research-article

Software developers' perceptions of productivity

Authors:

André N. Meyer,

Gail C. Murphy,

Thomas ZimmermannAuthors Info & Claims

FSE 2014: Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering

Pages 19 - 29

https://doi.org/10.1145/2635868.2635892

Published: 11 November 2014 Publication History

Abstract

The better the software development community becomes at creating software, the more software the world seems to demand. Although there is a large body of research about measuring and investigating productivity from an organizational point of view, there is a paucity of research about how software developers, those at the front-line of software construction, think about, assess and try to improve their productivity. To investigate software developers' perceptions of software development productivity, we conducted two studies: a survey with 379 professional software developers to help elicit themes and an observational study with 11 professional software developers to investigate emergent themes in more detail. In both studies, we found that developers perceive their days as productive when they complete many or big tasks without significant interruptions or context switches. Yet, the observational data we collected shows our participants performed significant task and activity switching while still feeling productive. We analyze such apparent contradictions in our findings and use the analysis to propose ways to better support software developers in a retrospection and improvement of their productivity through the development of new tools and the sharing of best practices.

References

[1]

www.ifi.uzh.ch/seal/people/meyer/developersproductivity.

[2]

M. Andreessen. Why software is eating the world. The Wall Street Journal, August 20, 2011.

[3]

K. Beck and C. Andres. Extreme programming explained: embrace change. Addison-Wesley, 2004.

Digital Library

[4]

A. Begel and B. Simon. Novice software developers, all over again. In Proceedings of the Fourth International Workshop on Computing Education Research, ICER ’08, pages 3–14. ACM, 2008.

Digital Library

[5]

J. Blackburn, G. Scudder, and L. Van Wassenhove. Improving speed and productivity of software development: a global survey of software developers. IEEE Transactions on Software Engineering, 22(12):875–885, 1996.

Digital Library

[6]

B. W. Boehm. Improving software productivity. volume 20, pages 43–57. IEEE, 1987.

Digital Library

[7]

D. M. Bravata, C. Smith-Spangler, V. Sundaram, A. L. Gienger, N. Lin, R. Lewis, C. D. Stave, I. Olkin, and J. R. Sirard. Using pedometers to increase physical activity and improve health: A systematic review. Jama, 298(19):2296–2304, 2007.

[8]

D. N. Card. The Challenge of Productivity Measurements. In Pacific Northwest Software Quality Conference, pages 1–10, 2006.

[9]

M. Cataldo, J. D. Herbsleb, and K. M. Carley. Socio-technical congruence: A framework for assessing the impact of technical and work dependencies on software development productivity. In Proceedings of the Second ACM-IEEE International Symposium on Empirical Software Engineering and Measurement, ESEM ’08, pages 2–11. ACM, 2008.

Digital Library

[10]

S. Consolvo, P. Klasnja, D. W. McDonald, and J. A. Landay. Goal-setting considerations for persuasive technologies that encourage physical activity. In Proceedings of the 4th international Conference on Persuasive Technology, pages 8:1–8:8. ACM, 2009.

Digital Library

[11]

S. Consolvo, D. W. McDonald, T. Toscos, M. Y. Chen, J. Froehlich, B. Harrison, P. Klasnja, A. LaMarca, L. LeGrand, R. Libby, et al. Activity sensing in the wild: a field trial of ubifit garden. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pages 1797–1806. ACM, 2008.

Digital Library

[12]

L. Dabbish, G. Mark, and V. M. González. Why do i keep interrupting myself?: Environment, habit and self-interruption. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’11, pages 3127–3130. ACM, 2011.

Digital Library

[13]

C. R. B. de Souza and D. F. Redmiles. An empirical study of software developers’ management of dependencies and changes. In Proceedings of the 30th International Conference on Software Engineering, ICSE ’08, pages 241–250. ACM, 2008.

Digital Library

[14]

T. DeMarco and T. Lister. Programmer performance and the effects of the workplace. In Proceedings of the 8th International Conference on Software Engineering, ICSE ’85, pages 268–272. IEEE, 1985.

Digital Library

[15]

P. Devanbu, S. Karstu, W. Melo, and W. Thomas. Analytical and empirical evaluation of software reuse metrics. In Proceedings of the 18th International Conference on Software Engineering, ICSE ’96, pages 189–199. IEEE, 1996.

Digital Library

[16]

E. W. Dijkstra. The humble programmer. Communications of the ACM, 15(10):859–866, 1972.

Digital Library

[17]

B. J. Fogg. Persuasive technology: Using computers to change what we think and do. Ubiquity, 2002:5, 2002.

Digital Library

[18]

T. Fritz, E. M. Huan, G. C. Murphy, and T. Zimmermann. Persuasive technology in the real world: A study of long-term use of activity sensing devices for fitness. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2014. to appear.

Digital Library

[19]

W. Gibbs. Software’s chronic crisis. Scientific American, 271(3):86–94, 1994.

[20]

V. M. González and G. Mark. ”constant, constant, multi-tasking craziness”: Managing multiple working spheres. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI ’04, pages 113–120. ACM, 2004.

Digital Library

[21]

H. Hulkko and P. Abrahamsson. A multiple case study on the impact of pair programming on product quality. In Proceedings of the 27th International Conference on Software Engineering, ICSE ’05, pages 495–504. ACM, 2005.

Digital Library

[22]

W. S. Humphrey. Introduction to the Personal Software Process. Addison-Wesley Professional, first edition, 1996.

Digital Library

[23]

W. S. Humphrey. Using a defined and measured personal software process. IEEE, 13(3):77–88, 1996.

Digital Library

[24]

P. M. Johnson, H. Kou, J. Agustin, C. Chan, C. Moore, J. Miglani, S. Zhen, and W. E. J. Doane. Beyond the personal software process: Metrics collection and analysis for the differently disciplined. In Proceedings of the 25th International Conference on Software Engineering, ICSE ’03, pages 641–646. IEEE, 2003.

Digital Library

[25]

C. Jones. Software metrics: good, bad and missing. Computer, 27(9):98–100, 1994.

Digital Library

[26]

D. Kamma and P. Jalote. Effect of task processes on programmer productivity in model-based testing. In Proceedings of the 6th India Software Engineering Conference, ISEC ’13, pages 23–28. ACM, 2013.

Digital Library

[27]

M. Kersten and G. C. Murphy. Using task context to improve programmer productivity. In Proceedings of the 14th ACM SIGSOFT International Symposium on Foundations of Software Engineering, SIGSOFT ’06/FSE-14, pages 1–11. ACM, 2006.

Digital Library

[28]

R. B. Kieburtz, L. McKinney, J. M. Bell, J. Hook, A. Kotov, J. Lewis, D. P. Oliva, T. Sheard, I. Smith, and L. Walton. A software engineering experiment in software component generation. In Proceedings of the 18th International Conference on Software Engineering, ICSE ’96, pages 542–552. IEEE, 1996.

Digital Library

[29]

A. J. Ko, R. DeLine, and G. Venolia. Information needs in collocated software development teams. In Proceedings of the 29th International Conference on Software Engineering, ICSE ’07, pages 344–353. IEEE, 2007.

Digital Library

[30]

J. A. Lane and D. Zubrow. Integrating measurement with improvement: An action-oriented approach: Experience report. In Proceedings of the 19th International Conference on Software Engineering, ICSE ’97, pages 380–389. ACM, 1997.

Digital Library

[31]

H. Mintzberg. The nature of managerial work. Theory of management policy series. Prentice-Hall, 1980.

[32]

A. Mockus, R. T. Fielding, and J. D. Herbsleb. Two case studies of open source software development: Apache and mozilla. ACM Transactions on Software Engineering and Methodology, 11(3):309–346, 2002.

Digital Library

[33]

S. Munson. Mindfulness, reflection, and persuasion in personal informatics. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2012.

[34]

P. Naur and B. Randell. Software engineering: Report of a conference sponsored by the nato science committee. Scientific Affairs Division, NATO, 1969.

[35]

V. Nguyen, L. Huang, and B. Boehm. An analysis of trends in productivity and cost drivers over years. In Proceedings of the 7th International Conference on Predictive Models in Software Engineering, Promise ’11, pages 3:1–3:10. ACM, 2011.

Digital Library

[36]

D. E. Perry, N. A. Staudenmayer, and L. G. Votta. People, organizations, and process improvement. Software, IEEE, 11(4):36–45, 1994.

Digital Library

[37]

O. U. Press. Oxford dictionary. www.oxforddictionaries.com/us/definition/american english/productivity.

[38]

T. Roehm, R. Tiarks, R. Koschke, and W. Maalej. How do professional developers comprehend software? In Proceedings of the 2012 International Conference on Software Engineering, ICSE 2012, pages 255–265. IEEE, 2012.

Digital Library

[39]

J. Sillito, G. C. Murphy, and K. De Volder. Questions programmers ask during software evolution tasks. In Proceedings of the 14th ACM SIGSOFT International Symposium on Foundations of Software Engineering, SIGSOFT ’06/FSE-14, pages 23–34. ACM, 2006.

Digital Library

[40]

S. Wagner, M. Ruhe, and A. Siemens. A systematic review of productivity factors in software development, 2008.

[41]

M. Zhou and A. Mockus. Developer fluency: Achieving true mastery in software projects. In Proceedings of the Eighteenth ACM SIGSOFT International Symposium on Foundations of Software Engineering, FSE ’10, pages 137–146. ACM, 2010.

Digital Library

Cited By

Murazvu GParkinson SKhan SLiu NAllen G(2024)A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis ApproachSoftware10.3390/software30100013:1(1-27)Online publication date: 2-Jan-2024
https://doi.org/10.3390/software3010001
Razzaq ABuckley JLai QYu TBotterweck G(2024)A Systematic Literature Review on the Influence of Enhanced Developer Experience on Developers' Productivity: Factors, Practices, and RecommendationsACM Computing Surveys10.1145/368729957:1(1-46)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3687299
Weber TBrandmaier MSchmidt AMayer S(2024)Significant Productivity Gains through Programming with Large Language ModelsProceedings of the ACM on Human-Computer Interaction10.1145/36611458:EICS(1-29)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3661145
Show More Cited By

Index Terms

Software developers' perceptions of productivity
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
2. Information systems
  1. Information systems applications

Recommendations

Understanding Personal Productivity: How Knowledge Workers Define, Evaluate, and Reflect on Their Productivity
CHI '19: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

Productivity tracking tools often determine productivity based on the time interacting with work-related applications. To deconstruct productivity's diverse and nebulous nature, we investigate how knowledge workers conceptualize personal productivity ...
Software Project Managers' Perceptions of Productivity Factors: Findings from a Qualitative Study
ESEM '16: Proceedings of the 10th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

Context -- Developers' productivity plays an important role in software development organizations; however, in many cases the management of such human capital is mainly based on how project managers perceive productivity. Therefore, it is important to ...
Characterizing software developers by perceptions of productivity
ESEM '17: Proceedings of the 11th ACM/IEEE International Symposium on Empirical Software Engineering and Measurement

Understanding developer productivity is important to deliver software on time and at reasonable cost. Yet, there are numerous definitions of productivity and, as previous research found, productivity means different things to different developers. In ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Conferences

FSE 2014: Proceedings of the 22nd ACM SIGSOFT International Symposium on Foundations of Software Engineering

November 2014

856 pages

ISBN:9781450330565

DOI:10.1145/2635868

General Chair:
Shing-Chi Cheung
Hong Kong University of Science and Technology, China
,
Program Chairs:
Alessandro Orso
Georgia Institute of Technology, USA
,
Margaret-Anne Storey
University of Victoria, Canada

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

Sponsors

SIGSOFT: ACM Special Interest Group on Software Engineering

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 November 2014

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Conference

SIGSOFT/FSE'14

Sponsor:

SIGSOFT

SIGSOFT/FSE'14: 22nd ACM SIGSOFT Symposium on the Foundations of Software Engineering

November 16 - 21, 2014

Hong Kong, China

Acceptance Rates

Overall Acceptance Rate 17 of 128 submissions, 13%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

142
Total Citations
View Citations
2,771
Total Downloads

Downloads (Last 12 months)419
Downloads (Last 6 weeks)58

Reflects downloads up to 18 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Murazvu GParkinson SKhan SLiu NAllen G(2024)A Survey on Factors Preventing the Adoption of Automated Software Testing: A Principal Component Analysis ApproachSoftware10.3390/software30100013:1(1-27)Online publication date: 2-Jan-2024
https://doi.org/10.3390/software3010001
Razzaq ABuckley JLai QYu TBotterweck G(2024)A Systematic Literature Review on the Influence of Enhanced Developer Experience on Developers' Productivity: Factors, Practices, and RecommendationsACM Computing Surveys10.1145/368729957:1(1-46)Online publication date: 7-Oct-2024
https://dl.acm.org/doi/10.1145/3687299
Weber TBrandmaier MSchmidt AMayer S(2024)Significant Productivity Gains through Programming with Large Language ModelsProceedings of the ACM on Human-Computer Interaction10.1145/36611458:EICS(1-29)Online publication date: 17-Jun-2024
https://dl.acm.org/doi/10.1145/3661145
Straubinger PFraser GDig DBryksin TGolubev YBezzubov A(2024)An IDE Plugin for Gamified Continuous IntegrationProceedings of the 1st ACM/IEEE Workshop on Integrated Development Environments10.1145/3643796.3648462(91-94)Online publication date: 20-Apr-2024
https://dl.acm.org/doi/10.1145/3643796.3648462
Russo DHanel PVan Berkel N(2024)Understanding Developers Well-Being and Productivity: A 2-year Longitudinal Analysis during the COVID-19 PandemicACM Transactions on Software Engineering and Methodology10.1145/363824433:3(1-44)Online publication date: 15-Mar-2024
https://dl.acm.org/doi/10.1145/3638244
Ziegler AKalliamvakou ELi XRice ARifkin DSimister SSittampalam GAftandilian E(2024)Measuring GitHub Copilot's Impact on ProductivityCommunications of the ACM10.1145/363345367:3(54-63)Online publication date: 22-Feb-2024
https://dl.acm.org/doi/10.1145/3633453
Hernandez RSong QKou YGui X(2024)"At the end of the day, I am accountable": Gig Workers' Self-Tracking for Multi-Dimensional Accountability ManagementProceedings of the 2024 CHI Conference on Human Factors in Computing Systems10.1145/3613904.3642151(1-20)Online publication date: 11-May-2024
https://dl.acm.org/doi/10.1145/3613904.3642151
Leinen FElsner DPretschner AStahlbauer ASailer MJürgens E(2024)Cost of Flaky Tests in Continuous Integration: An Industrial Case Study2024 IEEE Conference on Software Testing, Verification and Validation (ICST)10.1109/ICST60714.2024.00037(329-340)Online publication date: 27-May-2024
https://doi.org/10.1109/ICST60714.2024.00037
Guerra EIvo APereira FRobbes RJanes ASilveira F(2024)Impermanent identifiers: Enhanced source code comprehension and refactoringJournal of Systems and Software10.1016/j.jss.2024.112137216(112137)Online publication date: Oct-2024
https://doi.org/10.1016/j.jss.2024.112137
Azad NHyrynsalmi SSmolander K(2024)Understanding DevOps Critical Success Factors: A Thematic AnalysisDigital Product Management in the Era of Data Economy, Artificial Intelligence, and Ecosystems10.1007/978-3-031-71515-0_3(28-43)Online publication date: 16-Oct-2024
https://doi.org/10.1007/978-3-031-71515-0_3
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Media

Figures

Other

Tables

View Table of Contents