LTL in the Wild: A Decade of Specifying Edge/IoT System Behaviors
Internet of Things (IoT) and edge systems induce complex, heterogeneous, and distributed environments where interconnected physical devices and localized computing resources exhibit intricate behaviors. Specifying behavioral requirements in such systems is inherently challenging. Temporal logic, notably Linear Temporal Logic (LTL), is widely adopted for their formal specification, serving as a critical precursor to, e.g., verification or synthesis. This paper systematically investigates scientific literature spanning the past decade. We collect requirements and their corresponding LTL properties, analyzing trends in LTL specification within edge/IoT systems over time. Subsequently, we automatically extract defining features of these requirements and properties, including formula complexity and natural-language characteristics, and analyze their correlations. The insights we derive offer a valuable resource for researchers and practitioners engaged in reasoning within edge/IoT systems. Beyond serving as a reference corpus, the dataset can aid evaluation and validation of other approaches developed by the formal methods community, or serve as training data for machine learning techniques targeting the formalization process.