No abstract

Growing data volumes and velocities in fields such as Industry 4.0 or the Internet of Things have led to the increased popularity of data stream processing systems. Enterprises can leverage these developments by enriching their core business data and analyses with up-to-date streaming data. Comparing streaming architectures for these complex use cases is challenging, as existing benchmarks do not cover them. ESPBench is a new enterprise stream processing benchmark that fills this gap. We present its architecture, the benchmarking process, and the query workload. We employ ESPBench on three state-of-the-art stream processing systems, Apache Spark, Apache Flink, and Hazelcast Jet, using provided query implementations developed with Apache Beam. Our results highlight the need for the provided ESPBench toolkit that supports benchmark execution, as it enables query result validation and objective latency measures. CCS CONCEPTS• Software and its engineering → Software performance; • Information systems → Stream management; Database performance evaluation; • Applied computing → Enterprise data management.

Teaching agile software development by pairing lectures with hands-on projects has become the norm. This approach poses the problem of grading and evaluating practical project work as well as process conformance during development. Yet, few best practices exist for measuring the success of students in implementing agile practices. Most university courses rely on observations during the course or final oral exams. In this paper, we propose a set of metrics which give insights into the adherence to agile practices in teams. The metrics identify instances in development data, e.g. commits or user stories, where agile processes were not followed. The identified violations can serve as starting points for further investigation and team discussions. With contextual knowledge of the violation, the executed process or the metric itself can be refined. The metrics reflect our experiences with running a software engineering course over the last five years. They measure aspects which students frequently have issues with and that diminish process adoption and student engagement. We present the proposed metrics, which were tested in the latest course installment, alongside tutoring, lectures, and oral exams.