nach oben

Empirical Software Engineering

Erschienen in:

01.01.2022

Developers perception of peer code review in research software development

verfasst von: Nasir U. Eisty, Jeffrey C. Carver

Erschienen in: Empirical Software Engineering | Ausgabe 1/2022

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Context

Research software is software developed by and/or used by researchers, across a wide variety of domains, to perform their research. Because of the complexity of research software, developers cannot conduct exhaustive testing. As a result, researchers have lower confidence in the correctness of the output of the software. Peer code review, a standard software engineering practice, has helped address this problem in other types of software.

Objective

Peer code review is less prevalent in research software than it is in other types of software. In addition, the literature does not contain any studies about the use of peer code review in research software. Therefore, through analyzing developers perceptions, the goal of this work is to understand the current practice of peer code review in the development of research software, identify challenges and barriers associated with peer code review in research software, and present approaches to improve the peer code review in research software.

Method

We conducted interviews and a community survey of research software developers to collect information about their current peer code review practices, difficulties they face, and how they address those difficulties.

Results

We received 84 unique responses from the interviews and surveys. The results show that while research software teams review a large amount of their code, they lack formal process, proper organization, and adequate people to perform the reviews.

Conclusions

Use of peer code review is promising for improving the quality of research software and thereby improving the trustworthiness of the underlying research results. In addition, by using peer code review, research software developers produce more readable and understandable code, which will be easier to maintain.

Vorheriger Artikel How do i refactor this? An empirical study on refactoring trends and topics in Stack Overflow

Nächster Artikel Quick remedy commits and their impact on mining software repositories

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

http://www.ncsa.illinois.edu/Conferences/ETK17/

https://www.qualtrics.com/

https://se4science.github.io/SE-CODESE17/

Ackerman AF, Buchwald LS, Lewski FH (1989) Software inspections: an effective verification process. IEEE Softw 6(3):31–36. https://doi.org/10.1109/52.28121CrossRef

Bacchelli A, Bird C (2013) Expectations, outcomes, and challenges of modern code review. In: Proceedings of the 2013 international conference on software engineering, ICSE ’13. IEEE Press, Piscataway, pp 712–721. http://dl.acm.org/citation.cfm?id=2486788.2486882

Beller M, Bacchelli A, Zaidman A, Juergens E (2014a) Modern code reviews in open-source projects: Which problems do they fix?. In: Proceedings of the 11th working conference on mining software repositories, MSR 2014. Association for Computing Machinery, New York, pp 202–211. https://doi.org/10.1145/2597073.2597082

Beller M, Bacchelli A, Zaidman A, Juergens E (2014b) Modern code reviews in open-source projects: Which problems do they fix?. In: Proceedings of the 11th working conference on mining software repositories, MSR 2014. ACM, New York. https://doi.org/10.1145/2597073.2597082, pp 202–211

Bosu A, Carver JC (2013) Impact of peer code review on peer impression formation: A survey. In: 2013 ACM/IEEE international symposium on empirical software engineering and measurement. https://doi.org/10.1109/ESEM.2013.23, pp 133–142

Bosu A, Carver J, Guadagno R, Bassett B, McCallum D, Hochstein L (2014) Peer impressions in open source organizations: A survey. J Syst Softw 94:4–15. https://doi.org/10.1016/j.jss.2014.03.061. http://www.sciencedirect.com/science/article/pii/S0164121214000818CrossRef

Bosu A, Greiler M, Bird C (2015) Characteristics of useful code reviews: An empirical study at microsoft. In: 2015 IEEE/ACM 12th working conference on mining software repositories. https://doi.org/10.1109/MSR.2015.21, pp 146–156

Bosu A, Carver JC, Bird C, Orbeck J, Chockley C (2017) Process aspects and social dynamics of contemporary code review: Insights from open source development and industrial practice at microsoft. IEEE Trans Softw Eng 43(1):56–75CrossRef

Carver J, Chue Hong N, Thiruvathukal G (2016) Software engineering for science. CRC Press, Boca RatonCrossRef

Carver JC (2008) Se-cse 2008: The first international workshop on software engineering for computational science and engineering. In: Companion of the 30th international conference on software engineering, ICSE Companion ’08. Association for Computing Machinery, New York, pp 1071–1072. https://doi.org/10.1145/1370175.1370252

Carver JC, Eisty N (2021) Data set from survey on peer code review in research software. https://doi.org/10.6084/m9.figshare.14736468. https://figshare.com/articles/dataset/_/14736468/0

Ciolkowski M, Laitenberger O, Biffl S (2003) Software reviews, the state of the practice. IEEE Softw 20(6):46–51. https://doi.org/10.1109/MS.2003.1241366CrossRef

Clune T, Rood R (2011) Software testing and verification in climate model development. IEEE Softw 28(6):49–55. 10.1109/MS.2011.117CrossRef

Eisty NU, Thiruvathukal GK, Carver JC (2018) A survey of software metric use in research software development. In: 2018 IEEE 14th international conference on e-Science (e-Science), pp 212–222

Eisty NU, Thiruvathukal GK, Carver JC (2019) Use of software process in research software development: A survey. In: Proceedings of the evaluation and assessment on software engineering, EASE ’19. ACM, New York. https://doi.org/10.1145/3319008.3319351., pp 276–282

Fagan ME (1976) Design and code inspections to reduce errors in program development. IBM Syst J 15(3):182–211. 10.1147/sj.153.0182CrossRef

Faulk S, Loh E, Vanter MLVD, Squires S, Votta LG (2009) Scientific computing’s productivity gridlock: How software engineering can help. Comput Sci Eng 11(6):30–39CrossRef

Hannay JE, MacLeod C, Singer J, Langtangen HP, Pfahl D, Wilson G (2009) How do scientists develop and use scientific software?. In: 2009 ICSE workshop on software engineering for computational science and engineering. https://doi.org/10.1109/SECSE.2009.5069155, pp 1–8

Heaton D, Carver JC (2015) Claims about the use of software engineering practices in science: A systematic literature review. Inform Softw Technol 67:207–219. https://doi.org/10.1016/j.infsof.2015.07.011. http://www.sciencedirect.com/science/article/pii/S0950584915001342CrossRef

Hook D, Kelly D (2009) Testing for trustworthiness in scientific software. In: 2009 ICSE workshop on soft. eng. for computational science and eng. https://doi.org/10.1109/SECSE.2009.5069163, pp 59–64

Kanewala U, Bieman JM (2014) Testing scientific software: A systematic literature review. Inf Softw Technol 56(10):1219–1232. https://doi.org/10.1016/j.infsof.2014.05.006. http://www.sciencedirect.com/science/article/pii/S0950584914001232CrossRef

Mantyla MV, Lassenius C (2009) What types of defects are really discovered in code reviews? IEEE Trans Softw Eng 35(3):430–448. https://doi.org/10.1109/TSE.2008.71CrossRef

McIntosh S, Kamei Y, Adams B, Hassan AE (2014) The impact of code review coverage and code review participation on software quality: A case study of the qt, vtk, and itk projects. In: Proceedings of the 11th working conference on mining software repositories, MSR 2014. Association for Computing Machinery, New York. https://doi.org/10.1145/2597073.2597076, pp 192–201

Morales R, McIntosh S, Khomh F (2015) Do code review practices impact design quality? a case study of the qt, vtk, and itk projects. In: 2015 IEEE 22nd international conference on software analysis, evolution, and reengineering (SANER). https://doi.org/10.1109/SANER.2015.7081827, pp 171–180

Nangia U, Katz DS (2017) Track 1 paper: Surveying the u.s. national postdoctoral association regarding software use and training in research. https://doi.org/10.6084/m9.figshare.5328442.v3. https://figshare.com/articles/Track_1_Paper_Surveying_the_U_S_National_Postdoctoral_Association_Regarding_Software_Use_and_Training_in_Research/5328442/3

Petre M, Wilson G (2014) Code review for and by scientists. In: Proc. 2nd workshop on sustainable software for science: practice and experience

Potvin R, Levenberg J (2016) Why google stores billions of lines of code in a single repository. Commun ACM 59(7):78–87. https://doi.org/10.1145/2854146CrossRef

Remmel H, Paech B, Bastian P, Engwer C (2012) System testing a scientific framework using a regression-test environment. Comput Sci Eng 14(2):38–45CrossRef

Rigby P, Cleary B, Painchaud F, Storey M, German D (2012) Contemporary peer review in action: Lessons from open source development. IEEE Softw 29(6):56–61. https://doi.org/10.1109/MS.2012.24CrossRef

Rigby PC, German DM, Storey MA (2008) Open source software peer review practices: A case study of the apache server. In: Proceedings of the 30th international conference on software engineering, ICSE ’08. ACM, New York. https://doi.org/10.1145/1368088.1368162., pp 541–550

Sadowski C, Söderberg E, Church L, Sipko M, Bacchelli A (2018) Modern code review: A case study at google. In: Proceedings of the 40th international conference on software engineering: software engineering in practice, ICSE-SEIP ’18. ACM, New York. https://doi.org/10.1145/3183519.3183525., pp 181–190

Sanders R, Kelly D (2008) Dealing with risk in scientific software development. IEEE Softw 25(4):21–28CrossRef

Segal J (2005) When software engineers met research scientists: A case study. Empir Softw Eng 10. https://doi.org/10.1007/s10664-005-3865-y

Segal J (2009) Some challenges facing software engineers developing software for scientists. In: 2009 ICSE workshop on software engineering for computational science and engineering. pp 9–14

Sutherland A, Venolia G (2009) Can peer code reviews be exploited for later information needs?. In: 2009 31st international conference on software engineering - companion volume. https://doi.org/10.1109/ICSE-COMPANION.2009.5070996, pp 259–262

Vilkomir SA, Swain WT, Poore JH, Clarno KT (2008) Modeling input space for testing scientific computational software: A case study. In: Bubak M, van Albada GD, Dongarra J, Sloot PMA (eds) Computational science – ICCS 2008. Springer, Berlin, pp 291–300

Titel: Developers perception of peer code review in research software development
verfasst von: Nasir U. Eisty
Jeffrey C. Carver
Publikationsdatum: 01.01.2022
Verlag: Springer US
Erschienen in: Empirical Software Engineering / Ausgabe 1/2022
Print ISSN: 1382-3256
Elektronische ISSN: 1573-7616
DOI: https://doi.org/10.1007/s10664-021-10053-x

Springer Professional

Abstract

Context

Objective

Method

Results

Conclusions

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Springer Professional "Wirtschaft+Technik"

Weitere Artikel der Ausgabe 1/2022

Enjoy your observability: an industrial survey of microservice tracing and analysis

On the analysis of non-coding roles in open source development

Correction to: Preface to the special issue on program comprehension

An empirical study of developers’ discussions about security challenges of different programming languages

Efficient static analysis and verification of featured transition systems

GitHub Discussions: An exploratory study of early adoption

Premium Partner