Exploring synergies between bottleneck analysis and performance antipatterns

The problem of interpreting the results of performance analysis is quite critical, mostly because the analysis results (i.e. mean values, variances, and probability distributions) are hard to transform into feedback for software engineers that allows to remove performance problems. Approaches aimed at identifying and removing the causes of poor performance in software systems commonly fall in two categories: (i) bottleneck analysis, aimed at identifying overloaded software components and/or hardware resources that a↵ect the whole system performance, and (ii) performance antipatterns, aimed at detecting and removing common design mistakes that notably induce performance degradation. In this paper, we look for possible synergies between these two categories of approaches in order to empower the performance investigation capabilities. In particular, we aim at showing that the approach combination allows to provide software engineers with broader sets of alternative solutions leading to better performance results. We have explored this research direction in the context of Layered Queueing Network models, and we have considered a case study in the e-commerce domain. After comparing the results achievable with each approach separately, we quantitatively show the benefits of merging bottleneck analysis and performance antipatterns.