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We present AIOCJ, a framework for programming distributed adaptive applications. Applications are programmed using AIOC, a choreographic language suited for expressing patterns of interaction from a global point of view. AIOC allows the programmer to specify which parts of the application can be adapted. Adaptation takes place at runtime by means of rules, which can change during the execution to tackle possibly unforeseen adaptation needs. AIOCJ relies on a solid theory that ensures applications to be deadlock-free by construction also after adaptation. We describe the architecture of AIOCJ, the design of the AIOC language, and an empirical validation of the framework.
Programming distributed applications free from communication deadlocks and races is complex. Preserving these properties when applications are updated at runtime is even harder. We present DIOC, a language for programming distributed applications tha
Programming systems incorporating aspects of functional programming, e.g., higher-order functions, are becoming increasingly popular for large-scale distributed programming. New frameworks such as Apache Spark leverage functional techniques to provid
Adaptive model predictive control (MPC) robustly ensures safety while reducing uncertainty during operation. In this paper, a distributed version is proposed to deal with network systems featuring multiple agents and limited communication. To solve t
Motion planning is an extremely well-studied problem in the robotics community, yet existing work largely falls into one of two categories: computationally efficient but with few if any safety guarantees, or able to give stronger guarantees but at hi
Blockchains host smart contracts for crowdfunding, tokens, and many other purposes. Vulnerabilities in contracts are often discovered, leading to the loss of large quantities of money. Psamathe is a new language we are designing around a new flow abs