From Aristotle to Ringelmann: a large-scale analysis of team productivity and coordination in Open Source Software projects

被引:38
|
作者
Scholtes, Ingo [1 ]
Mavrodiev, Pavlin [1 ]
Schweitzer, Frank [1 ]
机构
[1] ETH, Chair Syst Design, Weinbergstr 56-58, CH-8092 Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
Software engineering; Repository mining; Productivity factors; Social aspects of software engineering; Open source software; Coordination; GROUP-SIZE; ECONOMIES; COMMIT;
D O I
10.1007/s10664-015-9406-4
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
Complex software development projects rely on the contribution of teams of developers, who are required to collaborate and coordinate their efforts. The productivity of such development teams, i.e., how their size is related to the produced output, is an important consideration for project and schedule management as well as for cost estimation. The majority of studies in empirical software engineering suggest that - due to coordination overhead - teams of collaborating developers become less productive as they grow in size. This phenomenon is commonly paraphrased as Brooks' law of software project management, which states that "adding manpower to a software project makes it later". Outside software engineering, the non-additive scaling of productivity in teams is often referred to as the Ringelmann effect, which is studied extensively in social psychology and organizational theory. Conversely, a recent study suggested that in Open Source Software (OSS) projects, the productivity of developers increases as the team grows in size. Attributing it to collective synergetic effects, this surprising finding was linked to the Aristotelian quote that "the whole is more than the sum of its parts". Using a data set of 58 OSS projects with more than 580,000 commits contributed by more than 30,000 developers, in this article we provide a large-scale analysis of the relation between size and productivity of software development teams. Our findings confirm the negative relation between team size and productivity previously suggested by empirical software engineering research, thus providing quantitative evidence for the presence of a strong Ringelmann effect. Using fine-grained data on the association between developers and source code files, we investigate possible explanations for the observed relations between team size and productivity. In particular, we take a network perspective on developer-code associations in software development teams and show that the magnitude of the decrease in productivity is likely to be related to the growth dynamics of co-editing networks which can be interpreted as a first-order approximation of coordination requirements.
引用
收藏
页码:642 / 683
页数:42
相关论文
共 50 条
  • [1] From Aristotle to Ringelmann: a large-scale analysis of team productivity and coordination in Open Source Software projects
    Ingo Scholtes
    Pavlin Mavrodiev
    Frank Schweitzer
    [J]. Empirical Software Engineering, 2016, 21 : 642 - 683
  • [2] Team-external coordination in large-scale software development projects
    Sablis, Aivars
    Smite, Darja
    Moe, Nils
    [J]. JOURNAL OF SOFTWARE-EVOLUTION AND PROCESS, 2021, 33 (03)
  • [3] Software evolution in open source projects - a large-scale investigation
    Koch, Stefan
    [J]. JOURNAL OF SOFTWARE MAINTENANCE AND EVOLUTION-RESEARCH AND PRACTICE, 2007, 19 (06): : 361 - 382
  • [4] Aristotle vs. Ringelmann: On superlinear production in open source software
    Maillart, Thomas
    Sornette, Didier
    [J]. PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2019, 523 : 964 - 972
  • [5] A large-scale empirical exploration on refactoring activities in open source software projects
    Vassallo, Carmine
    Grano, Giovanni
    Palomba, Fabio
    Gall, Harald C.
    Bacchelli, Alberto
    [J]. SCIENCE OF COMPUTER PROGRAMMING, 2019, 180 : 1 - 15
  • [6] Productivity, Turnover, and Team Stability of Agile Teams in Open-Source Software Projects
    Scott, Ezequiel
    Charkie, Khaled Nimr
    Pfahl, Dietmar
    [J]. 2020 46TH EUROMICRO CONFERENCE ON SOFTWARE ENGINEERING AND ADVANCED APPLICATIONS (SEAA 2020), 2020, : 124 - 131
  • [7] Analyzing the State of Static Analysis: A Large-Scale Evaluation in Open Source Software
    Beller, Moritz
    Bholanath, Radjino
    McIntosh, Shane
    Zaidman, Andy
    [J]. 2016 IEEE 23RD INTERNATIONAL CONFERENCE ON SOFTWARE ANALYSIS, EVOLUTION, AND REENGINEERING (SANER), VOL 1, 2016, : 470 - 481
  • [8] Adaptation of large-scale open source software - An experience report
    Pizka, M
    [J]. CSMR 2004: EIGHTH EUROPEAN CONFERENCE ON SOFTWARE MAINTENANCE AND REENGINEERING, PROCEEDINGS, 2004, : 147 - 153
  • [9] COORDINATION OF MODELS IN SOFTWARE SYSTEMS FOR LARGE-SCALE WATER-RESOURCES PROJECTS
    BEREZNER, AS
    ERESHKO, FI
    [J]. WATER SUPPLY & MANAGEMENT, 1980, 4 (04): : 253 - 262
  • [10] A Method to Detect License Inconsistencies in Large-Scale Open Source Projects
    Wu, Yuhao
    Manabe, Yuki
    Kanda, Tetsuya
    German, Daniel M.
    Inoue, Katsuro
    [J]. 12TH WORKING CONFERENCE ON MINING SOFTWARE REPOSITORIES (MSR 2015), 2015, : 324 - 333