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Serverless computing enables service developers to focus on creating useful services, without being concerned about how these services would be deployed and provisioned. Many developers reuse existing open-source serverless functions to create their own functions. However, existing technologies for searching open-source software repositories have not taken into consideration the unique features of serverless functions. This paper presents a novel approach to searching for serverless functions, called Open-Source Serverless Search (OS3) that maximizes the utility of the returned serverless functions by (1) basing the search process on both descriptive keywords and library usages, thus increasing the search results' precision and completeness; (2) filtering and ranking the search results based on the software license, to accommodate the unique requirements of deploying serverless functions on dissimilar platforms, including cloud and edge computing. Implemented in 3K lines of Python, with a search space of 5,981 serverless repositories from four major serverless platforms, OS3 outperforms existing search approaches in terms of the suitability of the search results, based on our evaluation with realistic use cases. 

Project-based learning (PjBL) has been increasingly adopted in computer science courses to improve students’ engagement and learning outcomes. Although a computer networks course is in great need of a PjBL course module, no such module is available due to the huge gap between PjBL’s design requirements and the current structure and content of the course. This paper introduces a novel PjBL module for a computer networks course, which challenges the students with a real world problem of developing the communication system for a smart lock. Following the PjBL design principles, we devise several scaffolding activities and assignments, which can be integrated into a semester-long computer networks course. We test ran the PjBL module in both undergraduate- and graduate-level computer networks courses. Our preliminary evaluation results show that the proposed PjBL module is well received by the students and helps improve their learning outcomes. 

Equivalent services deliver the same functionality with dissimilar non-functional characteristics, including latency, accuracy, and cost. With these dissimilarities in mind, developers can exploit the combined execution of equivalent services to increase accuracy, shorten latency, or reduce cost. However, it remains unknown how to effectively combine equivalent services to satisfy application requirements. With the recent surge in popularity of machine learning, different vendors offer a plethora of equivalent services, whose characteristics are mostly undocumented. As a result, developers cannot make an informed decision about which service to select from a set of equivalent services. To address this problem, we explore different service combination strategies (i.e., majority voting, weighted-majority voting, stacking, and custom) to ascertain their impact on nonfunctional characteristics. In particular, we study how these strategies impact the accuracy, cost, and latency of the face detection task and validate our findings on the sentiment analysis task. We consider the combined executions of commercial web services, deployed in the cloud, and open-source implementations, deployed as edge services. Our evaluation reveals that the combined execution of equivalent services is most effective for improving cost and latency. Informed by our experimental results, we formulate practical guidelines to help developers identify the best execution strategy for a given set of services. 

Edge computing applications use the computational, sensor, and networking resources of nearby mobile and stationary computing devices. Because dissimilar devices can provide these resources, one cannot predict which exact combinations of resources will be available at runtime. The resulting variability hinders the development of edge computing applications. To address this problem, we present a new programming model that employs a domain-specific language (DSL), through which the developer declaratively specifies a collection of microservices and how they invoke each other. Given a concise declarative service suite specification, the DSL compiler automatically generates an execution plan, carried out by our distributed runtime. The resulting programming model is both reliable and efficient. The reliability is achieved by enabling the developer to provide equivalent microservices as switch-over recovery strategies. The efficiency is achieved by the DSL compiler orchestrating the speculatively parallel execution of certain equivalent microservices. Our evaluation demonstrates the reliability, efficiency, and expressiveness of the programming model, which can help developers who need to cope with variable resources at the edge. 

The applicability of the microservice architecture has extended beyond traditional web services, making steady inroads into the domains of IoT and edge computing. Due to dissimilar contexts in different execution environments and inherent mobility, edge and IoT applications suffer from low execution reliability. Replication, traditionally used to increase service reliability and scalability, is inapplicable in these resourcescarce environments. Alternately, programmers can orchestrate the parallel or sequential execution of equivalent microservices— microservices that provide the same functionality by different means. Unfortunately, the resulting orchestrations rely on parallelization, synchronization, and failure handing, all tedious and error-prone to implement. Although automated orchestration shifts the burden of generating workflows from the programmer to the compiler, existing programming models lack both syntactic and semantic support for equivalence. In this paper, we enhance compiler-generated execution orchestration with equivalence to efficiently increase reliability. We introduce a dataflow-based domain-specific language, whose dataflow specifications include the implicit declarations of equivalent microservices and their execution patterns. To automatically generate reliable workflows and execute them efficiently, we introduce new equivalence workflow constructs. Our evaluation results indicate that our solution can effectively and efficiently increase the reliability of microservice-based applications.