Visualizing test diversity to support test optimisation

TL;DR

This paper explores how visualizing test diversity can aid testers in optimizing test suites by providing insights into redundancy and fault detection, based on a case study with industrial projects.

Contribution

It introduces a visual approach to represent test diversity, demonstrating its effectiveness in helping practitioners improve test repositories and optimize testing activities.

Findings

Test similarity maps reveal redundancy and fault detection potential.

Visual diversity data helps identify issues in test repositories.

Practitioners can make informed decisions for test suite improvement.

Abstract

Diversity has been used as an effective criteria to optimise test suites for cost-effective testing. Particularly, diversity-based (alternatively referred to as similarity-based) techniques have the benefit of being generic and applicable across different Systems Under Test (SUT), and have been used to automatically select or prioritise large sets of test cases. However, it is a challenge to feedback diversity information to developers and testers since results are typically many-dimensional. Furthermore, the generality of diversity-based approaches makes it harder to choose when and where to apply them. In this paper we address these challenges by investigating: i) what are the trade-off in using different sources of diversity (e.g., diversity of test requirements or test scripts) to optimise large test suites, and ii) how visualisation of test diversity data can assist testers for test optimisation and improvement. We perform a case study on three industrial projects and present quantitative results on the fault detection capabilities and redundancy levels of different sets of test cases. Our key result is that test similarity maps, based on pair-wise diversity calculations, helped industrial practitioners identify issues with their test repositories and decide on actions to improve. We conclude that the visualisation of diversity information can assist testers in their maintenance and optimisation activities.