Crowdsourcing in Software Engineering: Models, Motivations, and Challenges

LaToza, Thomas D.; Hoek, André van der

doi:10.1109/ms.2016.12

Cited by 141 publications

(64 citation statements)

References 9 publications

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“…Likewise, Yan et al [45] hire programmers in a crowdsourced process to improve software testing. LaToza and van der Hoek [46] discuss several similar strategies, involving hiring many programmers to assist in tasks that are relatively small in the context of software development.…”

Section: Crowdsourcing In Software Engineeringmentioning

confidence: 99%

Automatically Extracting Subroutine Summary Descriptions from Unstructured Comments

Eberhart

LeClair

McMillan

2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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descriptions of subroutines are short (usually one-sentence) natural language explanations of a subroutine's behavior and purpose in a program. These summaries are ubiquitous in documentation, and many tools such as JavaDocs and Doxygen generate documentation built around them. And yet, extracting summaries from unstructured source code repositories remains a difficult research problem -it is very difficult to generate clean structured documentation unless the summaries are annotated by programmers. This becomes a problem in large repositories of legacy code, since it is cost prohibitive to retroactively annotate summaries in dozens or hundreds of old programs. Likewise, it is a problem for creators of automatic documentation generation algorithms, since these algorithms usually must learn from large annotated datasets, which do not exist for many programming languages. In this paper, we present a semi-automated approach via crowdsourcing and a fully-automated approach for annotating summaries from unstructured code comments. We present experiments validating the approaches, and provide recommendations and cost estimates for automatically annotating large repositories.

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Section: Crowdsourcing In Software Engineeringmentioning

confidence: 99%

Automatically Extracting Subroutine Summary Descriptions from Unstructured Comments

Eberhart

LeClair

McMillan

2020

2020 IEEE 27th International Conference on Software Analysis, Evolution and Reengineering (SANER)

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“…In the onion models, advancement through the member types is reward and recognition for each member's abilities and achievements [17], and developer initiation in OSS depends on the social and technical actions of project contributors [18]. Therefore, newcomers must first become familiar with the code base, architecture, build environment, and work practices, which might take days or weeks [5]. Bug bounty program contributors are almost outside of traditional software development hierarchies and onion models.…”

Section: B Beyond Onion Modelsmentioning

confidence: 99%

“…LaToza and van der Hoek presented three factors that distinguish crowdsourcing from other outsourced work: (1) the work is solicited through an open call to which basically anyone can respond, (2) the workers who volunteer are unknown to the organization needing the work done, and (3) the group of workers can be large [5]. The authors compared different types of crowdsourcing work based on eight dimensions as shown in Table I.…”

Section: Introductionmentioning

confidence: 99%

Understanding the Heterogeneity of Contributors in Bug Bounty Programs

Hata

Guo

Babar

2017

2017 ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM)

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Background: While bug bounty programs are not new in software development, an increasing number of companies, as well as open source projects, rely on external parties to perform the security assessment of their software for reward. However, there is relatively little empirical knowledge about the characteristics of bug bounty program contributors. Aim: This paper aims to understand those contributors by highlighting the heterogeneity among them. Method: We analyzed the histories of 82 bug bounty programs and 2,504 distinct bug bounty contributors, and conducted a quantitative and qualitative survey. Results: We found that there are project-specific and non-specific contributors who have different motivations for contributing to the products and organizations. Conclusions: Our findings provide insights to make bug bounty programs better and for further studies of new software development roles.

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“…While the end-users indirectly benefit from APP STORE 2.0 with better apps, we also imagine more direct ways to involve users in the automated quality feedback loop. In this direction, we imagine that the APP STORE 2.0 would provide incentive mechanisms [14] to encourage users to participate in the process of collecting execution data, running performance measurement scenarios, executing automatically generated patched versions. For instance, users can be rewarded with early access to new updates, with free access to paid functionalities, etc.…”

Section: Techniquesmentioning

confidence: 99%

App Store 2.0: From Crowdsourced Information to Actionable Feedback in Mobile Ecosystems

et al. 2017

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Given the increasing competition in mobile app ecosystems, improving the experience of users has become a major goal for app vendors. This article introduces a visionary app store, called APP STORE 2.0, which exploits crowdsourced information about apps, devices and users to increase the overall quality of the delivered mobile apps. We sketch a blueprint architecture of the envisioned app stores and discuss different kinds of actionable feedback that app stores can generate using crowdsourced information.

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Crowdsourcing in Software Engineering: Models, Motivations, and Challenges

Cited by 141 publications

References 9 publications

Automatically Extracting Subroutine Summary Descriptions from Unstructured Comments

Automatically Extracting Subroutine Summary Descriptions from Unstructured Comments

Understanding the Heterogeneity of Contributors in Bug Bounty Programs

App Store 2.0: From Crowdsourced Information to Actionable Feedback in Mobile Ecosystems

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