1,720,980 research outputs found
GENOA—a customizable, front-end-retargetable source code analysis framework
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Code analysis
tools provide support for such software engineering tasks as program understanding, software metrics, testing, and reengineering. In this article we describe GENOA, the framework underlying application generators such as Aria and GEN++ which have been used to generate a wide range of practical code analysis tools. This experience illustrates
front-end retargetability
of GENOA; we describe the features of the GENOA framework that allow it to be used with different front ends. While permitting arbitrary parse tree computations, the GENOA specification language has special, compact iteration operators that are tuned for expressing simple, polynomial-time analysis programs; in fact, there is a useful sublanguage of the GENOA language that can express precisely all (and only)
polynomial-time
(PTIME) analysis programs on parse trees. Thus, we argue that the GENOA language is a simple and convenient vehicle for implementing a range of analysis tools. We also argue that the “front-and reuse” approach of GENOA offers an important advantage for tools aimed at large software projects: the reuse of complex, expensive build procedures to run generated tools over large source bases. In this article, we describe the GENOA framework and our experiences with it.
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Reverse Engineering the Bazaar: Collaboration and Communication in Open Source Development
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ManyTypes4TypeScript: A Comprehensive TypeScript Dataset for Sequence-Based Type Inference
No full textIn this paper, we present ManyTypes4TypeScript, a very large corpus for training and evaluating machine-learning models for sequence-based type inference in TypeScript. The dataset includes over 9 million type annotations, across 13,953 projects and 539,571 files. The dataset is approximately 10x larger than analogous type inference datasets for Python, and is the largest available for TypeScript. We also provide API access to the dataset, which can be integrated into any tokenizer and used with any state-of-the-art sequence-based model. Finally, we provide analysis and performance results for state-of-the-art code-specific models, for baselining. ManyTypes4TypeScript is available on Huggingface and Zenodo.
This dataset was collected on January 22, 2022 and deduplicated with Allamanis code deduplication tool
First International Workshop on Quantitative Stochastic Models in the Verification and Design of Software Systems (QUOVADIS 2010)
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Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Measuring the effect of social communications on individual working rhythms: A case study of open source software
No full textAbstract—This paper proposes novel quantitative methods to measure the effects of social communications on individual working rhythms by analyzing the communication and code committing records in tens of Open Source Software (OSS) projects. Our methods are based on complex network and time-series analysis. We define the notion of a working rhythm as the average time spent on a commit task and we study the correlation between working rhythm and communication frequency. We build communication networks for code developers, and find that the developers with higher social status, represented by the nodes with larger number of outgoing or incoming links, always have faster working rhythms and thus contribute more per unit time to the projects. We also study the dependency between work (committing) and talk (communication) activities, in particular the effect of their interleaving. We introduce multi-activity time-series and quantitative measures based on activity latencies to evaluate this dependency. Comparison of simulated time-series with the real ones suggests that when work and talk activities are in proximity they may accelerate each other in OSS systems. These findings suggest that frequent communication before and after committing activities is essential for effective software development in distributed systems. Index Terms—social network; time-series; committing rhythm; open source software; work and talk; I
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