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2 results for “golang”
A Study of Real-world Data Races in Golang (Artifact)
<p>The concurrent programming literature is rich with tools and techniques for data race detection. Less, however, has been known about real-world, industry-scale deployment, experience, and insights about data races. Golang (Go for short) is a modern programming language that makes concurrency a first-class citizen. Go offers both message passing and shared memory for communicating among concurrent threads. Go is gaining popularity in modern microservice-based systems. Data races in Go stand in the face of its emerging popularity.</p> <p>In this paper, using our industrial codebase as an example, we demonstrate that Go developers embrace concurrency and show how the abundance of concurrency alongside language idioms and nuances make Go programs highly susceptible to data races. <br> Google's Go distribution ships with a built-in dynamic data race detector based on ThreadSanitizer. Dynamic race detectors pose scalability and flakiness challenges; we discuss various software engineering trade-offs to scale this detector to work effectively at scale.</p> <p>We have deployed this detector in our 50-million lines of Go codebase hosting 2100 distinct microservices, found over 2000 data races, fixed over 1000 data races, spanning 790 distinct code patches submitted by 210 unique developers over a six-month period. Based on a detailed investigation of these data race patterns in Go, we make seven high-level observations relating to the complex interplay between the Go language paradigm and data races. </p>
Dataset for 'Assessing Golang Static Analysis Tools on Real-World Issues'
<p>Go Linter Evaluation Dataset</p> <p>This is a publicly available dataset for 'An empirical evaluation of Golang static code analysis tools for real-world issues.' Please refer to the data according to the names of the spreadsheets.</p> <p>Authors: Jianwei Wu, James Clause</p> <p>Collected Survey Data:<br>- This Excel file contains the collected survey data for the empirical study in details.</p> <p>R Scripts and Raw Data:<br>- These scripts are used for data analysis and processing.<br>- This is the initial data collected from surveys or other sources before any processing or analysis.</p> <p>Surveys for External Participants:<br>- This Excel file contains survey data collected for the evaluation of Go linters.<br>- This folder contains the surveys sent to external participants for collecting their feedback or data.</p> <p>Recruitment Letter.pdf:<br>- This PDF contains an example of the recruitment letter sent to potential survey participants, inviting them to take part in the study.</p> <p>Outputs from Existing Go Linters and Summarized Categories.xlsx:<br>- This Excel file contains outputs from various Go linters and categorized summaries of these outputs. It helps in comparing the performance and features of different linters.</p> <p>Selection of Go Linters.xlsx:<br>- This Excel file lists the Go linters selected for evaluation, along with criteria or reasons for their selection.</p> <p>UD IRB Exempt Letter.pdf:<br>- This PDF contains the Institutional Review Board (IRB) exemption letter from the University of Delaware (UD), indicating that the study involving human participants was exempt from full review.</p> <p>Survey Template.pdf:<br>- This PDF contains an example of the survey sent to the participants.</p> <p>govet issues.pdf:<br>- This PDF contains a list of reported issues about govet. Collected from various pull requests.</p> <p>Approved linters:<br>- staticcheck gofmt govet revive gosec deadcode errcheck.</p> <p>Table 2.jpg:<br>- A detailed figure to show the technical data in Table 2 of the paper.</p> <p>PR-summary-standalone:<br>- This is the AI tool we used to summarize the content of pull requests. Readme file is avaliable in this folder.</p>
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