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A new approach for software testability analysis

Published: 28 May 2006 Publication History

Abstract

Software testability analysis has been an important research direction since 1990s and becomes more pervasive when entering 21st century. In this paper, we summarize problems in existing research work. We propose to use beta distribution to indicate software testability. When incorporating testing effectiveness information, we theoretically prove that the distribution can express testing effort and test value at the same time. We conduct experiment and validate our results on Siemens programs. Future work concentrate on deducing a prior estimation of the distribution for given software and testing criterion pair from program slicing and semantic analysis.

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  • (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
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cover image ACM Conferences
ICSE '06: Proceedings of the 28th international conference on Software engineering
May 2006
1110 pages
ISBN:1595933751
DOI:10.1145/1134285
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 ACM 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]

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Published: 28 May 2006

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Author Tags

  1. beta distribution
  2. measure
  3. software testability
  4. testing effectiveness

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Cited By

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  • (2024)Measuring Software Testability via Automatically Generated Test CasesIEEE Access10.1109/ACCESS.2024.339662512(63904-63916)Online publication date: 2024
  • (2023)Investigating developers’ perception on software testability and its effectsEmpirical Software Engineering10.1007/s10664-023-10373-028:5Online publication date: 13-Sep-2023
  • (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
  • (2018)Predicting different levels of the unit testing effort of classes using source code metricsInnovations in Systems and Software Engineering10.1007/s11334-017-0306-114:1(15-46)Online publication date: 1-Mar-2018
  • (2016)An estimation of software testability using fuzzy logic2016 6th International Conference - Cloud System and Big Data Engineering (Confluence)10.1109/CONFLUENCE.2016.7508094(95-100)Online publication date: Jan-2016
  • (2016)Analyzing defect inflow distribution and applying Bayesian inference method for software defect prediction in large software projectsJournal of Systems and Software10.1016/j.jss.2016.02.015117:C(229-244)Online publication date: 1-Jul-2016
  • (2015)Metric Based Testability Estimation Model for Object Oriented Design: Quality PerspectiveJournal of Software Engineering and Applications10.4236/jsea.2015.8402408:04(234-243)Online publication date: 2015
  • (2015)Predicting Unit Testing Effort Levels of Classes: An Exploratory Study based on Multinomial Logistic Regression ModelingProcedia Computer Science10.1016/j.procs.2015.08.52862(529-538)Online publication date: 2015
  • (2012)Empirical Analysis of Object-Oriented Design Metrics for Predicting Unit Testing Effort of ClassesJournal of Software Engineering and Applications10.4236/jsea.2012.5706005:07(513-526)Online publication date: 2012
  • (2012)Evaluating the effect of control flow on the unit testing effort of classesAdvances in Software Engineering10.1155/2012/9640642012(5-5)Online publication date: 1-Jan-2012
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