# Timeline:2011.06

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

#  Timesheet

```01/06/2011    Doc Introduction to Maisqual + Readings + Update wiki
03/06/2011    Readings + Summary of this month's work
07/06/2011    Readings + R & data manipulations
08/06/2011    Readings + R & data manipulations
13/06/2011    Update Wiki: Glossary
14/06/2011    Update Wiki: Glossary + Standards
15/06/2011    Update Wiki: Glossary + Standards
16/06/2011    Update Wiki: Glossary + Standards
23/06/2011    Update wiki readings + summary of this month
24/06/2011    Presenting Maisqual document + Update wiki
```

#  What has been done this month

The work for this month has been targeted at the following objectives:

• Start to fill the maisqual:Category:Glossary and maisqual:Category:Standards parts of the wiki. The glossary has been started, with definitions from as many standards as were available. Many standards have been added, with some basic information about them.
• Continue with readings, with a focus on metrics. 5 papers have been added, other are on the way.
• Following a discussion with Philippe, try to improve hyper-linking in the wiki, to make it really interactive and browsable. That means hyper-linking terms, metrics, standards to their own page, cross-linking papers and definitions.. This is a time-consuming work, but really adds value to the work.

The readings have been targeted at metrics rather than data-mining for this month. The papers read and added to the wiki are the following:

Many other papers and articles have been found about metrics and software measurement.

#  Thoughts

The readings above show that metrics have to be carefully thought before being applied. A strong mathematical basis may improve the confidence we have in them.

The better answer, from the knowledge we have now, is the multidimensional analysis:

• First define what we want to measure: efficiency of teams, of code, complexity for what purpose, etc.
• Define metrics based on multiple criteria

This is the main point of Squore: considering multiple metrics to measure something, instead of just relying meaninglessly on a single measure.

##  About the process of improvement

The basic process of measurement would look like:

1. Measure quality of process and products, considering code metrics, complexity, project history, etc. As an example, one of the measures we could use is the quality evolution patterns shown in maisqual:Monitoring Software Quality Evolution for Defects.
2. Ask for directions for improvement (reliability, efficiency, costs, etc.). => Define what are directions for improvement.
3. Compute shortest path to next step in that direction.
4. Measure improvement and goal completion.
5. Get back to 1.

Which means, for the intermediate goals:

• Find the most relevant metrics for quality (whatever we call quality).
• Find correlations between practices and quality (because we will propose practices, I guess).
• Weight them, and find a way to better use *this* practice for *this* quality (again, for whatever we may call quality). => Decision.

##  Data Mining and Metrics

Another question is: how can we apply data mining algorithms on software engineering data for our purpose?

Directions that can be foreseen from there are:

• For the multidimensional analysis:
• Can we automatically find the best base measures to be used for the multidimensional analysis?
• Can we compute a "best compromise" between these criteria/measures to measure something at a higher level?
• Once we have correctly measured the state of quality, how it correlates to practices (which are attributes of the code/process)?
• Once we have correctly correlated practices and quality, what is the shortest path to the next step of quality wanted?

#  Next Steps

In the next weeks/months, the following items will be investigated/worked on:

• Continue improving the glossary and standards. A first publishable version should show up in September.
• Continue readings on metrics and measurement.
• Continue improving readability/interactivity through linking (both from and outside the wiki).

The directions for the next papers are:

• Read standards, write them to standards/glossary/metrics.
• Find papers relevant for the multidimensional analysis.