@article {2026:jiot,
	title = {BPSmart-CARE: a framework for managing contextualized actions in IoT systems through the integration of business process modelling and complex event processing},
	journal = {Internet of Things},
	volume = {36},
	year = {2026},
	month = {March},
	chapter = {101887},
	abstract = {The exponential growth of Internet of Things (IoT) sensors and data has led to multiple software applications which aim at collecting, monitoring, controlling, and automating decisions based on such data in several domains such as smart cities. Even though early IoT frameworks and software architectures relied on correlating data from a single application domain, missing opportunities to improve contextualisation; in the last years several Complex Event Processing (CEP)-based frameworks and applications have been provided to improve the correlation of data from heterogenous domains, facilitating context-aware decision making. However, several issues remain unsolved: on the one hand, frameworks should not only provide the means for data correlation and contextualisation, but also for the definition of customisable real-time actions based on the context. On the other hand, CEP patterns update remains static in these frameworks, while there is a need for dynamically updating CEP pattern logic to adapt to changing contexts in real time. Even more, CEP patterns logic understanding might also be a handicap for developers. To face these challenges, in this paper, we enhance an existent CEP-based framework and software architecture by incorporating Business Process Modelling (BPM) to facilitate the definition of CEP patterns rationale, manage interdependencies between patterns, define and handle contextualised user actions, and enable real-time updating of CEP pattern logic based on detected situations. The proposed approach is illustrated through a case study, assessed via usability and performance evaluations, which show improvements in comprehensibility, maintainability, and updatability of CEP-based software applications for context-aware IoT scenarios.},
	keywords = {BPMN, Complex Event Processing, Internet of Things},
	doi = {10.1016/j.iot.2026.101887},
	author = {Adrian Bazan-Mu{\~n}oz and Cesare Pautasso and Guadalupe Ortiz and Alfonso Garcia- de-Prado}
}
@article {2026:ieeesw,
	title = {Facilitating the Adoption of Complex Event Processing for IoT: Framework and Lessons Learned},
	year = {2026},
	month = {March-April},
	abstract = {This paper introduces a novel framework designed to significantly facilitate the adoption by software developers and domain experts of the entire lifecycle of Complex Event Processing (CEP) for IoT domains. Recognizing the challenges non-technical users face, the framework integrates tools and processes that facilitate synthetic data generation for testing, intuitive definition, storage, and deployment of event types and patterns, and crucial runtime management. It also supports the storage and visualization of generated complex events. Its central component is SEC-API4CEP, a secure RESTful API enabling dynamic deployment, updating, and undeployment of event patterns at runtime, overcoming limitations of existing solutions, with integrated security. By addressing these critical aspects, the framework empowers software practitioners to leverage CEP for real-time analysis and response without requiring deep technical expertise while also allowing domain experts to graphically design IoT patterns to be detected by the CEP engine.},
	keywords = {API, Complex Event Processing, Internet of Things},
	doi = {10.1109/MS.2026.3664449},
	author = {Manuel Cano-Crespo and Guadalupe Ortiz and Cesare Pautasso and Alfonso Garcia- de-Prado}
}
@conference {2019:icpe:benchflow,
	title = {Behavior-driven Load Testing Using Contextual Knowledge {\textemdash} Approach and Experiences},
	booktitle = {10th ACM/SPEC International Conference on Performance Engineering (ICPE 2019)},
	year = {2019},
	month = {April},
	pages = {265-272},
	publisher = {ACM/SPEC},
	organization = {ACM/SPEC},
	address = {Mumbai, India},
	abstract = {Load testing is widely considered a meaningful technique for performance quality assurance. However, empirical studies reveal that in practice, load testing is not applied systematically, due to the sound expert knowledge required to specify, implement, and execute load tests. Our Behavior-driven Load Testing (BDLT) approach eases load test specification and execution for users with no or little expert knowledge. It allows a user to describe a load test in a template based on
natural language and to rely on an automated framework to execute the test. Utilizing the system{\textquoteright}s contextual knowledge such as workload-influencing events, the framework automatically determines the workload and test configuration. We investigated the applicability of our approach in an industrial case study, where we were able to express four load test concerns using BDLT and received positive feedback from our industrial partner. They understood the BDLT definitions well and proposed further applications, such as the usage for software quality acceptance criteria.},
	keywords = {BenchFlow, Performance Testing},
	doi = {10.1145/3297663.3309674},
	author = {Henning Schulz and Du{\v s}an Okanovi{\'c} and Andr{\'e} van Hoorn and Vincenzo Ferme and Cesare Pautasso}
}
@inbook {db:2009:mediation,
	title = {Mediation},
	booktitle = {Encyclopedia of Database Systems},
	year = {2009},
	pages = {1704-1706},
	publisher = {Springer},
	organization = {Springer},
	keywords = {software composition},
	doi = {10.1007/978-0-387-39940-9_1546},
	author = {Cesare Pautasso},
	editor = {Ling Liu and M. Tamer {\"O}zsu}
}
