Abstract-Self-explanation is one cognitive strategy through which developers comprehend error notifications. Selfexplanation, when left solely to developers, can result in a significant loss of productivity because humans are imperfect and bounded in their cognitive abilities. We argue that modern IDEs offer limited visual affordances for aiding developers with self-explanation, because compilers do not reveal their reasoning about the causes of errors to the developer.The contribution of our paper is a foundational set of visual annotations that aid developers in better comprehending error messages when compilers expose their internal reasoning. We demonstrate through a user study of 28 undergraduate Software Engineering students that our annotations align with the way in which developers self-explain error notifications. We show that these annotations allow developers to give significantly better self-explanations when compared against today's dominant visualization paradigm, and that better self-explanations yield better mental models of notifications.The results of our work suggest that the diagrammatic techniques developers use to explain problems can serve as an effective foundation for how IDEs should visually communicate to developers.

Current programming models for developing Internet of Things (IoT) applications conceive of an application as an orchestration. An orchestration even if physically distributed is logically centralized and thus ill-suited to the most interesting IoT applications, which involve multiple autonomous parties. We contribute Protocols over Things (PoT), a decentralized programming model for IoT applications that represents an IoT application via a protocol between the parties involved. Notably, PoT works over unordered delivery mechanisms such as UDP and supports application-level reliability mechanisms such as resending messages. We realize PoT using Node-RED, a popular IoT framework, to show how PoT simplifies implementation and avoids errors. Further, we empirically demonstrate that by supporting application-level retry policies, PoT provides improved performance over network-level delivery guarantees.

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Communication protocols are central to engineering decentralized multiagent systems. Modern protocol languages are typically formal and address aspects of decentralization, such as asynchrony. However, modern languages differ in important ways in their basic abstractions and operational assumptions. This diversity makes a comparative evaluation of protocol languages a challenging task. We contribute a rich evaluation of diverse and modern protocol languages. Among the selected languages, Scribble is based on session types; Trace-C and Trace-F on trace expressions; HAPN on hierarchical state machines, and BSPL on information causality. Our contribution is four-fold. One, we contribute important criteria for evaluating protocol languages. Two, for each criterion, we compare the languages on the basis of whether they are able to specify elementary protocols that go to the heart of the criterion. Three, for each language, we map our findings to a canonical architecture style for multiagent systems, highlighting where the languages depart from the architecture. Four, we identify design principles for protocol languages as guidance for future research.

We conceptualize a decentralized software application as one constituted from autonomous agents that communicate via asynchronous messaging. Modern software paradigms such as microservices and settings such as the Internet of Things evidence a growing interest in decentralized applications. Constructing a decentralized application involves designing agents as independent local computations that coordinate successfully to realize the application’s requirements. Moreover, a decentralized application is susceptible to faults manifested as message loss, delay, and reordering. We contribute Mandrake, a programming model for decentralized applications that tackles these challenges without relying on infrastructure guarantees. Specifically, we adopt the construct of an information protocol that specifies messaging between agents purely in causal terms and can be correctly enacted by agents in a shared-nothing environment over nothing more than unreliable, unordered transport. Mandrake facilitates (1) implementing protocol-compliant agents by introducing a programming model; (2) transforming protocols into fault-tolerant ones with simple annotations; and (3) a declarative policy language that makes it easy to implement fault-tolerance in agents based on the capabilities in protocols. Mandrake’s significance lies in demonstrating a straightforward approach for constructing decentralized applications without relying on coordination mechanisms in the infrastructure, thus achieving some of the goals of the founders of networked computing from the 1970s.