research-article

An empirical study of system design instability metric and design evolution in an agile software process

Authors:

Mohammad Alshayeb,

Wei LiAuthors Info & Claims

Journal of Systems and Software, Volume 74, Issue 3

Pages 269 - 274

https://doi.org/10.1016/j.jss.2004.02.002

Published: 01 February 2005 Publication History

Abstract

Software project tracking and project plan adjustment are two important software engineering activities. The class growth shows the design evolution of the software. The System Design Instability (SDI) metric indicates the progress of an object-oriented (OO) project once the project is set in motion. The SDI metric provides information on project evolution to project managers for possible adjustment to the project plan. The objectives of this paper are to test if the System Design Instability metric can be used to estimate and re-plan software projects in an XP-like agile process and study system design evolution in the Agile software process. We present an empirical study of the class growth and the SDI metric in two OO systems, developed using an agile process similar to Extreme Programming (XP). We analyzed the system evolutionary data collected on a daily basis from the two systems. We concluded that: the systems' class growth follows observable trends, the SDI metric can indicate project progress with certain trends, and the SDI metric is correlated with XP activities. In both of the analyzed systems, we observed two consistent jumps in the SDI metric values in early and late development phases. Part of the results agrees with a previous empirical study in another environment.

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Cited By

Capilla RSalamanca VValdezate ARobles G(2024)Can instability variations warn developers when open-source projects boost?Empirical Software Engineering10.1007/s10664-024-10482-429:4Online publication date: 14-Jun-2024
https://dl.acm.org/doi/10.1007/s10664-024-10482-4
Chloros DGerogiannis VKakarontzas G(2022)Use of software and project management metrics in agile software development methodologiesProceedings of the 2022 European Symposium on Software Engineering10.1145/3571697.3571701(25-32)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1145/3571697.3571701
Salama MBahsoon RLago P(2021)Stability in Software Engineering: Survey of the State-of-the-Art and Research DirectionsIEEE Transactions on Software Engineering10.1109/TSE.2019.292561647:7(1468-1510)Online publication date: 16-Jul-2021
https://dl.acm.org/doi/10.1109/TSE.2019.2925616
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Index Terms

An empirical study of system design instability metric and design evolution in an agile software process
1. Social and professional topics
  1. Professional topics
    1. Management of computing and information systems
      1. Project and people management
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods
        Rapid application development

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cover image Journal of Systems and Software

Journal of Systems and Software Volume 74, Issue 3

February 2005

108 pages

ISSN:0164-1212

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Copyright © Elsevier Inc.

Publisher

Elsevier Science Inc.

United States

Publication History

Published: 01 February 2005

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Cited By

Capilla RSalamanca VValdezate ARobles G(2024)Can instability variations warn developers when open-source projects boost?Empirical Software Engineering10.1007/s10664-024-10482-429:4Online publication date: 14-Jun-2024
https://dl.acm.org/doi/10.1007/s10664-024-10482-4
Chloros DGerogiannis VKakarontzas G(2022)Use of software and project management metrics in agile software development methodologiesProceedings of the 2022 European Symposium on Software Engineering10.1145/3571697.3571701(25-32)Online publication date: 27-Oct-2022
https://dl.acm.org/doi/10.1145/3571697.3571701
Salama MBahsoon RLago P(2021)Stability in Software Engineering: Survey of the State-of-the-Art and Research DirectionsIEEE Transactions on Software Engineering10.1109/TSE.2019.292561647:7(1468-1510)Online publication date: 16-Jul-2021
https://dl.acm.org/doi/10.1109/TSE.2019.2925616
Abuhassan AAlshayeb M(2019)A metrics suite for UML model stabilitySoftware and Systems Modeling (SoSyM)10.1007/s10270-016-0573-618:1(557-583)Online publication date: 1-Feb-2019
https://dl.acm.org/doi/10.1007/s10270-016-0573-6
Hussain SShin SShin DLencastre M(2017)A methodology to predict the instable classesProceedings of the Symposium on Applied Computing10.1145/3019612.3019927(1307-1308)Online publication date: 3-Apr-2017
https://dl.acm.org/doi/10.1145/3019612.3019927
(2017)On tackling quality threats for the assessment of measurement programsScience of Computer Programming10.1016/j.scico.2016.09.006135:C(45-74)Online publication date: 15-Feb-2017
https://dl.acm.org/doi/10.1016/j.scico.2016.09.006
de Oliveira MBonifácio RRamos GRibeiro MFuentes LBatory DCzarnecki K(2016)Unveiling and reasoning about co-change dependenciesProceedings of the 15th International Conference on Modularity10.1145/2889443.2889450(25-36)Online publication date: 14-Mar-2016
https://dl.acm.org/doi/10.1145/2889443.2889450
Staron MMeding W(2016)MeSRAM - A method for assessing robustness of measurement programs in large software development organizations and its industrial evaluationJournal of Systems and Software10.1016/j.jss.2015.10.051113:C(76-100)Online publication date: 1-Mar-2016
https://dl.acm.org/doi/10.1016/j.jss.2015.10.051
Chen JXiao JWang QOsterweil LLi M(2016)Perspectives on refactoring planning and practiceEmpirical Software Engineering10.1007/s10664-015-9390-821:3(1397-1436)Online publication date: 1-Jun-2016
https://dl.acm.org/doi/10.1007/s10664-015-9390-8
Rufiange SFuhrman C(2014)Visualizing protected variations in evolving software designsJournal of Systems and Software10.5555/2747015.274718288:C(231-249)Online publication date: 1-Feb-2014
https://dl.acm.org/doi/10.5555/2747015.2747182
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