Combining Dynamic Analysis and Visualization to Explore the Distribution of Unit Test Suites

TL;DR

This paper presents a visualization approach combining dynamic and static analysis to explore unit test distribution in large OSS systems, aiming to improve understanding of test coverage and system dependencies.

Contribution

It introduces a method that maps dynamic coupling data onto static test information using visualization and graph analysis, revealing discrepancies in test distribution.

Findings

Unit tests do not align with dynamic coupling in studied systems.

Visualization helps identify central classes and test coverage gaps.

Graph metrics reveal test effort distribution relative to system dependencies.

Abstract

As software systems have grown in scale and complexity the test suites built alongside those systems have also become increasingly complex. Understanding key aspects of test suites, such as their coverage of production code, is important when maintaining or reengineering systems. This work investigates the distribution of unit tests in Open Source Software (OSS) systems through the visualization of data obtained from both dynamic and static analysis. Our long-term aim is to support developers in their understanding of test distribution and the relationship of tests to production code. We first obtain dynamic coupling information from five selected OSS systems and we then map the test and production code results. The mapping is shown in graphs that depict both the dependencies between classes and static test information. We analyze these graphs using Centrality metrics derived from graph theory and SNA. Our findings suggest that, for these five systems at least, unit test and dynamic coupling information 'do not match', in that unit tests do not appear to be distributed in line with the systems' dynamic coupling. We contend that, by mapping dynamic coupling data onto unit test information, and through the use of software metrics and visualization, we can locate central system classes and identify to which classes unit testing effort has (or has not) been dedicated.