research-article

Metric based testability model for object oriented design (MTMOOD)

Authors:

K. MustafaAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 34, Issue 2

Pages 1 - 6

https://doi.org/10.1145/1507195.1507204

Published: 28 February 2009 Publication History

Abstract

This paper does an extensive review on testability of object oriented software, and put forth some relevant information about class-level testability. Testability has been identified as a key factor to software quality, and emphasis is being drawn to predict class testability early in the software development life cycle. A Metrics Based Model for Object Oriented Design Testability (MTMOOD) has been proposed. The relationship from design properties to testability is weighted in accordance with its anticipated influence and importance. A suit of adequate object-oriented metrics useful in determining testability of a system has been proposed, which may be used to locate parts of design that could be error prone. Identification of changes in theses parts early could significantly improve the quality of the final product and hence decrease the testing effort. The proposed model has been further empirically validated and contextual interpretation has been drawn using industrial software projects.

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Cited By

Parsa SZakeri-Nasrabadi MTurhan B(2025)Testability-driven developmentComputer Standards & Interfaces10.1016/j.csi.2024.10387791:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.csi.2024.103877
Guglielmo LMariani LDenaro G(2024)Measuring Software Testability via Automatically Generated Test CasesIEEE Access10.1109/ACCESS.2024.339662512(63904-63916)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3396625
Zakeri-Nasrabadi MParsa S(2024)Natural language requirements testability measurement based on requirement smellsNeural Computing and Applications10.1007/s00521-024-09730-x36:21(13051-13085)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00521-024-09730-x
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Index Terms

Metric based testability model for object oriented design (MTMOOD)
1. General and reference
  1. Cross-computing tools and techniques
    1. Metrics
2. Software and its engineering
  1. Software creation and management
    1. Software development techniques
      1. Object oriented development
    2. Software verification and validation
      1. Software defect analysis
        Software testing and debugging
  2. Software notations and tools
    1. Development frameworks and environments
      1. Object oriented frameworks

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Published In

cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 34, Issue 2

March 2009

140 pages

ISSN:0163-5948

DOI:10.1145/1507195

Issue’s Table of Contents

Copyright © 2009 Authors.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 28 February 2009

Published in SIGSOFT Volume 34, Issue 2

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Cited By

Parsa SZakeri-Nasrabadi MTurhan B(2025)Testability-driven developmentComputer Standards & Interfaces10.1016/j.csi.2024.10387791:COnline publication date: 1-Jan-2025
https://dl.acm.org/doi/10.1016/j.csi.2024.103877
Guglielmo LMariani LDenaro G(2024)Measuring Software Testability via Automatically Generated Test CasesIEEE Access10.1109/ACCESS.2024.339662512(63904-63916)Online publication date: 2024
https://doi.org/10.1109/ACCESS.2024.3396625
Zakeri-Nasrabadi MParsa S(2024)Natural language requirements testability measurement based on requirement smellsNeural Computing and Applications10.1007/s00521-024-09730-x36:21(13051-13085)Online publication date: 1-Jul-2024
https://dl.acm.org/doi/10.1007/s00521-024-09730-x
Sharma TGeorgiou SKechagia MGhaleb TSarro F(2023)Investigating developers’ perception on software testability and its effectsEmpirical Software Engineering10.1007/s10664-023-10373-028:5Online publication date: 13-Sep-2023
https://dl.acm.org/doi/10.1007/s10664-023-10373-0
Zakeri-Nasrabadi MParsa S(2022)An ensemble meta-estimator to predict source code testability▪Applied Soft Computing10.1016/j.asoc.2022.109562129:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.asoc.2022.109562
Zakeri‐Nasrabadi MParsa S(2022)Learning to predict test effectivenessInternational Journal of Intelligent Systems10.1002/int.2272237:8(4363-4392)Online publication date: 28-Jun-2022
https://dl.acm.org/doi/10.1002/int.22722
Nasrabadi MParsa S(2021)Learning to Predict Software Testability2021 26th International Computer Conference, Computer Society of Iran (CSICC)10.1109/CSICC52343.2021.9420548(1-5)Online publication date: 3-Mar-2021
https://doi.org/10.1109/CSICC52343.2021.9420548
Filho FLelli VSantos IAndrade R(2020)Correlations among Software Testability MetricsProceedings of the XIX Brazilian Symposium on Software Quality10.1145/3439961.3439972(1-10)Online publication date: 1-Dec-2020
https://dl.acm.org/doi/10.1145/3439961.3439972
Grano GTitov TPanichella SGall H(2019)Branch coverage prediction in automated testingJournal of Software: Evolution and Process10.1002/smr.215831:9Online publication date: 13-Oct-2019
https://dl.acm.org/doi/10.1002/smr.2158
Sharma RSaha A(2018)A Systematic Review of Software Testability Measurement Techniques2018 International Conference on Computing, Power and Communication Technologies (GUCON)10.1109/GUCON.2018.8675006(299-303)Online publication date: Sep-2018
https://doi.org/10.1109/GUCON.2018.8675006
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