agarbayo

Time tracking features are similar, I believe Wakatime might have a couple of reports more and git commits integration. For now, CoderMirror supports only Jetbrains IDEs while Wakatime has impressive support of IDEs and editors.

In CoderMirror data is stored locally in a SQLite database, so there is no limit to the data range you have access for free. Because of that, you can always write an ad-hoc query or export to the tool of your choice for further analysis when default reports don't match your needs (I'd be very interested in hearing what kind of reports developers need).

The focus of CoderMirror is on collecting data that can support a methodical continuous improvement effort. I try to create reports that give objective data for personal retrospectives to measure what works and what doesn't for you.

Along with time tracking collects data on what libraries you used and creates personalized quizzes with spaced repetition that attempt to deepen your understanding of the libraries you use.

This is in early stages and limited to Java projects and is the area where I want to focus in the future. Currently there is material for Java standard library, Spring framework, JUnit, etc.

Thank you for your feedback. I have updated the page to try to explain a little better what it does, eg that is a plugin that tracks your time and gives reports and training based on the collected data.

The first thing to keep in mind is that reasonable accuracy might never be achieved because of the nature of the problem. Social causes and bad process contribute to bad estimates. It’s not only the difficulty of guessing the unknown. Biases, guesses taken as deadlines and stakeholders trying to influence the estimation results contribute to worsening the problem.

This article https://www.infoq.com/articles/software-development-effort-e... written by a researcher at Simula Research Laboratory is one of the best summaries on the estate of software estimation.

Simula has excellent research on estimation. I found particularly interesting the different biases that might affect us: the scale used, how the question is asked (introduces an anchor to your estimate), the size of the task estimated previously, etc.

However, we can improve on gut feeling estimates and training on a personal level can reduce the uncertainty. A few highlights:

- On a team level, planning poker is known to improve estimates.

- Checklists (common forgotten activities) and historical data (% of time spent on unplanned or project management) tailored to your current project improve estimates.

- Avoid early estimation based on incomplete data. Avoid exposure to irrelevant, misleading estimation information.

- Break specs in tasks and estimate those tasks. Keep historical data on your estimates and final times and review them periodically. Automated time tracking tools for developers like https://www.codermirror.com/ can help in removing the burden of tracking coding times.