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An exploratory empirical eye-tracker study of visualization techniques for coverage of combinatorial interaction testing in software product lines☆

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JOURNAL OF SYSTEMS AND SOFTWARE 2025年 220卷

作者： Balouchi, Kambiz Nezami Mercier, Julien Lopez-Herrejon, Roberto E. Ecole technol Super Dept Software Engn & IT Montreal PQ Canada Univ Quebec Montreal Dept Comp Sci Montreal PQ Canada

Software Product Lines (SPLs) typically provide a large number of configurations to cater to a set of diverse requirements of specific markets. This large number of configurations renders unfeasible to test them all individually. Instead, combinatorial interaction testing (CIT) computes a representative sample according to criteria of the interactions of features in the configurations. We performed an empirical study using eye-tracker technologies to analyze the effectiveness of two basic visualization techniques at conveying test coverage information often case studies of varying complexity. Our evaluation considered response accuracy, time-ontask, metacognitive monitoring, and visual attention. The study revealed clear advantages of a visualization technique over the other in three evaluation aspects, with a reverse effect depending on the strength of the coverage and distinct areas of visual attention.

关键词： Software product lines combinatorial interaction testing Covering array Parallel dimensions plot Scatter plot Eye-tracker study

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combinatorial interaction testing of a Java Card static verifier

Combinatorial interaction testing of a Java Card static veri...

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7th IEEE International Conference on Software testing, Verification and Validation (ICST)

作者： Calvagna, Andrea Fornaia, Andrea Tramontana, Emiliano Univ Catania Dipartimento Matemat & Informat I-95124 Catania Italy

ISBN: (纸本)9780769551944

We present a combinatorial interaction testing approach to perform validation testing of a fundamental component for the security of Java Cards: the byte code verifier. combinatorial testing of all states of the Java Card virtual machine has been adopted as the coverage criteria. We developed a formal model of the Java Card byte code syntax to enable the combinatorial enumeration of well-formed states, and a formal model of the byte code semantic rules to be able to distinguish between well-typed and ill-typed ones, and to derive actual test programs from them. A complete framework has been implemented, enabling fully automated application and evaluation of the conformance tests to any verifier implementation.

关键词： Software engineering combinatorial interaction testing Java virtual machine

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Practical combinatorial interaction testing: Empirical Findings on Efficiency and Early Fault Detection

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2015年第9期41卷 901-924页

作者： Petke, Justyna Cohen, Myra B. Harman, Mark Yoo, Shin UCL Dept Comp Sci London England Univ Nebraska Dept Comp Sci & Engn Lincoln NE USA

combinatorial interaction testing (CIT) is important because it tests the interactions between the many features and parameters that make up the configuration space of software systems. Simulated Annealing (SA) and Greedy Algorithms have been widely used to find CIT test suites. From the literature, there is a widely-held belief that SA is slower, but produces more effective tests suites than Greedy and that SA cannot scale to higher strength coverage. We evaluated both algorithms on seven real-world subjects for the well-studied two-way up to the rarely-studied six-way interaction strengths. Our findings present evidence to challenge this current orthodoxy: real-world constraints allow SA to achieve higher strengths. Furthermore, there was no evidence that Greedy was less effective (in terms of time to fault revelation) compared to SA;the results for the greedy algorithm are actually slightly superior. However, the results are critically dependent on the approach adopted to constraint handling. Moreover, we have also evaluated a genetic algorithm for constrained CIT test suite generation. This is the first time strengths higher than 3 and constraint handling have been used to evaluate GA. Our results show that GA is competitive only for pairwise testing for subjects with a small number of constraints.

关键词： combinatorial interaction testing prioritisation empirical studies software testing

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Test Case-Aware combinatorial interaction testing

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2013年第5期39卷 684-706页

作者： Yilmaz, Cemal Sabanci Univ Fac Engn & Nat Sci TR-34956 Istanbul Turkey

The configuration spaces of modern software systems are too large to test exhaustively. combinatorial interaction testing (CIT) approaches, such as covering arrays, systematically sample the configuration space and test only the selected configurations by using a battery of test cases. Traditional covering arrays, while taking system-wide interoption constraints into account, do not provide a systematic way of handling test case-specific interoption constraints. The basic justification for t-way covering arrays is that they can cost effectively exercise all system behaviors caused by the settings of t or fewer options. In this paper, we hypothesize, however, that in the presence of test case-specific interoption constraints, many such behaviors may not be tested due to masking effects caused by the overlooked test case-specific constraints. For example, if a test case refuses to run in a configuration due to an unsatisfied test case-specific constraint, none of the valid option setting combinations appearing in the configuration will be tested by that test case. To account for test case-specific constraints, we introduce a new combinatorial object, called a test case-aware covering array. A t-way test case-aware covering array is not just a set of configurations, as is the case in traditional covering arrays, but a set of configurations, each of which is associated with a set of test cases such that all test case-specific constraints are satisfied and that, for each test case, each valid combination of option settings for every combination of t options appears at least once in the set of configurations that the test case is associated with. We furthermore present three algorithms to compute test case-aware covering arrays. Two of the algorithms aim to minimize the number of configurations required (one is fast, but produces larger arrays, the other is slower, but produces smaller arrays), whereas the remaining algorithm aims to minimize the number of test runs requi

关键词： Software quality assurance combinatorial interaction testing covering arrays

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Flexible combinatorial interaction testing

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2022年第3期48卷 1030-1066页

作者： Mercan, Hanefi Javeed, Arsalan Yilmaz, Cemal Sabanci Univ Fac Engn & Nat Sci TR-34956 Istanbul Turkey

We present Flexible combinatorial interaction testing (F-CIT), which aims to improve the flexibility of combinatorial interaction testing (CIT) by eliminating the necessity of developing specialized constructors for CIT problems that cannot be efficiently and effectively addressed by the existing CIT constructors. F-CIT expresses the entities to be covered and the space of valid test cases, from which the samples are drawn to obtain full coverage, as constraints. Computing an F-CIT object (i.e., a set of test cases obtaining full coverage under a given coverage criterion) then turns into an interesting constraint solving problem, which we call cov-CSP. cov-CSP aims to divide the constraints, each representing an entity to be covered, into a minimum number of satisfiable clusters, such that a solution for a cluster represents a test case and the collection of all the test cases generated (one per cluster) constitutes an F-CIT object, covering each required entity at least once. To solve the cov-CSP problem, thus to compute F-CIT objects, we first present two constructors. One of these constructors attempts to cover as many entities as possible in a cluster before generating a test case, whereas the other constructor generates a test case first and then marks all the entities accommodated by this test case as covered. We then use these constructors to evaluate F-CIT in three studies, each of which addresses a different CIT problem. In the first study, we develop structure-based F-CIT objects to obtain decision coverage-adequate test suites. In the second study, we develop order-based F-CIT objects, which enhance a number of existing order-based coverage criteria by taking the reachability constraints imposed by graph-based models directly into account when computing interaction test suites. In the third study, we develop usage-based F-CIT objects to address the scenarios, in which standard covering arrays are not desirable due to their sizes, by choosing the entities

关键词： testing Standards Software Computational modeling Computers Electronic mail Tools combinatorial interaction testing covering arrays sequence covering arrays constraint solving structural coverage coverage criteria

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Moving Forward with combinatorial interaction testing

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COMPUTER 2014年第2期47卷 37-45页

作者： Yilmaz, Cemal Fouche, Sandro Cohen, Myra B. Porter, Adam Demiroz, Gulsen Koc, Ugur Sabanci Univ Fac Engn & Nat Sci Istanbul Turkey Towson Univ Dept Comp & Informat Sci Towson MD USA Univ Nebraska Lincoln Dept Comp Sci & Engn Lincoln NE USA Univ Maryland Inst Adv Studies UMIACS College Pk MD 20742 USA

combinatorial interaction testing (CIT) is an effective failure detection method for many types of software systems. This review discusses the current approaches CIT uses in detecting parameter interactions, the diffi... 详细信息

关键词： Software testing Biological System Modeling Arrays Analytical Models Failure Detection Adaptation Models combinatorial Mathematics Software testing combinatorial interaction testing Covering Arrays

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Constraints handling in combinatorial interaction testing using multi-objective crow search and fruitfly optimization

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SOFT COMPUTING 2019年第8期23卷 2713-2726页

作者： Ramgouda, P. Chandraprakash, V. Koneru Lakshmaiah Educ Fdn Dept Comp Sci & Engn Vaddeswaram Guntur India

combinatorial testing strategies are the recent interest of the researchers because of their wide variety of applications. The combinatorial testing strategy posses a great deal of minimizing the count of the input parameters of a system such that a small set of parameters is obtained depending on their interaction. Practically, the input models of the software system are subjected to the constraints mainly in highly configurable systems. There exist a number of issues while integrating the constraint in the testing strategy that is overcome using the proposed method. The proposed method aims at developing the combinatorial interaction test suites in the presence of constraints. The proposed strategy is multi-objective crow search and fruitfly optimization that is developed by the integration of the crow search algorithm and the chaotic fruitfly optimization algorithm. The proposed algorithm offers an optimal selection of the test suites at the better convergence. The experimentation based on the constraints and the analysis are carried out in terms of average size and average time with their values as 10 and 30s, respectively.

关键词： combinatorial interaction testing Constraints Crow search algorithm (CSA) Chaotic FOA Multi-objectives

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Sampling Program Inputs with Mutation Analysis: Going Beyond combinatorial interaction testing

Sampling Program Inputs with Mutation Analysis: Going Beyond...

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7th IEEE International Conference on Software testing, Verification and Validation (ICST)

作者： Papadakis, Mike Henard, Christopher Le Traon, Yves Univ Luxembourg Interdisciplinary Ctr Secur Reliabil & Trust SnT Luxembourg Luxembourg

ISBN: (纸本)9780769551852

Modern systems tend to be highly configurable. testing such systems requires selecting test cases from a large input space. Thus, there is a need to systematically sample program inputs in order to reduce the testing effort. In such cases, testing the interactions between program parameters has been identified as an effective way to deal with this problem. In these lines, combinatorial interaction testing (CIT) models the program input interactions and uses this model to select test cases. Going a step further, we apply mutation analysis on the CIT input model to select program test cases. Mutation operates by injecting defects to the program input model and measures the number of defects found by the selected test cases. Experiments performed on four real programs show that measuring the number of model-based defects gives a stronger correlation to code-level faults than measuring the number of the exercised interactions. Therefore, the proposed mutation analysis approach forms a valid and more effective alternative to CIT.

关键词： Mutation Analysis combinatorial interaction testing Fault Detection

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Meta -Heuristic Algorithm for Constructing Higher-Index Covering Arrays for combinatorial interaction testing 16

Meta -Heuristic Algorithm for Constructing Higher-Index Cove...

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16th IEEE International Conference on Software testing, Verification and Validation (ICST)

作者： Qin, Gang Zheng, Junjun Tsuchiya, Tatsuhiro Osaka Univ Grad Sch Info Sci Tech Suita Osaka Japan

ISBN: (纸本)9798350333350

A covering array is a mathematical object commonly used to represent a test suite for combinatorial interaction testing (CIT). Covering array generation has been extensively studied in the past two decades, and most of these studies considered cases in which each interaction was covered at least once. However, when one needs to test each interaction more than once, it is necessary to generate a higher-index covering array in which each interaction is covered twice or more. The generation of higherindex covering arrays has rarely been studied. In this paper, we proposed a meta-heuristic algorithm to generate higherindex covering arrays. We conducted experiments to compare the proposed algorithm with existing algorithms. The experimental results demonstrated that the proposed algorithm can generate smaller higher-index covering arrays than existing algorithms.

关键词： Terms higher-index covering arrays combinatorial interaction testing software testing meta-heuristic algorithms

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Beyond Pairwise testing: Advancing 3-wise combinatorial interaction testing for Highly Configurable Systems 2024

Beyond Pairwise Testing: Advancing 3-wise Combinatorial Inte...

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33rd ACM SIGSOFT International Conference on Software testing and Analysis (ISSTA)

作者： Luo, Chuan Lyu, Shuangyu Zhao, Qiyuan Wu, Wei Zhang, Hongyu Hu, Chunming Beihang Univ Beijing Peoples R China Natl Univ Singapore Singapore Singapore Cent South Univ Changsha Peoples R China Xiangjiang Lab Changsha Peoples R China Chongqing Univ Chongqing Peoples R China

ISBN: (纸本)9798400706127

To meet the rising demand for software customization, highly configurable software systems play key roles in practice. combinatorial interaction testing (CIT) is recognized as an effective approach for testing such systems. For CIT, the most important problem is constrained covering array generation (CCAG), which aims to construct a minimum-sized t-wise covering array (CA), where t denotes testing strength. Compared to pairwise testing (i.e., 2-wise CIT) that is a widely-used CIT technique, 3-wise CIT can discover more faults and bring more benefit in real-world applications. However, current state-of-the-art CCAG algorithms suffer from the severe scalability challenge for 3-wise CIT, which renders them ineffective in building 3-wise CAs for highly configurable systems. In this work, we perform an empirical study on various practical, highly configurable systems to present that it is promising to build 3-wise CA through extending 2-wise CA. Inspired by this, we propose ScalableCA, a novel and scalable algorithm that can effectively alleviate the scalability challenge for 3-wise CIT. Further, ScalableCA introduces three new and effective techniques, including fast invalidity detection, uncovering-guided sampling, and remainder-aware local search, to enhance its performance. Our experiments on extensive realworld, highly configurable systems show that, compared to current state-of-the-art algorithms, ScalableCA requires one to two orders of magnitude less running time to build 3-wise CA of 38.9% smaller size in average for large-scale instances. Our results indicate that ScalableCA greatly advances the state of the art in 3-wise CIT.

关键词： combinatorial interaction testing Satisfiability Sampling

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