Skip to main content
SpringerLink
Log in

An Empirical Study of Link Sharing in Review Comments

  • Conference paper
  • First Online:
Software Engineering and Methodology for Emerging Domains (NASAC 2017, NASAC 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 861))

Abstract

In the pull-based development, developers sometimes exchange review comments and share links, namely Uniform Resource Locators (URLs). Links are used to refer to related information from different websites, which may be beneficial to pull request evaluation. Nevertheless, little effort has been done on analyzing how links are shared and whether sharing links has any impacts on code review in GitHub. In this paper, we conduct a study of link sharing in review comments. We collect 114,810 pull requests and 251,487 review comments from 10 popular projects in GitHub. We find that 5.25% of pull requests have links in review comments on average. We divide links into two types: internal links which point to context in the same project, and external links which point to context outside of the project. We observe that 51.49% of links are internal, while 48.51% of links are external. The majority of internal links point to pull requests or blobs inside projects. We further study impacts of links. Results show that pull requests with links in review comments have more comments, more commenters and longer evaluation time than pull requests without links. These findings show that developers indeed share links and refer to related information in review comments. These results inspire future studies which enable more effective information sharing in the open source community, and improve information accessibility and navigability for software developers.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    https://developer.github.com/v3/pulls/comments/.

  2. 2.

    https://github.com/symfony/symfony/pull/13638.

  3. 3.

    https://developer.github.com/.

  4. 4.

    http://ghtorrent.org/.

  5. 5.

    https://github.com/Yuyue/pullreq_ci/blob/master/all_projects.csv.

  6. 6.

    Jing Jiang, Jin Cao, Xin Xia, Li Zhang. Exploring and Recommending Tags for Pull Requests in GitHub. In submission.

  7. 7.

    https://developer.github.com/v3/git/blobs/.

  8. 8.

    https://github.com/owncloud/core/blob/master/config/config.sample.php#L81.

  9. 9.

    https://help.github.com/articles/about-github-wikis/.

References

  1. Gousios, G., Pinzger, M., van Deursen, A.: An exploratory study of the pull-based software development model. In: Proceedings of the 36th International Conference on Software Engineering, pp. 345–355. ACM (2014)

    Google Scholar 

  2. Tsay, J., Dabbish, L., Herbsleb, J.: Influence of social and technical factors for evaluating contribution in GitHub. In: Proceedings of the 36th International Conference on Software Engineering, pp. 356–366. ACM (2014)

    Google Scholar 

  3. Tsay, J., Dabbish, L., Herbsleb, J.: Let’s talk about it: evaluating contributions through discussion in GitHub. In: Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering - FSE 2014, pp. 144–154 (2014)

    Google Scholar 

  4. Rahman, M.M., Roy, C.K., Kula, R.G.: Predicting usefulness of code review comments using textual features and developer experience. In: Proceedings of MSR, Buenos Aires, Argentina, pp. 215–226, May 2017

    Google Scholar 

  5. Jiang, J., Yang, Y., He, J., Blanc, X., Zhang, L.: Who should comment on this pull request? Analyzing attributes for more accurate commenter recommendation in pull-based development. Inf. Softw. Technol. 84, 48–62 (2017)

    Article  Google Scholar 

  6. Gomez, C., Cleary, B., Singer, L.: A study of innovation diffusion through link sharing on stack overflow. In: Proceedings of MSR, San Francisco, USA, May 2013

    Google Scholar 

  7. Ye, D., Xing, Z., Kapre, N.: The structure and dynamics of knowledge network in domain-specific qa sites: a case study of stack overflow. Empir. Softw. Eng. 22, 375–406 (2017)

    Article  Google Scholar 

  8. Hellendoorn, V.J., Devanbu, P.T., Bacchelli, A.: Will they like this?: evaluating code contributions with language models. In: Proceedings of the 12th Working Conference on Mining Software Repositories, pp. 157–167. IEEE Press (2015)

    Google Scholar 

  9. Gousios, G., Zaidman, A., Storey, M.-A., Van Deursen, A.: Work practices and challenges in pull-based development: the integrator’s perspective. In: Proceedings of the 37th International Conference on Software Engineering-Volume 1, pp. 358–368. IEEE Press (2015)

    Google Scholar 

  10. Bacchelli, A., Bird, C.: Expectations, outcomes, and challenges of modern code review. In: Proceedings of ICSE, San Francisco, USA, May 2013

    Google Scholar 

  11. Zhang, Y., Wang, H., Yin, G., Wang, T., Yue, Y.: Social media in github the role of @-mention in assisting software development. Sci. China Inf. Sci. 60, 1–18 (2017)

    Google Scholar 

  12. Vasilescu, B., Yu, Y., Wang, H., Devanbu, P., Filkov, V.: Quality and productivity outcomes relating to continuous integration in GitHub. In: Proceedings of the 2015 10th Joint Meeting on Foundations of Software Engineering, pp. 805–816. ACM (2015)

    Google Scholar 

  13. Cabot, J., Izquierdo, J.L.C., Cosentino, V., Rolandi, B.: Exploring the use of labels to categorize issues in open-source software projects. In: 2015 IEEE 22nd International Conference on Software Analysis, Evolution and Reengineering (SANER), pp. 550–554. IEEE (2015)

    Google Scholar 

  14. Bissyande, T.F., Lo, D., Jiang, L., Reveillere, L., Klein, J., Le Traon, Y.: Got issues? Who cares about it? A large scale investigation of issue trackers from GitHub. In: Proceedings of ISSRE, Washington DC, USA, November 2013

    Google Scholar 

  15. Mann, H.B., Whitney, D.R.: On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Stat. 18, 50–60 (1947)

    Article  MathSciNet  Google Scholar 

  16. Zhang, Y., Yu, Y., Wang, H., Vasilescu, B., Filkov, V.: Within-ecosystem issue linking: a large-scale study of rails. In: The 7th International Workshop on Mining Software Repositories, Montpellier, France, September 2018

    Google Scholar 

  17. Gousios, G., Storey, M.-A., Bacchelli, A.: Work practices and challenges in pull-based development: the contributor’s perspective. In: Proceedings of ICSE, Austin, USA, pp. 285–296, May 2016

    Google Scholar 

  18. Coelho, J., Valente, M.T.: Why modern open source projects fail. In: Proceedings of FSE, Paderborn, Germany, pp. 186–196, September 2017

    Google Scholar 

  19. Zhu, J., Zhou, M., Mockus, A.: Effectiveness of code contribution: from patch-based to pull-request-based tools. In: Effectiveness of Code Contribution: From Patch-Based to Pull-Request-Based Tools, Seattle, USA, pp. 871–882, November 2016

    Google Scholar 

  20. Jiang, J., Lo, D., Ma, X., Feng, F., Zhang, L.: Understanding inactive yet available assignees in GitHub. Inf. Softw. Technol. 91, 44–55 (2017)

    Article  Google Scholar 

  21. Li, Z., Yue, Y., Yin, G., Wang, T., Fan, Q., Wang, H.: Automatic classification of review comments in pull-based development model. In: Proceedings of SEKE, Pittsburgh, USA, July 2017

    Google Scholar 

  22. Yue, Y., Yin, G., Wang, T., Yang, C., Wang, H.: Determinants of pull-based development in the context of continuous integration. Sci. China Inf. Sci. 59(8), 1–14 (2016)

    Google Scholar 

  23. Yue, Y., Wang, H., Yin, G., Wang, T.: Reviewer recommendation for pull-requests in GitHub: what can we learn from code review and bug assignment? Inf. Softw. Technol. 74, 204–218 (2016)

    Article  Google Scholar 

Download references

Acknowledgment

This work is supported by the National Key Research and Development Program of China No. 2018YFB1004202, National Natural Science Foundation of China under Grant No. 61732019 and the State Key Laboratory of Software Development Environment under Grant No. SKLSDE-2018ZX-12.

Author information

Authors and Affiliations

  1. State Key Laboratory of Software Development Environment, Beihang University, Beijing, China

    Jing Jiang, Jin Cao & Li Zhang

Authors
  1. Jing Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jin Cao
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Li Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Li Zhang .

Editor information

Editors and Affiliations

  1. Beijing University of Chemical Technology, Beijing, China

    Zheng Li

  2. Beijing Institute of Technology, Beijing, China

    He Jiang

  3. Peking University, Beijing, China

    Ge Li

  4. Peking University, Beijing, China

    Minghui Zhou

  5. Nanjing University, Nanjing, China

    Ming Li

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Jiang, J., Cao, J., Zhang, L. (2019). An Empirical Study of Link Sharing in Review Comments. In: Li, Z., Jiang, H., Li, G., Zhou, M., Li, M. (eds) Software Engineering and Methodology for Emerging Domains. NASAC NASAC 2017 2018. Communications in Computer and Information Science, vol 861. Springer, Singapore. https://doi.org/10.1007/978-981-15-0310-8_7

Download citation

  • DOI: https://doi.org/10.1007/978-981-15-0310-8_7

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-0309-2

  • Online ISBN: 978-981-15-0310-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Societies and partnerships

Search

Navigation