Boa: A language and infrastructure for analyzing ultra-large-scale software repositories

Dyer, Robert; Nguyen, Hoan Anh; Rajan, Hridesh; Nguyen, Tien N.

doi:10.1109/icse.2013.6606588

Cited by 284 publications

(261 citation statements)

References 13 publications

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“…Since we required JavaScript tokens from each file, other GitHub mining resources such as Boa (Dyer et al, 2013) and GHTorrent (Gousios, 2013) were insufficient. Thus, at the end of June 2017, we downloaded the top 10,000 Java repositories by stars (as an analog of popularity).…”

Section: Building a Corpus Through Miningmentioning

confidence: 99%

Finding and correcting syntax errors using recurrent neural networks

Santos

Campbell

Hindle

et al. 2017

Preprint

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Minor syntax errors are made by novice and experienced programmers alike; however, novice programmers lack the years of intuition that help them resolve these tiny errors. Standard LR parsers typically resolve syntax errors and their precise location poorly. We propose a methodology that helps locate where syntax errors occur, but also suggests possible changes to the token stream that can fix the error identified. This methodology finds syntax errors by checking if two language models "agree" on each token. If the models disagree, it indicates a possible syntax error; the methodology tries to suggest a fix by finding an alternative token sequence obtained from the models. We trained two LSTM (Long short-term memory) language models on a large corpus of JavaScript code collected from GitHub. The dual LSTM neural network model predicts the correct location of the syntax error 54.74% in its top 4 suggestions and produces an exact fix up to 35.50% of the time. The results show that this tool and methodology can locate and suggest corrections for syntax errors. Our methodology is of practical use to all programmers, but will be especially useful to novices frustrated with incomprehensible syntax errors.

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Section: Building a Corpus Through Miningmentioning

confidence: 99%

Finding and correcting syntax errors using recurrent neural networks

Santos

Campbell

Hindle

et al. 2017

Preprint

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“…), in particular most of them ( [13], [14], [15], [16], [17], [18], [19]) target older SCM systems such as CVS and SVN, while only few focus on Git ( [7], [20], [8], [9], [21]). More recent works have the goal of analyzing complete OSS forges such as GitHub or SourceForge ( [10], [22]).…”

Section: Motivation and State Of The Artmentioning

confidence: 99%

“…Only [19], [15], [16], [8], [9] and [21] make their implementations available to download. However only [21] and [15] have been active in the past years. Gitana has been made available on GitHub at [12].…”

Section: Motivation and State Of The Artmentioning

confidence: 99%

Gitana: A SQL-Based Git Repository Inspector

Cosentino

Izquierdo

Cabot

2015

Conceptual Modeling

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Abstract. Software development projects are notoriously complex and difficult to deal with. Several support tools such as issue tracking, code review and Source Control Management (SCM) systems have been introduced in the past decades to ease development activities. While such tools efficiently track the evolution of a given aspect of the project (e.g., bug reports), they provide just a partial view of the project and often lack of advanced querying mechanisms limiting themselves to command line or simple GUI support. This is particularly true for projects that rely on Git, the most popular SCM system today. In this paper, we propose a conceptual schema for Git and an approach that, given a Git repository, exports its data to a relational database in order to (1) promote data integration with other existing SCM tools and (2) enable writing queries on Git data using standard SQL syntax. To ensure efficiency, our approach comes with an incremental propagation mechanism that refreshes the database content with the latest modifications. We have implemented our approach in Gitana, an open-source tool available on GitHub.

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“…Boa [3] is a query language for large-scale software repositories. It allows answering high-level questions over a plethora of software repositories.…”

Section: Related Workmentioning

confidence: 99%

“…QWALKEKO has been applied successfully to detect refactorings [1] and classify changes made to SELENIUM scripts [2]. The source code, installation instructions 2 , code 3 and video used in this paper can be found on Github.…”

Section: Introductionmentioning

confidence: 99%

Querying the History of Software Projects Using QWALKEKO

Stevens

Roover

2014

2014 IEEE International Conference on Software Maintenance and Evolution

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Abstract-We present the QWALKEKO meta-programming library for Clojure that enables querying the history of versioned software projects in a declarative manner. Unique to this library is its support for regular path expressions within history queries. Regular path expressions are akin to regular expressions, except that they match a sequence of successive snapshots of a software project along which user-specified logic conditions must hold. Such logic conditions can concern the source code within a snapshot, versioning information associated with the snapshot, as well as patterns of source code changes with respect to other snapshots. We have successfully used the resulting multi-faceted queries to detect refactorings in project histories. In this paper, we discuss how applicative logic meta-programming enabled combining the heterogenous components of QWALKEKO into a uniform whole. We focus on the applicative logic interface to a new implementation of a well-known change distilling algorithm. We use the problem of detecting and categorizing changes made to SELENIUM-based test scripts for illustration purposes.

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Boa: A language and infrastructure for analyzing ultra-large-scale software repositories

Cited by 284 publications

References 13 publications

Finding and correcting syntax errors using recurrent neural networks

Finding and correcting syntax errors using recurrent neural networks

Gitana: A SQL-Based Git Repository Inspector

Querying the History of Software Projects Using QWALKEKO

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