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This is the monthly checkpoint for summarising work that have been accomplished recently. Please feel free to comment.


[edit] Timesheet

11/07/2011	Point Squoring Toulouse + Update wiki
12/07/2011	Update Wiki Glossary + Standards
13/07/2011	Update Wiki Glossary + Standards
15/07/2011	Point Data Mining Philippe
18/07/2011	Update Wiki Glossary + Standards
19/07/2011	Point Squoring + Update Wiki Glossary + Standards
20/07/2011	Update Wiki Glossary + Standards
21/07/2011	Update Wiki Glossary + Standards
22/07/2011	Update Wiki Glossary + Standards

[edit] What has been done this month

[edit] Public wiki

The glossary and standards categories have been greatly improved. The wiki now has:

  • 275 words for the glossary,
  • 92 standard definitions,
  • 10 metrics, and
  • 11 papers.

The glossary spans across several standards and is now quite complete. Some work still needs to be done to:

  • Complete some missing words / missing definitions.
  • Cross-link words between articles.
  • Review the whole glossary and ensure consistency.

2 articles have been added to the wiki (in the Project category) about what is Maisqual and how people can participate in it.

We should hit the September target for the public wiki, at least for the glossary and standards categories.

[edit] Thoughts

Some articles have been added to the private wiki:

  • Data Mining Treatments has been created, following a discussion held with Philippe about what we need to apply data mining techniques on our subject.
  • Roadmap is a draft of the overall thesis planning.

Other articles have been improved with more new elements:

  • Data To Mine that lists the means we have for data mining on software repositories.
  • Use Cases that try to define what we want from the end-user point of view.
  • Characteristics of Quality, (was Attribute of Quality) about what we call quality and what is good or bad software.

[edit] Next steps

The following steps are planned for the next weeks/months:

  • Finalise the glossary and standards wiki categories.
  • Read more research articles about metrics.
  • Add metrics to the wiki.
  • Try to find example data for the mining algorithms (see Data Mining Treatments)..
  • Take Philippe's courses on Data Mining.
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