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Wednesday, May 8, 2013

Risk planning - Look at bug curves for previous projects and identify patterns - Part 2

In the previous post (Looking at bug curves for identifying patterns - Part 1), I talked about how the defect curves for the previous versions of the software product should be reviewed to look for patterns that will help in predicting defect patters in the current release. As an example, if there was a phase in previous cycles where the pressure caused a greater number of defects to be either partially or completely rejected, then this was worrisome. Such a problem area is something that should be focused on to ensure that these kind of issues are reduced or removed totally altogether, and the benefits can be considerable.
In this post, I will continue on this subject area. One of the biggest problems that teams face is that they are so worked up in terms of what is happening in the current release that they use previous versions for help in estimation, and do not really use defect management and analysis to the level they should. One of the critical focus items in terms of project management and risk planning is about understanding that one looks not only at the current version of the software development cycle, but also at future versions. There is a lot of learning to be had from current releases and one should ensure that we are able to gain from this learning in the next release.
The Defect database should be set in such a manner that while it provides you the functionality to do your defect management for the current release, there should be the ability to store this information. If for example, your defect database is not able to store the data that defects have been rejected, or capture the fact that defects did multiple rounds back and forth between the developer and tester, you are losing out on data that is pretty important. We actually ran into such a situation, where we wanted to determine which defects are going back and forth between the developers and testers, or even between multiple people on the team. This was a way to figure out which defects are taking more time, and it seemed like a good place to start. The concept was that if we could figure out these from the previous cycle, and were able to get a figure on which sets of people do not work well together (too much back and forth between people over a defect is certainly not useful, you would expect people to collaborate and resolve issues rather than doing discussion in a defect).
However, things did not work as well as we expected. The defect management system did not have such a query or something even similar to it. It was possible to get this information once we got access to the tables in the database, but this is not something that is easy or quick to do. We needed to get hold of people who had some expertise in how the database was structured, and also needed access to people who knew how to manipulate the database and get us the report that we wanted. It took a fair amount of time, and in the end, we got what we wanted. The results were interesting. They showed that there was a person in the team who wanted every bit of information to be in the database, even something that was clear could be asked and did not add any value to the defect information. But, the defect was passed back to the other person, and then it would depend on the time and defect load of the other person. However, since the person did not have the defect on himself, normal statistics would not show any problem.
We took some action on this one in terms of some counseling for the person from the manager, in a non-threatening way, and resulted in improvement in terms of defect handling. However, it was difficult to quantify the time saved, but we were satisfied in terms of the results we could see, and felt that there was improvements we made in the defect management, and would help in terms of reducing the load due to defects.

Read more about this effort in the next post (Look at bug curves for previous projects and identify patterns - Part 3)

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