Test them all, is it worth it? Assessing configuration sampling on the JHipster Web development stack

TL;DR

This paper explores the feasibility and benefits of exhaustively testing all configurations of the JHipster web development system, revealing significant failure rates and the effectiveness of sampling strategies within practical constraints.

Contribution

First comprehensive case study testing all configurations of an industry-strength configurable system, providing insights into fault detection and sampling strategy effectiveness.

Findings

35.70% configurations fail during testing

Sampling strategies outperform default configurations in fault detection

Exhaustive testing can be costly but yields valuable insights

Abstract

Many approaches for testing configurable software systems start from the same assumption: it is impossible to test all configurations. This motivated the definition of variability-aware abstractions and sampling techniques to cope with large configuration spaces. Yet, there is no theoretical barrier that prevents the exhaustive testing of all configurations by simply enumerating them, if the effort required to do so remains acceptable. Not only this: we believe there is lots to be learned by systematically and exhaustively testing a configurable system. In this case study, we report on the first ever endeavour to test all possible configurations of an industry-strength, open source configurable software system, JHipster, a popular code generator for web applications. We built a testing scaffold for the 26,000+ configurations of JHipster using a cluster of 80 machines during 4 nights for a total of 4,376 hours (182 days) CPU time. We find that 35.70% configurations fail and we identify the feature interactions that cause the errors. We show that sampling strategies (like dissimilarity and 2-wise): (1) are more effective to find faults than the 12 default configurations used in the JHipster continuous integration; (2) can be too costly and exceed the available testing budget. We cross this quantitative analysis with the qualitative assessment of JHipster's lead developers.