Article

Coupling-based class integration and test order

Authors:

Aynur Abdurazik,

Jeff OffuttAuthors Info & Claims

AST '06: Proceedings of the 2006 international workshop on Automation of software test

Pages 50 - 56

https://doi.org/10.1145/1138929.1138940

Published: 23 May 2006 Publication History

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Abstract

During component-based and object-oriented software development, software classes exhibit relationships that complicate integration, including method calls, inheritance, and aggregation. When classes are integrated and tested, an order of integration must be established. The difficulty arises when cyclic dependencies exist - the functionality that is used by the first class to be tested must be mimicked by creating "stubs" (sometimes called "mocks"), an expensive and error-prone operation. This problem is generally called the class integration and test order (CITO) problem, and solutions must be fully automated for integration and testing to proceed smoothly and efficiently. This paper describes new techniques and algorithms to solve the CITO problem. New results include improved edge weights that are derived from quantitative coupling measures to more precisely model the cost of stubbing, and the use of weights on nodes, allowing more information to be used. Also, a new algorithm for computing the integration and test orders is presented. The technique is compared with an existing approach with positive results.

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Cited By

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Li YZhang YDing YJiang SYuan G(2023)A class integration test order generation approach based on Sarsa algorithmAutomated Software Engineering10.1007/s10515-023-00406-931:1Online publication date: 13-Dec-2023
https://doi.org/10.1007/s10515-023-00406-9
Meng FWang YYu HZhu Z(2022)Devising optimal integration test orders using cost–benefit analysis基于成本收益分析的集成测试序列生成优化方法Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.210046623:5(692-714)Online publication date: 25-May-2022
https://doi.org/10.1631/FITEE.2100466
Zhang YJiang SDing YYuan GLiu JLu DQian J(2022)Generating Optimal Class Integration Test Orders Using Genetic AlgorithmsInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819402250030932:06(871-892)Online publication date: 11-Jun-2022
https://doi.org/10.1142/S0218194022500309
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Index Terms

Coupling-based class integration and test order
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Empirical software validation
      2. Software defect analysis
        Software testing and debugging
  2. Software organization and properties
    1. Software functional properties
      1. Formal methods

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Information & Contributors

Information

Published In

AST '06: Proceedings of the 2006 international workshop on Automation of software test

May 2006

128 pages

ISBN:1595934081

DOI:10.1145/1138929

Conference Chair:
Hong Zhu
Oxford Brookes University, UK
,
Program Chairs:
Joseph R. Horgan
Telcordia Technologies, USA
,
S. C. Cheung
The Hong Kong University of Science and Technology, Hong Kong
,
J. Jenny Li
Avaya Labs, USA

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 23 May 2006

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ICSE06

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ICSE06: International Conference on Software Engineering

May 23, 2006

Shanghai, China

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Cited By

View all

Li YZhang YDing YJiang SYuan G(2023)A class integration test order generation approach based on Sarsa algorithmAutomated Software Engineering10.1007/s10515-023-00406-931:1Online publication date: 13-Dec-2023
https://doi.org/10.1007/s10515-023-00406-9
Meng FWang YYu HZhu Z(2022)Devising optimal integration test orders using cost–benefit analysis基于成本收益分析的集成测试序列生成优化方法Frontiers of Information Technology & Electronic Engineering10.1631/FITEE.210046623:5(692-714)Online publication date: 25-May-2022
https://doi.org/10.1631/FITEE.2100466
Zhang YJiang SDing YYuan GLiu JLu DQian J(2022)Generating Optimal Class Integration Test Orders Using Genetic AlgorithmsInternational Journal of Software Engineering and Knowledge Engineering10.1142/S021819402250030932:06(871-892)Online publication date: 11-Jun-2022
https://doi.org/10.1142/S0218194022500309
Jiang SZhang MZhang YWang RYu QKeung J(2021)An Integration Test Order Strategy to Consider Control CouplingIEEE Transactions on Software Engineering10.1109/TSE.2019.292196547:7(1350-1367)Online publication date: 1-Jul-2021
https://doi.org/10.1109/TSE.2019.2921965
Mukherjee DMall R(2019)An integration test coverage metric for Java programsInternational Journal of System Assurance Engineering and Management10.1007/s13198-019-00787-9Online publication date: 15-Jun-2019
https://doi.org/10.1007/s13198-019-00787-9
Mukherjee DShekhar DMall R(2018)Proposal for A Structural Integration Test Coverage Metric for Object-Oriented ProgramsACM SIGSOFT Software Engineering Notes10.1145/3178315.317833043:1(1-4)Online publication date: 28-Mar-2018
https://dl.acm.org/doi/10.1145/3178315.3178330
Czibula ICzibula GMarian Z(2018)Identifying Class Integration Test Order Using an Improved Genetic Algorithm-Based ApproachSoftware Technologies10.1007/978-3-319-93641-3_8(163-187)Online publication date: 8-Jun-2018
https://doi.org/10.1007/978-3-319-93641-3_8
Ravber MMernik Mrepinek M(2017)The impact of Quality Indicators on the rating of Multi-objective Evolutionary AlgorithmsApplied Soft Computing10.1016/j.asoc.2017.01.03855:C(265-275)Online publication date: 1-Jun-2017
https://dl.acm.org/doi/10.1016/j.asoc.2017.01.038
Akour MAlazzam IBanitaan SHanandeh F(2016)Feature-Based Test Focus Selection Technique Using Classes Connections WeightInternational Journal of Operations Research and Information Systems10.4018/IJORIS.20160101037:1(33-44)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.4018/IJORIS.2016010103
Liu HChen J(2014)A Coupling-Based Approach for Class Integration and Test OrderProceedings of the 2014 Asia-Pacific Services Computing Conference10.1109/APSCC.2014.39(35-41)Online publication date: 4-Dec-2014
https://dl.acm.org/doi/10.1109/APSCC.2014.39
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