Feature Release Visualization

Uncovering Release Patterns Through Interactive Visualization

An innovative approach to visualizing software feature releases with embedded treemaps and calendar views

Design Evolution

Our design evolution from version 1 to version 4

Version 1

Calendar with Bubble Sort

Initial design showing feature releases as bubbles on a calendar layout.

  • Bubble size shows number of features released
  • Color-coded bubbles for different applications
  • Basic temporal visualization
View Version 1

Version 2

Calendar with Heat Intensity

Enhanced calendar view with heat mapping to show release intensity.

  • Color intensity indicates feature density
  • Multi-application comparison
  • Monthly and yearly views
View Version 2

Version 3

Calendar Plus Treemap

Combined approach with calendar for temporal data and treemap for categories.

  • Integration of temporal and categorical data
  • Hierarchical view of feature categories
  • Improved data exploration capabilities
View Version 3

Problem Statement & Motivation

Understanding the need for a better feature release visualization

The Challenge

Tracking the release and categorization of software features over time presents unique visualization challenges:

  • Difficulty in tracking temporal release patterns
  • Understanding categorical distribution of features
  • Identifying release intensity across time periods
  • Comparing release patterns across software products
Z

Zoom

571

Features

Jan 2022 - Jan 2024
F

Firefox

171

Features

Jan 2022 - Jan 2024
W

Webex

258

Features

Jan 2022 - Dec 2023

Visualization Design & Implementation

Technical approach and key components

Technical Implementation

Frontend Architecture

Built with JavaScript, HTML5, and CSS3, using XLSX.js for data processing and Lodash for utility functions.

Data Handling

Data loaded from Excel with fallback to sample data generation, processed to extract temporal and categorical patterns.

Visualization Components

  • Quarterly Calendar View
  • Embedded Treemap Visualization
  • Interactive Day Details Panel
  • Customizable color schemes

Target Users

  • Product Managers: For release planning
  • Software Engineers: To monitor feature evolution
  • Data Analysts: For trend analysis

Research Foundations

Built on established visualization techniques and academic research

1

Van Wijk & Van Selow (1999)

"Cluster and Calendar-Based Visualization of Time Series Data" IEEE InfoVis

Demonstrates the effectiveness of calendar layouts for exposing temporal patterns

→ Inspired our calendar-based layout

2

Wu et al. (2010)

"OpinionSeer: Interactive Visualization of Hotel Customer Feedback" IEEE TVCG

Demonstrates integration of temporal and categorical data in interactive visualization

→ Guided our approach to combining multiple data dimensions

3

de Carvalho et al. (2016)

"Temporal Data Visualization Technique Based on Treemap" IV

Validates combining treemap visualizations with a temporal hierarchy

→ Foundation for our embedded treemap approach

4

Bederson et al. (2004)

"DateLens: A Fisheye Calendar Interface for PDAs" ACM TOCHI

Highlights the usability and effectiveness of calendar-based interfaces

→ Informed our calendar design principles

5

Chen et al. (2017)

"Ordered Small Multiple Treemaps for Visualizing Time-Varying Hierarchical Data" The Visual Computer

Supports consistent category layout over time for comparison across periods

→ Guided our implementation of consistent treemap layouts

Team Organization & Contributions

Meet the people behind the visualization

Data Analysis

KG

Karthika Gogineni

Pattern identification, data exploration

MV

Maruthi Vadlamudi

Feature categorization, temporal analysis

Research Foundations

KD

Kundan Karthik Drona

Visualization research, literature review

MR

Maria Rampangu

Academic foundations, research integration

Visualization Design

PB

Pallavi Bagam

Core visualization concept, visual language

JP

Jaya Pavani Pathakota

UI design, information hierarchy

RP

Rohan Pothuru

Integration oversight, design direction

Development Team

KA

Karthik Amruthaluri

Prototype development, system architecture

KB

Kaushik Bhamidipati

Rendering engine, data pipeline

SL

Sahiti Lavu

Interactive elements, user experience

Analytics Team

SJ

Sai Bhargav Jonnalagadda

Pattern recognition algorithms, data mining

RS

Raghu Deepak Sorana

Statistical component design, trend analysis

IY

Indrani Yella

Summary visualizations, contextual statistics