The promises and perils of mining GitHub

Kalliamvakou, Eirini; Gousios, Georgios; Blincoe, Kelly; Singer, Leif; Germán, Daniel M.; Damian, Daniela

doi:10.1145/2597073.2597074

Cited by 599 publications

(400 citation statements)

References 25 publications

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“…The use of projects from GitHub leads to a number of threats, as documented by Kalliamvakou et al (2014). In our data collection, we tried to mitigate these biases (e.g., we only selected active projects), but some limitations are still present.…”

Section: Threats To Validitymentioning

confidence: 99%

On the reaction to deprecation of clients of 4 + 1 popular Java APIs and the JDK

2017

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Application Programming Interfaces (APIs) are a tremendous resource-that is, when they are stable. Several studies have shown that this is unfortunately not the case. Of those, a large-scale study of API changes in the Pharo Smalltalk ecosystem documented several findings about API deprecations and their impact on API clients. We extend this study, by analyzing clients of both popular third-party Java APIs and the JDK API. This results in a dataset consisting of more than 25,000 clients of five popular Java APIs on GitHub, and 60 clients of the JDK API from Maven Central. This work addresses several shortcomings of the previous study, namely: a study of several distinct API clients in a popular, statically-typed language, with more accurate version information. We compare and contrast our findings with the previous study and highlight new ones, particularly on the API client update practices and the startling similarities between reaction behavior in Smalltalk and Java. We make a comparison between reaction behavior for third-party APIs and JDK APIs, given that language APIs are a peculiar case in terms of wide-spread usage, documentation, and support from IDEs. Furthermore, we investigate the connection between reaction patterns of a client and the deprecation policy adopted by the API used.

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Section: Threats To Validitymentioning

confidence: 99%

On the reaction to deprecation of clients of 4 + 1 popular Java APIs and the JDK

2017

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“…Inferring User Name And Country The simple task of retrieving the first name of a GitHub user is challenging due to the noise and lack of information in the dataset [16]. Approximately 20% of all users were labeled as "unknown" in the GHTorrent dump analysed.…”

Section: Measuring the Control Variablesmentioning

confidence: 99%

How diverse is your team? Investigating gender and nationality diversity in GitHub teams

Destefanis

Counsell

Swift

et al. 2016

Preprint

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Abstract. Building an effective team of developers is a complex task faced by both software companies and open source communities. The problem of forming a "dream" team involves many variables, including consideration of human factors, and it is not a dilemma solvable in a mathematical way. Empirical studies might provide interesting insights to explain which factors need to be taken into account in building a team of developers and which levers act to optimise collaboration and productivity among developers. In this paper, we present the results of an empirical study aimed at investigating the link between team diversity (i.e., gender, nationality) and productivity (issue fixing time). We consider issues solved from the GHTorrent dataset inferring gender and nationality of each team's members. We also evaluate the politeness of all comments involved in issue resolution. Results show that higher gender diversity is linked with a lower team average issue fixing time and that nationality diversity is linked with lower team politeness.

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“…Kalliamvakou et al mined GitHub repositories to investigate their characteristics and their qualities [10]. They presented a detailed study discussing different project characteristics, such as (in)activity.…”

Section: Related Workmentioning

confidence: 99%

“…Previously mentioned approaches use a self-made database for their own purpose as we could seen this advice in the work of Kalliamvakou et al too [10]. Bug prediction techniques and approaches can be presented and compared in different ways; however, there are some basic points that can serve as common components.…”

Section: Related Workmentioning

confidence: 99%

“…To do this, the bug reports managed by these source code hosting providers must be connected to the appropriate source code parts [14]. A common practice in version control systems is to describe the changes in a comment belonging to a commit and often provide an ID for the associated bug report which the commit is supposed to fix [10]. This can be used to identify the faulty versions of the source code.…”

Section: Introductionmentioning

confidence: 99%

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Characterization of Source Code Defects by Data Mining Conducted on GitHub

Gyimesi

Tóth

et al. 2015

Computational Science and Its Applications -- ICCSA 2015

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Abstract. In software systems the coding errors are unavoidable due to the frequent source changes, the tight deadlines and the inaccurate specifications. Therefore, it is important to have tools that help us in finding these errors. One way of supporting bug prediction is to analyze the characteristics of the previous errors and identify the unknown ones based on these characteristics. This paper aims to characterize the known coding errors. Nowadays, the popularity of the source code hosting services like GitHub are increasing rapidly. They provide a variety of services, among which the most important ones are the version and bug tracking systems. Version control systems store all versions of the source code, and bug tracking systems provide a unified interface for reporting errors. Bug reports can be used to identify the wrong and the previously fixed source code parts, thus the bugs can be characterized by static source code metrics or by other quantitatively measured properties using the gathered data. We chose GitHub for the base of data collection and we selected 13 Java projects for analysis. As a result, a database was constructed, which characterizes the bugs of the examined projects, thus can be used, inter alia, to improve the automatic detection of software defects.

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The promises and perils of mining GitHub

Cited by 599 publications

References 25 publications

On the reaction to deprecation of clients of 4 + 1 popular Java APIs and the JDK

On the reaction to deprecation of clients of 4 + 1 popular Java APIs and the JDK

How diverse is your team? Investigating gender and nationality diversity in GitHub teams

Characterization of Source Code Defects by Data Mining Conducted on GitHub

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