Developers of thread-safe classes struggle with two opposing goals. The class must be correct, which requires synchronizing concurrent accesses, and the class should provide reasonable performance, which is difficult to realize in the presence of unnecessary synchronization. Validating the performance of a thread-safe class is challenging because it requires diverse workloads that use the class, because existing performance analysis techniques focus on individual bottleneck methods, and because reliably measuring the performance of concurrent executions is difficult. This paper presents SpeedGun, an automatic performance regression testing technique for thread-safe classes. The key idea is to generate multi-threaded performance tests and to compare two versions of a class with each other. The analysis notifies developers when changing a thread-safe class significantly influences the performance of clients of this class. An evaluation with 113 pairs of classes from popular Java projects shows that the analysis effectively identifies 13 performance differences, including performance regressions that the respective developers were not aware of.

Many studies in research deal with optimizing emergency medical services (EMS) on both the operational and the strategic level. It is the purpose of this method-oriented article to explain the major features of “rule-based discrete event simulation” (rule-based DES), which we developed independently in Germany and Switzerland. Our rule-based DES addresses questions concerning the location and relocation of ambulances, dispatching and routing policies, and EMS interplay with other players in prehospital care. We highlight three typical use cases from a practitioner’s perspective and go into different countries’ peculiarities. We show how research results are applied to EMS and healthcare organizations to simulate and optimize specific regions in Germany and Switzerland with their strong federal structures. The rule-based DES serves as basis for decision support to improve regional emergency services’ efficiency without increasing cost. Finally, all simulation-based methods suggest normative solutions and optimize EMS’ performance within given healthcare system structures. We argue that interactions between EMS, emergency departments, and public healthcare agencies are crucial to further improving effectiveness, efficiency, and quality.