Joint effect of team structure and software architecture in oss
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Mengru Zhao 7482645 Yiyi Dai 7067041. Joint Effect of Team Structure and Software Architecture in OSS. submitted to Professor Shervin Shirmohammadi in partial fulfillment of the requirements for the course ELG 5100. Introduction. What is OSS? Open source software Why OSS?

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Joint Effect of Team Structure and Software Architecture in OSS

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Joint effect of team structure and software architecture in oss

Mengru Zhao 7482645

Yiyi Dai 7067041

Joint Effect of Team Structure and Software Architecture in OSS

submitted to Professor Shervin Shirmohammadi in partial fulfillment of the requirements for the course ELG 5100


Introduction

Introduction

  • What is OSS?

    Open source software

  • Why OSS?

  • Self-organized

  • Allow a clear view of inner workings

  • How OSS?

    Coherent research Team structure - social

    Software architecture - technical

Mengru Zhao 7482645

Yiyi Dai 7067041 slide 2


Agenda

Agenda

  • Background

  • Hypotheses

  • Data Analysis and Result

  • Conclusion

  • Limitations and Future Research

  • Reference

Mengru Zhao 7482645

Yiyi Dai 7067041 slide 3


Background

Background

  • Role of Social & Technical

    “match”

    Inseparable role of organizational structure--Social

    task characteristics--Technical

  • Moderating effect of task characteristics on the causal

    pathway from organizational structure to work

    Performance.

  • Organizational structure may moderate the effect of

    task characteristics on work performance due to the

    endogeneityof software development task characteristics.

  • Equally important and mutually moderating roles

Mengru Zhao 7482645

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Background1

Background

  • Socio-Technical

  • Social-Development Team Structure

    Each collaboration network includes developers of a single

    OSS project as nodes and collaboration incidences on

    tasks of the same project as links

    Intraprojectnetwork is more relevant

    The basic unit of work is a file in the OSS CVS system

    (concurrent versioning system)

    Two commonly used measures: network size & network

    centralization

Mengru Zhao 7482645

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Background2

Background

2) Technical-Software Architecture

Structural interdependency: The strength of association

established by a connection from one module to another.

Past development activities

Mengru Zhao 7482645

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Background3

Background

  • Interaction Between Team Structure and Software

    Architecture

    Reters to the mutually moderating or mutually contingent

    relationship between team structure and software

    architecture in OSS development.

Mengru Zhao 7482645

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Hypotheses

Hypotheses

  • Hypotheses 1

    Collaboration network size and software structural

    interdependency mutually and positively moderate each

    other’s impact on OSS project performance.

    Software structural interdependency is higher

    impact of network size on project performance is

    more likely to be positive.

Mengru Zhao 7482645

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Hypotheses1

Hypotheses

  • Hypotheses 2

    Collaboration network centralization and software

    structural interdependency mutually and positively

    moderate each other’s impact on OSS project

    performance.

    Software structural interdependency is higher

    impact of network centralization on project

    performance is more likely to be positive

    Tendency for software structural interdependency to

    negatively affect can be strong in a team with a chain-like

    structure.

Mengru Zhao 7482645

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Data analysis and result

Data Analysis and Result

  • Data Collection

    Three key considerations

  • Detailed CVS information in the public domain;

  • Between Feb 2001 and Nov 2001;

  • At least ten developersin the collaboration network.

Mengru Zhao 7482645

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Data analysis and result1

Data Analysis and Result

  • Construct Operationalization

  • Collaboration Network Structure

    • The higher the value, the more centralized the network is.

  • Software Structural Interdependency

    • The average number of source code task files (CVS files) per folder in the CVS file tree, to measure software structural interdependency (SSI).

    • Capture both the total number of CVS files in an OSS project and CVS tree structure of the same project.

Mengru Zhao 7482645

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Data analysis and result2

Data Analysis and Result

  • OSS Development Performance

    • We choose the number of code commits per developer per day as our measure of OSS development performance.

    • Objective

Mengru Zhao 7482645

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Data analysis and result3

Data Analysis and Result

  • Control Variables

    • Product Size: LOC

    • Programming Language: 4 binary variances

    • License Type: GPL=1, others=0

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Data analysis and result4

Data Analysis and Result

  • Analysis

    Nonlinear relationship between project performance and network size and product size.

  • Results

    The ordinary least squares (OLS)

Mengru Zhao 7482645

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Data analysis and result5

Data Analysis and Result

Mengru Zhao 7482645

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Data analysis and result6

Data Analysis and Result

Mengru Zhao 7482645

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Data analysis and result7

Data Analysis and Result

H1 results

Fig. 1. Simple Slope of Network Size

Fig. 2. Simple Slope of SSI

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Data analysis and result8

Data Analysis and Result

H2 results

Fig. 3. Simple Slope of Centralization

Fig. 4. Simple Slope of SSI

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Conclusion

Conclusion

  • Research implication

    • IT properties and organization properties as equally important and tightly intertwined factors in work performance outcomes.

    • Conceptualize and empirically evaluate the role of socio-technical interactions in OSS projects.

  • Practical Implication

    • Gain the best of both worlds by adopting a hybrid software development process that incorporates strengths of traditional software development model and OSS model.

Mengru Zhao 7482645

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Conclusion1

Conclusion

  • Self-organized OSS development process jointly enacted by developer behaviors and project characteristics.

Mengru Zhao 7482645

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Limitations and future research

Limitations and Future Research

  • Gain analytical tractability, we employ a surrogate measure of software structural interdependency.

  • Based our analysis on the dataset collected from the CVS archives of the OSS projects.

  • Code commits do not reflect quality of code changes.

  • Team structure measures are extracted from CVS files.

Mengru Zhao 7482645

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Reference

Reference

  • [1] Nakagawa, E.Y.; de Sousa, E.P.M.; de Brito Murata, K.; de FariaAndery, G.; Morelli, L.B.; Maldonado, J.C., "Software Architecture Relevance in Open Source Software Evolution: A Case Study," Computer Software and Applications, 2008. COMPSAC '08. 32nd Annual IEEE International , pp.1234,1239, July 28 2008-Aug. 1 2008;

  • [2] Badri, M.; Drouin, N.; Toure, F., "On understanding software quality evolution from a defect perspective: A case study on an open source software system," Computer Systems and Industrial Informatics (ICCSII), 2012 International Conference, pp.1,6, 18-20 Dec. 2012;

  • [3] Krishna, V.; Basu, A., "Software Architecture for large/critical applications," Software Engineering (CONSEG), 2012 CSI Sixth International Conference, pp.1,4, 5-7 Sept. 2012;

  • [4] Petrov, P.; Buy, U.; Nord, R.L., "Enhancing the software architecture analysis and design process with inferred macro-architectural requirements," Twin Peaks of Requirements and Architecture (Twin Peaks), 2012 IEEE First International Workshop, pp.20,26, 25-25 Sept. 2012

  • [5] Ning Nan; Kumar, S., "Joint Effect of Team Structure and Software Architecture in Open Source Software Development," Engineering Management, IEEE Transactions, vol.60, no.3, pp.592,603, Aug. 2013----main reference

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Thank you

THANK YOU!


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