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9th International Conference on Quality Software (QSIC 2009)

作者： Yu, Y. T. Chan, Eric Y. K. Poon, P. -L. City Univ Hong Kong Dept Comp Sci Kowloon Tong Hong Kong Peoples R China Honkong Polytech Univ Hung Hom Sch Accounting & Finance Kowloon Hong Kong Peoples R China

ISBN: (纸本)9781424459124

Generating test cases from the specification can be done early in the software development life cycle. A test suite systematically generated from the software specification can be comprehensive in ensuring the intended functions to be exercised. Such a test suite is also instrumental in facilitating early discovery of software defects. On the other hand, an adequate level of code coverage is required to inspire confidence of the testing and quality assurance process. To examine the effectiveness of a specification-based test suite in covering program code, we conducted an exploratory case study which involved many different versions of programs that implemented the same specification. On the basis of the case study, this paper identifies the types of path in the programs, suggests enhancements to the existing test generation methods, and discusses several issues on how the code coverage can be improved.

关键词： category-partition method classification-tree method code coverage path coverage specification-based testing

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A novel approach for code coverage testing using hybrid metaheuristic algorithm

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International Journal of Information Technology (Singapore) 2024年第6期16卷 3691-3701页

作者： Ahsan, Fatma Anwer, Faisal Department of Computer Science Aligarh Muslim University Aligarh India

Testing is essential for the software’s success, but despite this, it is a time and resource-consuming activity. Therefore, researchers and practitioners continuously try to improve software testing automation to maximize test coverage and make it fast and reliable. Meta-heuristics are high-level frameworks that many researchers have used to generate test data for software testing. Maximizing test coverage would also indirectly help to find vulnerabilities in the code. In this paper, we have implemented an improved hybrid metaheuristic algorithm to generate test cases, utilizing particle swarm optimization (PSO) and genetic algorithm (GA) for path coverage testing criterion. The used fitness function is the combination of branch distance, approximation level and path distance. The proposed approach is a hybrid Particle Swarm Optimization and Genetic Algorithm (PSO-GA). We compared the meta-heuristics GA, PSO and Hybrid PSO-GA algorithm with different fitness functions. Moreover, the experimental result shows that the hybrid algorithm improves outcomes compared to GA and PSO for the combined fitness functions. This approach demonstrates noteworthy efficacy in addressing security vulnerabilities during testing, particularly due to its emphasis on comprehensive path testing. This methodology has yielded significant outcomes in the realm of security testing, highlighting its potential for practical application and exploration in research. Furthermore, more meta-heuristics can be incorporated into the hybrid approach. © Bharati Vidyapeeth's Institute of Computer Applications and Management 2024.

关键词： Code coverage Genetic algorithm Hybrid algorithm Memetic algorithm Particle swarm optimization path coverage Software testing

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Energy efficiency and lifetime enhancement of K-Barrier coverage in Wireless Sensor Networks 2

Energy efficiency and lifetime enhancement of K-Barrier cove...

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International Conference on Inventive Communication and Computational Technologies (ICICCT)

作者： Anand, Anagha S. Anitha, V. S. Govt Engn Coll Wayanad Comp Networks & Secur Wayanad 670644 Kerala India Govt Engn Coll Wayanad Comp Sci Engn Wayanad 670644 Kerala India

ISBN: (纸本)9781538619742

Highly dedicated hybrid directional wireless sensor networks are used for the security of borders of highly sensitive areas such as national borders, forest crossing paths, boundaries of nuclear reactors, battle fields etc. coverage provided by the sensor networks can be explained in terms of point coverage, line coverage, area coverage and path coverage. Based on the concept of path coverage, k-barrier coverage is achieved if and only if the path of an intruder is detected k-times inside a belt area by distinct k-number of disjoint sensors. The concept of strong barrier coverage can be combined with the lifetime of sensor nodes to achieve highly dedicated hybrid sensor networks which is a very relevant and genuine problem in the field of border protection. The cost for the maintenance of wireless sensor network depends on the energy efficiency and lifetime of the individual sensors. This paper discusses different mechanisms to achieve energy efficiency and lifetime enhancement of k-barrier coverage in wireless sensor networks.

关键词： Barrier coverage Directional sensors Mobile sensors path coverage Bounded belt area

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Formalizing path Explosion for Recursive Functions via Asymptotic path Complexity 11

Formalizing Path Explosion for Recursive Functions via Asymp...

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IEEE/ACM 11th International Conference on Formal Methods in Software Engineering (FormaliSE)

作者： Pregerson, Eli Cullen-Baratloo, Shaheen Chen, David Lam, Duy Szostak, Max Bang, Lucas Harvey Mudd Coll Comp Sci Dept Claremont CA 91711 USA

ISBN: (纸本)9798350312638

path coverage is of critical importance in software testing and verification. Furthermore, path explosion is a well-known challenge for automatic software analysis techniques like symbolic execution. Asymptotic path Complexity (APC) is a code complexity metric that formalizes the quantitative measurement of path explosion and therefore measures the difficulty of achieving path coverage. Prior APC methods were not sufficiently expressive to model the path explosion behavior in recursive functions. Existing analyses simply ignored recursive calls and were unable to correctly compute APC for recursive functions. We present a novel method for computing asymptotic path complexity for recursive functions, which we call APC-R. Our approach is based on the analytic combinatorics of context-free grammars. We implemented our approach on top of the code complexity analysis tool METRINOME and evaluated our implementation on a set of benchmark programs written in the C programming language. Our experiments demonstrate that APC-R is a sound upper bound on the growth rate of the number of program paths explored as a function of increasing exploration depth when generating tests with the KLEE symbolic execution engine. Our APC-R implementation provides sound bounds on KLEE's symbolic execution path explosion for recursive functions in cases where the original APC implementation did not, and APC-R matches the results of APC for non-recursive functions with only marginal computational overhead. That is, APC-R subsumes earlier APC work without significant performance cost.

关键词： code complexity path coverage path explosion symbolic execution

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Enhancing path-Oriented Test Data Generation Using Adaptive Random Testing Techniques 2

Enhancing Path-Oriented Test Data Generation Using Adaptive ...

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2nd International Conference on Knowledge Based Engineering and Innovation (KBEI)

作者： Nikravan, Esmaeel Feyzi, Farid Parsa, Saeed Iran Univ Sci & Technol Fac Comp Engn Tehran Iran

ISBN: (纸本)9781467365062

in this paper, we have developed an approach to generate test data for path coverage based testing. The main challenge of this kind testing lies in its ability to build efficiently such a test suite in order to minimize the number of rejects. We address this problem with a novel divide-and-conquer approach based on adaptive random testing strategy. Our approach takes as input the constraints of an executable path and computes a tight over-approximation of their associated sub-domain by using a dynamic domain partitioning approach. We implemented this approach and got experimental results that show the practical benefits compared to existing approaches. Our method generates less invalid inputs and is capable of obtaining the sub-domain of many complex constraints.

关键词： software testing test data path coverage random testing adaptive random testing

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Strategy-Guided Test-Case Order in Dynamic Symbolic Execution 11

Strategy-Guided Test-Case Order in Dynamic Symbolic Executio...

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2017 11th IEEE International Conference on Anti-counterfeiting,Security,and Identification(ASID)

作者： Jiaxi Ye Bin Zhang Chao Feng Chaojing Tang College of Electronic Science National University of Defense Technology

ISBN: (纸本)9781538605349;9781538605332

Dynamic symbolic execution(DSE) is a variation of symbolic execution, which is a path sensitive technique for software testing. Recently there has emerged much new techniques and many new tools, depending on DSE, to improve path coverage in testing. But when facing large-scale programs, there still exists a challenge that if DSE cannot choose better inputs as seeds, it has to do much redundant execution because of inputs' similarity in their trace. An intuitive idea to improve the performance of DSE is to reorder these inputs, which will be passed to the symbolic engine for path-constraints collection, by some criteria. In this paper,we present six strategies and design some experiments, aiming to demonstrate that ordering testing case is useful to improve the path-coverage in a limited resource.

关键词： dynamic symbolic execution strategy path coverage information security

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Evolutionary Multi-Objective Optimization for Data-Flow Testing of Object-Oriented Programs

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2nd International Conference on Advances in Computing and Informaiton Technology (ACITY 2012)

作者： Maragathavalli, P. Kanmani, S. Pondicherry Engn Coll Dept Informat Technol Pondicherry India

ISBN: (纸本)9783642315510

This paper presents a Class-Based Elitist Genetic Algorithm (CBEGA) to generate a suite of tests for testing the object-oriented programs using evolutionary multi-objective optimization techniques. Evolutionary Algorithms (EAs) are inspired by mechanisms in biological evolution like reproduction, mutation, recombination, and selection. EA applies these mechanisms repeatedly to a set of individuals called population to obtain solution. Multi-objective optimization involves optimizing a number of objectives simultaneously. The objectives considered in this paper for optimization are maximum coverage, minimum execution time and test-suite minimization. The experiment shows that CBEGA gives 92% path coverage and simple GA gives 88% path coverage for a set of java classes.

关键词： Evolutionary Algorithm multi-objective path coverage CBEGA immigration rate

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EPC Enacted: Integration in an Industrial Toolbox and Use Against a Railway Application 23

EPC Enacted: Integration in an Industrial Toolbox and Use Ag...

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23rd IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS)

作者： Mezzetti, Enrico Fernandez, Mikel Bardizbanyan, Alen Agirre, Irune Abella, Jaume Vardanega, Tullio Cazorla, Francisco Barcelona Supercomp Ctr Barcelona Spain Cobham Gaisler Gothenburg Sweden IK4 IKERLAN Arrasate Mondragon Spain Univ Padua Padua Italy Univ Politecn Cataluna Barcelona Spain IIIA CSIC Barcelona Spain

ISBN: (纸本)9781509052691

Measurement-based timing analysis approaches are increasingly making their way into several industrial domains on account of their good cost-benefit ratio. The trustworthiness of those methods, however, suffers from the limitation that their results are only valid for the particular paths and execution conditions that the user is able to explore with the available input vectors. It is generally not possible to guarantee that the collected measurements are fully representative of the worst-case timing behaviour. In the context of measurement-based probabilistic timing analysis, the Extended path coverage (EPC) approach has been recently proposed as a means to extend the representativeness of measurement observations, to obtain the same effect of full path coverage. At the time of its first publication, EPC had not reached an implementation maturity that could be trialled industrially. In this work we analyze the practical implications of using EPC with real-world applications, and discuss the challenges in integrating it in an industrial-quality toolchain. We show that we were able to meet EPC requirements and successfully evaluate the technique on a real Railway application, on top of a commercial toolchain and full execution stack.

关键词： Measurement-based probabilistic timing analysis path coverage Evaluation

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An Enhanced Set-based Evolutionary Algorithm for Generating Test Data that Cover Multiple paths of a Parallel Program 8

An Enhanced Set-based Evolutionary Algorithm for Generating ...

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8th IEEE Symposium Series on Computational Intelligence (IEEE SSCI)

作者： Tian, Tian Yang, Su Gong, Dunwei Shandong Jianzhu Univ Sch Comp Sci & Technol Jinan Shandong Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou Jiangsu Peoples R China

ISBN: (纸本)9781538692769

Although the traditional set-based evolutionary algorithm can generate test data covering multiple paths, it does not make full use of the uncertainty of parallel programs, information provided by the population during the evolution, and knowledge related to the domain, which makes the efficiency remain to be improved. This paper focuses on the problem of generating test data for multiple paths coverage of message-passing parallel programs, and proposes an enhanced set-based evolutionary algorithm that is suitable for parallel programs based on the evaluation of scheduling sequences to improve the efficiency in generating test data. We apply the proposed algorithm to nine message-passing parallel programs, and compare it with the traditional set-based evolutionary algorithm. The experimental results show that the proposed algorithm reduces the number of generations and the time consumption in test data generation.

关键词： message-passing parallel program test data generation path coverage set-based evolutionary optimization uncertainty

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An Approach for Improving Stability of path-Oriented Test Data Generation 2

An Approach for Improving Stability of Path-Oriented Test Da...

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2nd IEEE International Conference on Computer and Communications (ICCC)

作者： Zhao, Qing Fan, Fengxian Kunming Univ Sch Informat Technol Kunming Yunnan Peoples R China

ISBN: (纸本)9781467390262

path coverage testing is an important method for software structural testing. The application of evolutionary algorithms to path test can not only reduce the cost, but ensure the reliability of software quality. The research on applying genetic algorithm to test data generation of path coverage has gained substantial achievements in recent years. Because the accuracy of searching is not high enough to meet the requirements for generating path test data, the results are unstable in generic algorithm. In this paper, we propose multivariate optimization algorithm to solve this problem. Experimental results show that multivariate optimization algorithm achieves better searching precision and lower volatility in the search process, which provides a new method for the path-oriented Test data generation with higher quality.

关键词： software test path coverage genetic algorithm nmltivariate optimization algorithm

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