Do Developers Read Compiler Error Messages?

Barik, Titus; SMITH, JEAN C.; Lubick, Kevin; Holmes, Elisabeth; Feng, Jing; Murphy-Hill, Emerson; Parnin, Chris

doi:10.1109/icse.2017.59

Cited by 69 publications

(21 citation statements)

References 27 publications

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“…Eye-tracking experiments are a validated approach to understand the nonverbal cues used and challenges encountered by programmers. Fixation and scanpath data coupled with a supplementary metric to evaluate the outcome has helped better characterize how programmers use tools and infrastructure [25] For example, Barik and colleagues able to combine a combination of fixations, revisits, and task performance to interpret error reading styles in an IDE [26]. Likewise, Behroozi and colleagues used a similar approach to understand confusion during technical interviews at the white board [27].…”

Section: Related Workmentioning

confidence: 99%

Beyond the Code Itself: How Programmers Really Look at Pull Requests

Ford

Behroozi

Serebrenik

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS)

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Developers in open source projects must make decisions on contributions from other community members, such as whether or not to accept a pull request. However, secondary factors-beyond the code itself-can influence those decisions. For example, signals from GitHub profiles, such as a number of followers, activity, names, or gender can also be considered when developers make decisions. In this paper, we examine how developers use these signals (or not) when making decisions about code contributions. To evaluate this question, we evaluate how signals related to perceived gender identity and code quality influenced decisions on accepting pull requests. Unlike previous work, we analyze this decision process with data collected from an eye-tracker. We analyzed differences in what signals developers said are important for themselves versus what signals they actually used to make decisions about others. We found that after the code snippet (x = 57%), the second place programmers spent their time fixating is on supplemental technical signals (x = 32%), such as previous contributions and popular repositories. Diverging from what participants reported themselves, we also found that programmers fixated on social signals more than recalled.

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Section: Related Workmentioning

confidence: 99%

Beyond the Code Itself: How Programmers Really Look at Pull Requests

Ford

Behroozi

Serebrenik

et al. 2019

2019 IEEE/ACM 41st International Conference on Software Engineering: Software Engineering in Society (ICSE-SEIS)

Self Cite

View full text Add to dashboard Cite

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“…A comparable service for software developer recruitment is not yet known. Therefore, previous studies used convenience samples such as computer science students [2,5,21,23] or GitHub developers [3,15,26,38,39].…”

Section: Methodological Discussionmentioning

confidence: 99%

"If you want, I can store the encrypted password"

Naiakshina

Danilova

Gerlitz

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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In 2017 and 2018, Naiakshina et al. [21, 22] studied in a lab setting whether computer science students need to be told to write code that stores passwords securely. The authors' results showed that, without explicit prompting, none of the students implemented secure password storage. When asked about this oversight, a common answer was that they would have implemented secure storage-if they were creating code for a company. To shed light on this possible confusion, we conducted a mixed-methods field study with developers. We hired freelance developers online and gave them a similar password storage task followed by a questionnaire to gain additional insights into their work. From our research, we offer two contributions. First of all, we reveal that, similar to the students, freelancers do not store passwords securely unless prompted, they have misconceptions about secure password storage, and they use outdated methods. Secondly, we discuss the methodological implications of using freelancers and students in developer studies. CCS CONCEPTS • Security and privacy → Usability in security and privacy; • Human-centered computing → Empirical studies in HCI .

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“…Barik et al have developed a large number of guidelines about how the error messages should be presented to developers [33], [34], [35], [36]. Most of these guidelines could be applicable to novice programmers as well, for example, the recommendation that the error message which appears in the editor must be close to the source of error.…”

Section: B Compilation Error Message Enhancementmentioning

confidence: 99%

Targeted Example Generation for Compilation Errors

Ahmed

Sindhgatta

Srivastava

et al. 2019

2019 34th IEEE/ACM International Conference on Automated Software Engineering (ASE)

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We present TEGCER, an automated feedback tool for novice programmers. TEGCER uses supervised classification to match compilation errors in new code submissions with relevant pre-existing errors, submitted by other students before. The dense neural network used to perform this classification task is trained on 15000+ error-repair code examples. The proposed model yields a test set classification Pred@3 accuracy of 97.7% across 212 error category labels. Using this model as its base, TEGCER presents students with the closest relevant examples of solutions for their specific error on demand. A large scale (N > 230) usability study shows that students who use TEGCER are able to resolve errors more than 25% faster on average than students being assisted by human tutors.

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Do Developers Read Compiler Error Messages?

Cited by 69 publications

References 27 publications

Beyond the Code Itself: How Programmers Really Look at Pull Requests

Beyond the Code Itself: How Programmers Really Look at Pull Requests

"If you want, I can store the encrypted password"

Targeted Example Generation for Compilation Errors

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