By Jonathan Alexander
How will you aid your software program workforce increase? This concise publication introduces codermetrics, a transparent and aim approach to establish, study, and talk about the successes and screw ups of software program engineers-not as a part of a functionality overview, yet to be able to make the group a extra cohesive and efficient unit. skilled staff builder Jonathan Alexander explains how codermetrics is helping groups comprehend precisely what happened in the course of a venture, and permits each one coder to target particular advancements. Alexander provides a number of easy and complicated codermetrics, and teaches you ways to create your individual.
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Extra info for Codermetrics: Analytics for Improving Software Teams
My experience is that if you explain the usefulness and purpose of the data to the system owners or administrators, along with the fact that you don’t need any security-sensitive data, you should get cooperation. Sometimes you can pull the data directly from the systems, or you may get it indirectly through regularly generated reports or other documents such as departmental or financial summaries. In most cases, weekly or monthly collection of the target data will be sufficient, and most modern systems have the capability to schedule reports and exports.
Below are a few examples and my reasoning in regards to some of these excluded data types: KLOCs It seems reasonable to think that lines of code (KLOC stands for 1,000 lines of code) could be useful as a way to measure coder productivity, and by many accounts KLOCs have proven useful in estimation techniques and tools designed to reduce project estimation errors, especially on larger projects. But in general, I believe KLOCs are indicative of activity more than identifiable accomplishment, and I think it is hard to relate this metric to specific team goals, such as customer adoption or satisfaction or product quality.
These assigned team members need to have enough visibility to track the chosen items, such as a team leader, a project manager, or a scrum master. They can fill in stat sheets at your desired granularity, for example weekly by coder and by team. Then this data gets combined with the system-extracted data that contributes to your overall codermetrics data set. For smaller teams, having one assigned spotter should be fine. For larger teams, having multiple spotters might increase accuracy, the same as in pro sports.
Codermetrics: Analytics for Improving Software Teams by Jonathan Alexander