterm SEng 5861 - Mike Whalen

  15. Clarifications • Question 3: • Do one or two scenarios; don’t kill yourself • These are things that the site should do; they may or may not do it already • Things that the site already does are o.k. to use • Question 5: context diagram. • “hypothetical” means that you take the internal subsystems from question 4 and come up with a handful of external things that would communicate with them. • All of the internal subsystems go in a “rover” system in the middle of the diagram SEng 5861 - Mike Whalen

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