This function will help you parse a set of stories into a dataframe, where one row is each user story; The user story gets splitted into who, what and why sections, according to the use of keywords. The file must be a text file written in English, with one user story per row.
readStories(url)
| url | The URL of the text file to be parsed. Every user story must be
in a single line, and written in English. Punctuation is irrelevant as
it is processed out.
For this to work, user stories should follow the who, what, why
template, with keywords: |
|---|
A dataframe of three colums, representing sections who, what, why of the user stories. There is one row per user story, and they may not have the "why" part if it wasn't added. Using incorrect keywords means incorrect parsing, so be careful.
# Analyse without reports dataPath <- example_stories() stories <- readStories(dataPath) # Print some information head(dplyr::as_tibble(stories))#> # A tibble: 6 x 4 #> storyId who what why #> <int> <fct> <chr> <chr> #> 1 1 manag~ read working hours per employee from~ we are working with curr~ #> 2 2 manag~ use the current job assignments from~ we use the most recent d~ #> 3 3 manag~ read employee salaries from our hr d~ we use uptodate values #> 4 4 manag~ put the storage cost in the calculat~ we always have the most ~ #> 5 5 manag~ define the operating costs from the ~ all of them are linked t~ #> 6 6 manag~ limit the personnel assigned to stoc~ i can reduce the number ~