This project has been migrated to WinUI 3 implementation.
A Light-weight Todo Manager with Time Estimation Tracking.
Time estimation is a key need for todo management. We help you to better estimate the completion time of todos via evidence-based scheduling (EBS).
Evidence Based Scheduling or EBS is a statistical algorithm that produces ship date probability distributions. It gathers evidence, mostly from historical timesheet data and provides accurate schedules. EBS produces a probability distribution curve, so that you know for any given date, the probability that your project will be completed.
In DayDayUp, each todo has three attributes related to EBS:
- real duration : record by DayDayUp, after users finish a todo.
- estimated duration: set by users when (after) a todo is created. It means that, this todo is supposed to take estimated duration mins to finish.
- predicted duration: calculate by DayDayUp as the results of the EBS. It is a set of values, representing the bias of estimated duration under different probabilities.
After one todo is created, users can set the estimated duration.
For each unfinished todo, DayDayUp adopts Monte Carlo Method to calculate predicted durations, based on the bias of real durations and estimated durations of finished todos.
- Git
- Visual Studio 2022, community edition works.
git clone https://github.com/Fangjin98/DayDayUp.git
Open src/DayDayUp.sln and hit F5 to compile and run.
| Status | Features | Memo |
|---|---|---|
| ✅ | Create Todos | Set estimated duration of todos |
| ✅ | Start & Pause Todos | Switch status of todos |
| ✅ | Per-todo Informations | Estimated duration, Prediction durations and Current duration |
| 🔁 | Multi-language Support | |
| 🔁 | Data Export | |
| 🔲 | Multi-device Synchronization | |
| 🔲 | Category | Todos can be assigned to different categories |
| 🔲 | Dashboard | Statistics summary |
| 🔲 | CLI Support |
✅ Supported | 🔁 In progress | 🔲 Not started