Project Visualizations

A few development chronicles have been compiled in a suit for data visualization. Several scattered pieces of information were brought around and relations were performed in order to make up the stage.

Contents for “project” have been split into five subsections:

Results from the survey conducted between January to February 2019:

HeavenMS Field Survey Results

Everyone’s here! (Sorta…) Following is an acknowledgment list of the people who have been making presence during HeavenMS development.

Patrons

The visual flow of updates within the world can be followed in:

WorldMap movements

Technologies used in this case study:

Employed technologies

Files and Directories

Overview of the relation of most covered files and directories during HeavenMS development.

Archive 1: count of most edited files by commits.

Commits

Visualization of edition movements (per commit basis) during HeavenMS development.

Archive 1: number of additions and changes over each commit performed in development.

File line growth #1 (Java)

File line growth #2 (Java)

File line growth #3 (Java)

File line growth #1 (Js)

File line growth #2 (Js)

File line growth #3 (Js)

File line growth #1 (XML)

File line growth #2 (XML)

File line growth #3 (XML)

File line growth #1 (Others)

File line growth #2 (Others)

File line growth #3 (Others)

File line growth #1 (ALL)

File line growth #2 (ALL)

File line growth #3 (ALL)

Archive 2: aggregation in size difference from files between commits.

File size difference #1 (Java)

File size difference #2 (Java)

File size difference #1 (Js)

File size difference #2 (Js)

File size difference #3 (Js)

File size difference #1 (XML)

File size difference #2 (XML)

File size difference #3 (XML)

File size difference #1 (Others)

File size difference #2 (Others)

File size difference #3 (Others)

File size difference #1 (ALL)

File size difference #2 (ALL)

File size difference #3 (ALL)

Traffic

Visualization of view activities during HeavenMS development.

Notes:

Counters are reset every two weeks: the value seen on a given date is about activities performed over the last two weeks from that date.
“Commit dates” follow the timestamp on which code got updated on the repository. Counts from a given commit take the most active the repository had been on two-week basis.

Unique clones #1

Unique clones #2

Unique clones #3

Unique clones #4

Archive 1: Repository Clones from unique users.

Popular referrers

Popular paths

Archive 2: Most popular referrers and directories within the repository.

HeavenMS Field Survey Results

In 2019, HeavenMS conducted a MapleStory fanbase questionnaire. This survey shows up results accounting for 83 responses, from 76 respondents, having been opened from 11th January to 8th February (28 days).

The presented results, having warranted over three-quarters of a hundred players, is hoped to show a glimpse over the preferences shown from the player base.

Average age of respondent players (2019)

Respondents started playing MapleStory from…

Creator

Visualization contrasting activities realized while maintaining HeavenMS development.

Lines edited (Java)

Lines edited (Js)

Lines edited (XML)

Lines edited (Others)

Lines edited (ALL)

Archive 1: Measure of the number of lines changed in development.

Commits & issue movements

Average open time of issues

Archive 2: Measure of commits and issues over development time.

Employed Technologies

This study, conducted in Python, counts with several layers of external packages and interfaces. In summary:

ANTLR: syntax tree recognizer & parser, helps to uncover patron patterns in the source code.
Github API: repository information provider.
Google Translator: widely recognized JIT translator, for many languages.
Matplotlib: graphic package, generates the visual representation of many of the presented plots.
NLTK: Natural Language Toolkit, helps with stemming detected words and providing stopwords for the plotting library.
Pandas: data analysis tool, formats up data in a DataFrame to be inserted on the several plotting operations.
Pickle: Python data serializer, encodes and decodes the varied Python structures and object instances into file-friendly contents.
Seaborn: multi-purposeful plotting library.
Squarify: plotting library for area visualization of frequencies.
Wordcloud: plotting library for word visualization of frequencies.

Patrons

This software development would not have reached nearly as far as it had if not for the feedback and attention of each one that had picked their interest to watch the development, undoubtedly.

For being a programmer, and also the director of this communal software performance, it should be and feels like a duty and, above all, an honor, to try to represent the watchers’ feedbacks visually, and greet each one for the upstanding initiatives.

Without further ado, the feedbacks and patrons’ overview visualization:

patron_words

Archive 1: Symbolic overview of contents presented in messages during development.

Patrons (up to 15)

Patrons (up to 30)

Patrons (up to 45)

Patrons (up to 60)

Patrons (up to 75)

Patrons (up to 90)

Patrons (up to 105)

Archive 2: Patrons recognition. Shoutout for the folks who have been taking part along the way, making this development something worth the journey! It’s an honor to have been developing this source over such panorama.

Miscellaneous

Aggregation of several self-rounded visualizations (mainly ad-hoc contents).

Accepted PRs
File count
File size
Release growth
Repository growth
Keywords
Log keywords

Timely activities

Inter-releases activities

Archive 1: measures of public activities during development.

Quantity of files maintained within repository

Aggregated size (in bytes) of files maintained within repository

Relation of pull request activities

Archive 2: measures of performed development activities.

Ptbr-log keywords

Github chat keywords

Archive 3: In-Github keyword visualization.

WorldMap movements

During HeavenMS development, many aspects of the server source have been revised, some of those reflecting more directly to areas of the game and its internal objects (portals, mobs, reactors, etc).

Taking that into account, this section of the case study tries to paint traces of the movement that have been happening in the background, picturing those into a heatmap visualization.

The following plots are interactive, click a region to view flows inside that area.