Test them all, is it worth it? A ground truth comparison of configuration sampling strategies

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 industrystrength, 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; A. Halin, A. Nuttinck, G. Perrouin (FNRS research associate) PReCISE, NaDI, Faculty of Computer Science University of Namur, Belgium E-mail: [email protected] M. Acher IRISA, University of Rennes I, France E-mail: [email protected] X. Devroey SERG, Delft University of Technology, The Netherlands E-mail: [email protected] B. Baudry KTH Royal Institute of Technology, Sweden E-mail: [email protected] (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.