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Developing a Single Model and Test Prioritization Strategies for Event-Driven Software

IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2011年第1期37卷 48-64页

作者： Bryce, Renee C. Sampath, Sreedevi Memon, Atif M. Utah State Univ Dept Comp Sci Logan UT 84322 USA Univ Maryland Baltimore Cty Dept Informat Syst Baltimore MD 21250 USA Univ Maryland Dept Comp Sci College Pk MD 20742 USA

Event-Driven Software (EDS) can change state based on incoming events;common examples are GUI and Web applications. These EDSs pose a challenge to testing because there are a large number of possible event sequences that users can invoke through a user interface. While valuable contributions have been made for testing these two subclasses of EDS, such efforts have been disjoint. This work provides the first single model that is generic enough to study GUI and Web applications together. In this paper, we use the model to define generic prioritization criteria that are applicable to both GUI and Web applications. Our ultimate goal is to evolve the model and use it to develop a unified theory of how all EDS should be tested. An empirical study reveals that the GUI and Web-based applications, when recast using the new model, show similar behavior. For example, a criterion that gives priority to all pairs of event interactions did well for GUI and Web applications;another criterion that gives priority to the smallest number of parameter value settings did poorly for both. These results reinforce our belief that these two subclasses of applications should be modeled and studied together.

关键词： combinatorial interaction testing covering arrays event-driven software (EDS) t-way interaction coverage test suite prioritization user-session testing Web application testing GUI testing

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A Kidney Algorithm with Elitism for combinatorial testing Problem

A Kidney Algorithm with Elitism for Combinatorial Testing Pr...

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作者： Ameen A.Bahomaid AbdulRahman A.Alsewari Kamal Z.Zamli Kamal M.Alhendawi Ala Aldeen Al-Janabi Faculty of Computing Universiti Malaysia Pahang Pahang Faculty of Management Israa University

testing software is an important activity before delivering the software with high quality. Among the various approaches for software testing, combinatorial interaction testing(CIT) is a proper and alternative testing approach for exhaustive testing that covers all possible interactions for a software's parameters. Generating an efficient test list with the optimal size is the most challenging problem in combinatorial interaction testing. Adopting Artificial Intelligence(AI) algorithms as the main algorithm for CIT strategies to generate the most optimal test lists. Kidney algorithm(KA) is a recent computational AI algorithm with sufficient optimization capability which outperforms the other AI algorithms(such as Genetic Algorithm(GA), Cuckoo Search(CS), Particle Swarm Optimization(PSO), Harmony Search(HS)) from some aspects. Although, KA may be easy to fall into local optima by keeping the worst solutions from the past generation as a new population with the best solutions. This study proposes to embed the elitism in the KA to preserve only the best solutions and swap the worsts by the new random solutions. Experimental results have been evidence that the proposed CIT strategy which called elitist KA Strategy(eKAS) produced sufficiently competitive results as compared with the original KA as well the existing CIT strategies.

关键词： Meta-heuristic combinatorial interaction testing Kidney Algorithm Elitism

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Properties of realistic feature models make combinatorial testing of product lines feasible 11

Properties of realistic feature models make combinatorial te...

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Proceedings of the 14th international conference on Model driven engineering languages and systems

作者： Martin Fagereng Johansen Øystein Haugen Franck Fleurey SINTEF ICT and Institute for Informatics University of Oslo Oslo Norway SINTEF ICT Oslo Norway

ISBN: (纸本)9783642244841

Feature models and associated feature diagrams allow modeling and visualizing the constraints leading to the valid products of a product line. In terms of their expressiveness, feature diagrams are equivalent to propositional formulas which makes them theoretically expensive to process and analyze. For example, satisfying propositional formulas, which translates into finding a valid product for a given feature model, is an NP-hard problem, which has no fast, optimal solution. This theoretical complexity could prevent the use of powerful analysis techniques to assist in the development and testing of product lines. However, we have found that satisfying realistic feature models is quick. Thus, we show that combinatorial interaction testing of product lines is feasible in practice. Based on this, we investigate covering array generation time and results for realistic feature models and find where the algorithms can be improved.

关键词： software product lines practical realistic combinatorial interaction testing featuremodels testing

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Enhancing the requirements engineering of configurable systems by the ongoing use of variability models

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REQUIREMENTS ENGINEERING 2024年第3期29卷 303-328页

作者： Khor, Chin Lutz, Robyn R. Iowa State Univ Comp Sci Dept 2434 Osborn Dr Ames IA 50011 USA

Software systems and product lines often use configurable features to specify a portfolio of product variants from a common core. Typically, their requirements also include constraints on which combinations of features are valid. Especially for larger systems and systems where the specifications are scattered among documents, the analysis of a new product's variability-related requirements is challenging. To address this, we introduce a scalable, tool-supported framework that uses a variability model to automate checks for missing and inconsistent features and constraints. Our approach also extends and scales traditional variability requirements engineering by incorporating combinatorial interaction testing techniques to build valid product variants covering all configurations in the variability model and to automatically discover faulty feature settings in failed builds. Results from evaluation on two configurable systems show that our framework is effective both at early detection of missing, incorrect, and inconsistent variability requirements and at later finding faulty feature configurations.

关键词： Requirement engineering Variability constraints Variability requirements Configurable system Variability model combinatorial interaction testing

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Covering Array Constructors: An Experimental Analysis of Their interaction Coverage and Fault Detection

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COMPUTER JOURNAL 2021年第5期64卷 762-788页

作者： Huang, Rubing Chen, Haibo Zhou, Yunan Chen, Tsong Yueh Towey, Dave Lau, Man Fai Ng, Sebastian Merkel, Robert Chen, Jinfu Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang 212013 Jiangsu Peoples R China Jiangsu Univ Jiangsu Key Lab Secur Technol Ind Cyberspace Zhenjiang 212013 Jiangsu Peoples R China Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang 202013 Jiangsu Peoples R China Swinbume Univ Technol Dept Comp Sci & Software Engn Hawthorn Vic 3122 Australia Univ Nottingham Ningbo China Sch Comp Sci Ningbo 315100 Zhejiang Peoples R China Monash Univ Fac Informat Technol Clayton Vic 3168 Australia

combinatorial interaction testing (CIT) aims at constructing a covering array (CA) of all value combinations at a specific interaction strength, to detect faults that are caused by the interaction of parameters. CIT has been widely used in different applications, with many algorithms and tools having been proposed to support CA construction. To date, however, there appears to have been no studies comparing different CA constructors when only some of the CA test cases are executed. In this paper, we present an investigation of five popular CA constructors: ACTS, Jenny, PICT, CASA and TCA. We conducted empirical studies examining the five programs, focusing on interaction coverage and fault detection. The experimental results show that when there is no preference or special justification for using other CA constructors, then Jenny is recommended-because it achieves better interaction coverage and fault detection than the other four constructors in many cases. Our results also show that when using ACTS or CASA, their CAs must be prioritized before testing. The main reason for this is that these CAs can result in considerable interaction coverage or fault detection capabilities when executing a large number of test cases;however, they may also produce the lowest rates of fault detection and interaction coverage.

关键词： combinatorial interaction testing covering array constructor empirical study software testing

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Controlling Occurrence Frequencies of Parameter Values in Pair-Wise testing

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INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING 2018年第7期28卷 983-1000页

作者： Fujimoto, Satoshi Kojima, Hideharu Tsuchiya, Tatsuhiro Osaka Univ Grad Sch Informat Sci & Technol 1-5 Yamadaoka Suita Osaka Japan

Pair-wise testing is a widely used strategy of software testing. It requires testing every pair of parameter values at least once. This paper focuses weighting of parameter values for this testing strategy. Weighting is an added feature which allows the tester to prioritize different parameter values by specifying their desired frequency of occurrence in a test suite. This feature is desirable as it allows the tester to have more control over the resulting test suite. However, there has been not much research on weighting: to our knowledge, all existing weighting methods treat weights as a second class requirement and cannot generate a test suite that sufficiently respects the given weights. Aiming to overcome this problem, this paper proposes a weighting method which can be used in combination of any one-test-at-a-time greedy test case generation algorithm. By comparing the parameter value distribution in the current test suite and the ideal one specified by the given weights, the method generates each test case so that the resulting test suite can reflect the weights as accurately as possible. The usefulness of the method is demonstrated through empirical results.

关键词： Software testing pair-wise testing weighting combinatorial interaction testing

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Using simulated annealing for computing cost-aware covering arrays

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APPLIED SOFT COMPUTING 2016年 49卷 1129-1144页

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

The configuration spaces of software systems are often too large to test exhaustively. combinatorial interaction testing approaches, such as covering arrays, systematically sample the configuration space and test only the selected configurations. In an attempt to reduce the cost of testing, standard t-way covering arrays aim to cover all t-way combinations of option settings in a minimum number of configurations. By doing so, they simply assume that every configuration costs the same. When the cost varies from one configuration to another, however, minimizing the number of configurations is not necessarily the same as minimizing the cost. To overcome this issue, we have recently introduced cost-aware covering arrays. In a nutshell, a t-way cost-aware covering array is a standard t-way covering array that minimizes a given cost function modeling the actual cost of testing. In this work we develop a simulated annealing-based approach to compute cost-aware covering arrays, which takes as input a configuration space model enhanced with a cost function and computes a cost-aware covering array by using two alternating neighboring state generation strategies together with a fitness function expressed as a weighted sum of two objectives: covering all required t-way option setting combinations and minimizing the cost function. To the best of our knowledge, the proposed approach is the first approach that computes cost-aware covering arrays for general, non-additive linear cost functions with multiplicative interaction effects. We evaluate the approach both by conducting controlled experiments, in which we systematically vary the input models to study the sensitivity of the approach to various factors and by conducting experiments using real cost functions for real software systems. We also compare cost-aware covering arrays to standard covering arrays constructed by well-known algorithms and study how fast the construction costs are compensated by the cost reductions provide

关键词： Software quality assurance combinatorial interaction testing Covering arrays Cost-aware testing Simulated annealing

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Prioritising abstract test cases: an empirical study

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IET SOFTWARE 2019年第4期13卷 313-326页

作者： Huang, Rubing Zong, Weiwen Chen, Tsong Yueh Towey, Dave Zhou, Yunan Chen, Jinfu Jiangsu Univ Sch Comp Sci & Commun Engn Zhenjiang 212013 Jiangsu Peoples R China Swinburne Univ Technol Dept Comp Sci & Software Engn Hawthorn Vic 3122 Australia Univ Nottingham Ningbo China Sch Comp Sci Ningbo 315100 Zhejiang Peoples R China

Test-case prioritisation (TCP) attempts to schedule the order of test-case execution such that faults can be detected as quickly as possible. TCP has been widely applied in many testing scenarios such as regression testing and fault localisation. Abstract test cases (ATCs) are derived from models of the system under test and have been applied to many testing environments such as model-based testing and combinatorial interaction testing. Although various empirical and analytical comparisons for some ATC prioritisation (ATCP) techniques have been conducted, to the best of the authors' knowledge, no comparative study focusing on the most current techniques has yet been reported. In this study, they investigated 18 ATCP techniques, categorised into four classes. They conducted a comprehensive empirical study to compare 16 of the 18 ATCP techniques in terms of their testing effectiveness and efficiency. They found that different ATCP techniques could be cost-effective in different testing scenarios, allowing us to present recommendations and guidelines for which techniques to use under what conditions.

关键词： program testing software tools comprehensive empirical study testing effectiveness test-case prioritisation TCP test-case execution regression testing fault localisation model-based testing combinatorial interaction testing ATC prioritisation techniques ATCP techniques

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PRIORITIZATION OF combinatorial TEST CASES BY INCREMENTAL interaction COVERAGE

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INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING 2013年第10期23卷 1427-1457页

作者： Huang, Rubing Xie, Xiaodong Towey, Dave Chen, Tsong Yueh Lu, Yansheng Chen, Jinfu Huazhong Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430074 Hubei Peoples R China Jiangsu Univ Sch Comp Sci & Telecommun Engn Zhenjiang 212013 Jiangsu Peoples R China Huaqiao Univ Sch Comp Sci & Technol Xiamen 362021 Fujian Peoples R China Univ Nottingham Ningbo China Div Comp Sci Ningbo 315100 Zhejiang Peoples R China Swinburne Univ Technol Fac Informat & Commun Technol Hawthorn Vic 3122 Australia

combinatorial interaction testing is a well-recognized testing method, and has been widely applied in practice, often with the assumption that all test cases in a combinatorial test suite have the same fault detection capability. However, when testing resources are limited, an alternative assumption may be that some test cases are more likely to reveal failure, thus making the order of executing the test cases critical. To improve testing cost-effectiveness, prioritization of combinatorial test cases is employed. The most popular approach is based on interaction coverage, which prioritizes combinatorial test cases by repeatedly choosing an unexecuted test case that covers the largest number of uncovered parameter value combinations of a given strength (level of interaction among parameters). However, this approach suffers from some drawbacks. Based on previous observations that the majority of faults in practical systems can usually be triggered with parameter interactions of small strengths, we propose a new strategy of prioritizing combinatorial test cases by incrementally adjusting the strength values. Experimental results show that our method performs better than the random prioritization technique and the technique of prioritizing combinatorial test suites according to test case generation order, and has better performance than the interaction-coverage-based test prioritization technique in most cases.

关键词： Software testing combinatorial interaction testing test case prioritization interaction coverage incremental interaction coverage algorithm

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Construction of t-way covering arrays using genetic algorithm

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INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2017年第2期8卷 264-274页

作者： Sabharwal, Sangeeta Bansal, Priti Mittal, Nitish Netaji Subhas Inst Technol Dept Informat Technol New Delhi 110078 India Netaji Subhas Inst Technol Dept Comp Engn New Delhi 110078 India

In a component based system, interaction among components may give rise to interaction faults. Faults can be caused by the interactions of two or more than two components. Since, it is not feasible to test all possible interactions combinatorial interaction testing is being employed to generate covering arrays (CAs) that covers all t-way interactions between components. In this paper, we generalize our previous work, that uses a greedy based genetic algorithm, to generate CA from 2-way to t-way testing (2 <= t <= 4). We implement the proposed strategy by extending an open source tool PWiseGen. The main drawback of PWiseGen is the need to input the size of CA in advance. To overcome this restriction of PWiseGen, we propose a variation of binary search algorithm that generates optimal CA without knowing its size in advance. Experiments are conducted to evaluate the effectiveness of the proposed approach and it has been observed that the proposed approach performs well as compared to existing state-of-the-art algorithms.

关键词： combinatorial interaction testing Covering arrays t-way testing Genetic algorithm

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