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  1. null (Ed.)
    Best Paper Award 
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  2. Modern web applications are distributed across a browser-based client and a cloud-based server. Distribution provides access to remote resources, accessed over the web and shared by clients. Much of the complexity of inspecting and evolving web applications lies in their distributed nature. Also, the majority of mature program analysis and transformation tools works only with centralized software. Inspired by business process re-engineering, in which remote operations can be insourced back in house to restructure and outsource anew, we bring an analogous approach to the re-engineering of web applications. Our target domain are full-stack JavaScript applications that implement both the client and server code in this language. Our approach is enabled by Client Insourcing, a novel automatic refactoring that creates a semantically equivalent centralized version of a distributed application. This centralized version is then inspected, modified, and redistributed to meet new requirements. After describing the design and implementation of Client Insourcing, we demonstrate its utility and value in addressing changes in security, reliability, and performance requirements. By reducing the complexity of the non-trivial program inspection and evolution tasks performed to meet these requirements, our approach can become a helpful aid in the re-engineering of web applications in this domain. 
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  3. Distributed applications enhance their execution by using remote resources. However, distributed execution incurs communication, synchronization, fault-handling, and security overheads. If these overheads are not offset by the yet larger execution enhancement, distribution becomes counterproductive. For maximum benefits, the distribution’s granularity cannot be too fine or too crude; it must be just right. In this paper, we present a novel approach to re-architecting distributed applications, whose distribution granularity has turned ill-conceived. To adjust the distribution of such applications, our approach automatically reshapes their remote invocations to reduce aggregate latency and resource consumption. To that end, our approach insources a remote functionality for local execution, splits it into separate functions to profile their performance, and determines the optimal redistribution based on a cost function. Redistribution strategies combine separate functions into single remotely invocable units. To automate all the required program transformations, our approach introduces a series of domainspecific automatic refactorings. We have concretely realized our approach as an analysis and automatic program transformation infrastructure for the important domain of full-stack JavaScript applications, and evaluated its value, utility, and performance on a series of real-world cross-platform mobile apps. Our evaluation results indicate that our approach can become a useful tool for software developers charged with the challenges of re-architecting distributed applications. 
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  4. Localizing bugs in distributed applications is complicated by the potential presence of server/middleware misconfigurations and intermittent network connectivity. In this paper, we present a novel approach to localizing bugs in distributed web applications, targeting the important domain of full-stack JavaScript applications. The debugged application is first automatically refactored to create its semantically equivalent centralized version by gluing together the application’s client and server parts, thus separating the programmer-written code from configuration/environmental issues as suspected bug causes. The centralized version is then debugged to fix various bugs. Finally, based on the bug fixing changes of the centralized version, a patch is automatically generated to fix the original application source files. We show how our approach can be used to catch bugs that include performance bottlenecks and memory leaks. These results indicate that our debugging approach can facilitate the challenges of localizing and fixing bugs in web applications. 
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  5. A native cross-platform mobile app has multiple platform-specific implementations. Typically, an app is developed for one platform and then ported to the remaining ones. Translating an app from one language (e.g., Java) to another (e.g., Swift) by hand is tedious and error-prone, while automated translators either require manually defined translation rules or focus on translating APIs. To automate the translation of native cross-platform apps, we present J2SINFERER, a novel approach that iteratively infers syntactic transformation rules and API mappings from Java to Swift. Given a software corpus in both languages, J2SLNFERER first identifies the syntactically equivalent code based on braces and string similarity. For each pair of similar code segments, J2SLNFERER then creates syntax trees of both languages, leveraging the minimalist domain knowledge of language correspondence (e.g., operators and markers) to iteratively align syntax tree nodes, and to infer both syntax and API mapping rules. J2SLNFERER represents inferred rules as string templates, stored in a database, to translate code from Java to Swift. We evaluated J2SLNFERER with four applications, using one part of the data to infer translation rules, and the other part to apply the rules. With 76% in-project accuracy and 65% cross-project accuracy, J2SLNFERER outperforms in accuracy j2swift, a state-of-the-art Java-to-Swift conversion tool. As native cross-platform mobile apps grow in popularity, J2SLNFERER can shorten their time to market by automating the tedious and error prone task of source-to-source translation. 
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