- After discussing with Kenji Hiranabe about trying [Word frequency in source code
- I calculated the frequency by including all calls, not just the definitions, but some said I should limit it to just the definitions, which do you think is better?
- It seems like a good idea to analyze not only the function and class definitions, but also the calls
- It’s the ones that appear more frequently, including the calls, that are the most important concepts.
- I’ve divided the addItem-like methods into add and item and tabulated them, what do you think?
- Separated items are closer to “Domain Words”.
- What do you think? I think we should analyze everything together, not only classes and methods, but also comments and CSS.
- should do so
- Analyze everything people see and everything that describes the program
- supplement
- It is a process of “retrieval” and “meaning making.”
- Extract “strings that seem to correspond to important concepts” and verbalize their meanings.
- What is depicted here is a diagram of the relationships between concepts, an “ontology diagram” if you will.
- The goal is not to draw a diagram, but to arrive at the current situation, a little divergent.
- It is a process of “retrieval” and “meaning making.”
- consideration
- Age of aggregation by dividing method names into words, data on which method the word came from is available for correspondence.
- The item is listed in the ranking, and from there the link is “List of identifiers that use this word: addItem, removeItem”.
- And while we’re at it, it would be nice if we could jump to the code from that list of identifiers.
- Could this be accomplished as a vscode extension?
- I feel that a “dictionary” describing the meaning of words should be easily looked up while writing a program.
- Manage with source code?
- For example, you could write it in a fixed format in the root directory of the project.
- Age of aggregation by dividing method names into words, data on which method the word came from is available for correspondence.
relevance - Dictionary creation assistance
This page is auto-translated from /nishio/オントロジー図 using DeepL. If you looks something interesting but the auto-translated English is not good enough to understand it, feel free to let me know at @nishio_en. I’m very happy to spread my thought to non-Japanese readers.