In the previous post (Looking at bug curves for previous projects and identifying patterns - Part 3), I talked about how the bug graph analysis from previous projects indicated that there were a large number of open defects soon after a point when the development team had completed the handover of all the features to the testing. This was essentially because a number of the big ticket features came near this date, and this was the first time that the testing team was able to test these. But this overload of defects was something that was causing a lot of pressure to the team, and it was unhealthy for the project. We had to resolve this, but we would never have even actually realized this problem if we had not mined the data from previous projects.
In this post, I will take another example of what we did using the mining of the data of looking at defects from previous cycles and then doing some analysis of that data. There can be many such cases, and I will take up some of these cases that were important to us in these posts, but you can extrapolate these to as many cases as you like and then gather the data and do the analysis.
One of the quests that we had for our team was to figure out how to decrease the time period that a defect was open with a developer - or more accurately, the time period in which a developer first looked at a defect. One of the biggest problems was that there would be defects which were not looked at by a developer for many weeks because of the load that the developers had, and when they got the time to look many of such defects, the tester did not accurately remember the conditions, or the software application had been changed many times since then because of all the developers checking in their changes, and it was not easy to resolve such defects. In short, the quest was that defect ageing be reduced from the many weeks that it was currently, and everybody agreed that we had to do something. However, before we proceeded to do something, we needed to know the extent of the problem, especially at different parts of the development cycle.
For this purpose, we again needed to refer to the defect database for data for previous versions, set up the query for this, and then get the data. To some extent, we also compared the data for multiple previous versions to see whether there were patterns in the data, and we did find some patterns. The analysis for how to reduce this, and what this involved in terms of changes in terms of defect management was something that took effort, but there were rewards for the same. But the most important part remained that we could only do all this analysis once we had the data for the previous cycles, and this was recognized as an important of risk management.
Read more about this in the next post (Risk Planning - Look at bug curves for previous projects and identify patterns - Part 5)