Making a model understanding and developing a new software project is challenging. Much of the difficulty is from the size of the projects - they are too large to be fed into a model as a whole. Therefore, the model must retrieve key information when it is needed. Because the problem is too complex, we do not have such a dataset so far. However, because we are aiming at solving the problem, we want to make one first. We will give about 10 Python modules written in DocInPy. Each of them will have a few developing tasks to be finished.
Plan
Check whether there are similar datasets.
Decide the topics of the Python modules.
Decide the size of the Python modules.
Decide the tasks of the modules.
Make an experimental module.
Implement other modules as planned.
Using available methods to solve the problems in the dataset.
Make a new method to solve the problems.
Requirement of the module
The modules should be large enough so that they cannot be fed into the model as a whole.
The modules should contain developing todos of many types, including module using, bug fixing, feature development, and chores (maybe).
Motivation
Making a model understanding and developing a new software project is challenging. Much of the difficulty is from the size of the projects - they are too large to be fed into a model as a whole. Therefore, the model must retrieve key information when it is needed. Because the problem is too complex, we do not have such a dataset so far. However, because we are aiming at solving the problem, we want to make one first. We will give about 10 Python modules written in DocInPy. Each of them will have a few developing tasks to be finished.
Plan
Requirement of the module