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Proceedings of the 34th ACM SIGSOFT International Symposium on Software testing and Analysis

作者： Paul Kalbitzer Jose Antonio Zamudio Amaya Andreas Zeller CISPA Helmholtz Center for Information Security Saarbrücken Germany

ISBN: (纸本)9798400714740

Web services are essential for online interactions, supporting critical tasks like banking and shopping, but their importance also makes them prime targets for attacks. Attackers try to manipulate data injecting malicious code, potentially compromising systems. Current approaches to preventing such attacks use techniques like attack grammars, symbolic execution, or machine learning to detect vulnerabilities or manually embed malicious payloads, that can miss parts of the service under *** this paper, we propose XAVIER, a framework for detecting XML injection vulnerabilities. By leveraging the WSDL specification of a web service, XAVIER crafts XML messages that reflect the service's functionality, enabling the examination of web services for XMLi vulnerabilities. Results show that XAVIER performs equally, or better than the state-of-the-art tool, SOAPUI PRO. Compared to the latter, XAVIER is open source and extensible, providing a platform for future research in the field.

关键词： grammar-based testing

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Reducing the Cost of grammar-based testing Using Pattern Coverage 27th

Reducing the Cost of Grammar-Based Testing Using Pattern Cov...

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27th IFIP WG 6.1 International Conference on testing Software and Systems (ICTSS)

作者： Hentz, Cleverton Vinju, Jurgen J. Moreira, Anamaria M. Univ Fed Rio Grande do Norte BR-59072970 Natal RN Brazil Ctr Wiskunde & Informat Amsterdam Netherlands Eindhoven Univ Technol NL-5600 MB Eindhoven Netherlands INRIA Lille Nord Europe Villeneuve Dascq France Univ Fed Rio de Janeiro Rio De Janeiro Brazil

ISBN: (纸本)9783319259451;9783319259444

In grammar-based testing, context-free grammars may be used to generate relevant test inputs for language processors, or meta programs, such as programming language compilers, refactoring tools, and implementations of software quality metrics. This technique can be used to test these meta programs, but the amount of sentences, and syntax trees thereof, which needs to be generated to obtain reasonable coverage of the input language is exponential. Pattern matching is a programming language feature used often when writing meta programs. Pattern matching helps because it automates the frequently occurring task of detecting shapes in, and extracting information from syntax trees. However, meta programs which contain many patterns are difficult to test using only randomly generated sentences from grammar rules. The reason is that statistically it is uncommon to directly generate sentences which accidentally match the patterns in the code. To solve this problem, in this paper we extract information from the patterns in the code of meta programs to guide the sentence generation process. We introduce a new coverage criterion, called Pattern Coverage, which focuses on providing a test strategy to reduce the amount of test necessary cases, while covering the relevant parts of the meta program. An initial experimental evaluation is presented and the result is compared with traditional grammar-based testing.

关键词： Software test Meta program Pattern matching grammar-based testing

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Novelty-Driven Evolutionary Scriptless testing 18th

Novelty-Driven Evolutionary Scriptless Testing

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18th International Conference on Research Challenges in Information Sciences (RCIS)

作者： Hufkens, Lianne V. Vos, Tanja E. J. Marin, Beatriz Open Univ Valkenburgerweg 177 NL-6419 AT Heerlen Netherlands Univ Politecn Valencia Valencia Spain

ISBN: (纸本)9783031594670;9783031594687

In recent years, scriptless Graphical User Interface (GUI) testing has been positioned as a complement to traditional testing techniques. Automated scriptless GUI testing approaches use Action Selection Rules (ASR) to generate on-the-fly test sequences when testing a software system. Currently, random is the standard selection approach in scriptless testing, provoking drawbacks in the testing process, such as test sequences that do not reflect the human strategies for testing, and being unable to deal with multistep tasks. This paper presents an alternate selection approach based on the use of a grammar to design the ASR and an Evolutionary Algorithm (EA) with Novelty Search (NS) to direct the evolution process. Preliminary testing shows that the ASRS do evolve in the standard EA process. Further research is needed to show the benefits of the additional NS for the testing process.

关键词： Automated GUI testing Scriptless testing Novelty Search grammar-based testing Evolutionary testing Grammatical Evolution

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Random grammar-based testing for Covering All Non-Terminals

Random Grammar-based Testing for Covering All Non-Terminals

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6th IEEE International Conference on Software testing, Verification and Validation (ICST)

作者： Dreyfus, Alois Heam, Pierre-Cyrille Kouchnarenko, Olga Univ Franche Comte FEMTO ST CNRS UMR6174 INRIA CASSIS F-25030 Besancon France

ISBN: (纸本)9780769549934;9781479913244

In the context of software testing, generating complex data inputs is frequently performed using a grammar-based specification. For combinatorial reasons, an exhaustive generation of the data - of a given size - is practically impossible, and most approaches are either based on random techniques or on coverage criteria. In this paper, we show how to combine these two techniques by biasing the random generation in order to optimise the probability of satisfying a coverage criterion.

关键词： Random testing grammar-based testing

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Growing A Test Corpus with Bonsai Fuzzing 21

Growing A Test Corpus with Bonsai Fuzzing

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43rd IEEE/ACM International Conference on Software Engineering - Software Engineering in Practice (ICSE-SEIP) / 43rd ACM/IEEE International Conference on Software Engineering - New Ideas and Emerging Results (ICSE-NIER)

作者： Vikram, Vasudev Padhye, Rohan Sen, Koushik Univ Calif Berkeley Berkeley CA 94720 USA Carnegie Mellon Univ Pittsburgh PA 15213 USA

ISBN: (纸本)9780738113197

This paper presents a coverage-guided grammar-based fuzzing technique for automatically synthesizing a corpus of concise test inputs. We walk-through a case study of a compiler designed for education and the corresponding problem of generating meaningful test cases to provide to students. The prior state-of-the-art solution is a combination of fuzzing and test-case reduction techniques such as variants of delta-debugging. Our key insight is that instead of attempting to minimize convoluted fuzzer-generated test inputs, we can instead grow concise test inputs by construction using a form of iterative deepening. We call this approach bonsai fuzzing. Experimental results show that bonsai fuzzing can generate test corpora having inputs that are 16-45% smaller in size on average as compared to a fuzz-then-reduce approach, while achieving approximately the same code coverage and fault-detection capability.

关键词： test-case generation grammar-based testing fuzz testing small scope hypothesis test-case reduction

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Exploiting Model Morphology for Event-based testing

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IEEE TRANSACTIONS ON SOFTWARE ENGINEERING 2015年第2期41卷 113-134页

作者： Belli, Fevzi Beyazit, Mutlu Univ Paderborn Dept Elect Engn & Informat Technol D-33098 Paderborn Germany Izmir Inst Technol Dept Comp Engn Izmir Turkey Yasar Univ Dept Comp Engn Izmir Turkey

Model-based testing employs models for testing. Model-based mutation testing (MBMT) additionally involves fault models, called mutants, by applying mutation operators to the original model. A problem encountered with MBMT is the elimination of equivalent mutants and multiple mutants modeling the same faults. Another problem is the need to compare a mutant to the original model for test generation. This paper proposes an event-based approach to MBMT that is not fixed on single events and a single model but rather operates on sequences of events of length k >= 1 and invokes a sequence of models that are derived from the original one by varying its morphology based on k. The approach employs formal grammars, related mutation operators, and algorithms to generate test cases, enabling the following: (1) the exclusion of equivalent mutants and multiple mutants;(2) the generation of a test case in linear time to kill a selected mutant without comparing it to the original model;(3) the analysis of morphologically different models enabling the systematic generation of mutants, thereby extending the set of fault models studied in related literature. Three case studies validate the approach and analyze its characteristics in comparison to random testing and another MBMT approach.

关键词： Model-based mutation testing grammar-based testing (model) morphology mutant selection test generation

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The optimisation of stochastic grammars to enable cost-effective probabilistic structural testing

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JOURNAL OF SYSTEMS AND SOFTWARE 2015年 103卷 296-310页

作者： Poulding, S. Alexander, R. Clark, J. A. Hadley, M. J. Blekinge Inst Technol S-37179 Karlskrona Sweden Univ York York YO10 5DD N Yorkshire England

The effectiveness of statistical testing, a probabilistic structural testing strategy, depends on the characteristics of the probability distribution from which test inputs are sampled. Metaheuristic search has been shown to be a practical method of optimising the characteristics of such distributions. However, the applicability of the existing search-based algorithm is limited by the requirement that the software's inputs must be a fixed number of ordinal values. In this paper we propose a new algorithm that relaxes this limitation and so permits the derivation of probability distributions for a much wider range of software. The representation used by the new algorithm is based on a stochastic grammar supplemented with two novel features: conditional production weights and the dynamic partitioning of ordinal ranges. We demonstrate empirically that a search algorithm using this representation can optimise probability distributions over complex input domains and thereby enable costeffective statistical testing, and that the use of both conditional production weights and dynamic partitioning can be beneficial to the search process. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Search-based software engineering Software testing grammar-based testing

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Verifying Code Generation Tools for the B-Method Using Tests: A Case Study 1

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9th International Conference on Tests and Proofs (TAP) Held as Part of Conference on Software Technologies - Applications and Foundations (STAF)

作者： Moreira, Anamaria M. Hentz, Cleverton Deharbe, David de Matos, Ernesto C. B. Souza Neto, Joao B. de Medeiros, Valerio, Jr. Univ Fed Rio Grande do Norte BR-59072970 Natal RN Brazil Univ Fed Rio de Janeiro Rio De Janeiro Brazil

ISBN: (数字)9783319212159

ISBN: (纸本)9783319212159;9783319212142

In this paper, we present a case study where two code generators for the B-Method were validated using software testing techniques. Our testing strategy is a combination of grammar-based testing (GBT) and Model-based testing (MBT) techniques. The strategy consists of two steps. In the first step, grammar-based coverage criteria are used to generate a wide and meaningful set of test input models to validate the parsing capabilities of the code generators. In the second step, a MBT tool is used to validate the correctness of the output produced by these tools. The MBT tool generates a set of tests based on the same input model used by the code generation tools. The generated code is considered correct (consistent with the input model) if it passes this set of tests. Using this testing strategy, we were able to find problems in both code generation tools with moderate effort.

关键词： Model-based testing grammar-based testing B-Method Code generation

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Adding Contextual Guidance to the Automated Search for Probabilistic Test Profiles

Adding Contextual Guidance to the Automated Search for Proba...

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

作者： Poulding, Simon Waeselynck, Helene Univ York Dept Comp Sci York YO10 5DD N Yorkshire England Univ Toulouse LAAS CNRS Toulouse France

ISBN: (纸本)9780769551852

Statistical testing is a probabilistic approach to test data generation that has been demonstrated to be very effective at revealing faults. Its premise is to compensate for the imperfect connection between coverage criteria and the faults to be revealed by exercising each coverage element several times with different random data. The cornerstone of the approach is the often complex task of determining a suitable input profile, and recent work has shown that automated metaheuristic search can be a practical method of synthesising such profiles. The starting point of this paper is the hypothesis that, for some software, the existing grammar-based representation used by the search algorithm fails to capture important relationships between input arguments and this can limit the fault-revealing power of the synthesised profiles. We provide evidence in support of this hypothesis, and propose a solution in which the user provides some basic contextual knowledge to guide the search. Empirical results for two case studies are promising: knowledge gained by a very straightforward review of the software-undertest is sufficient to dramatically increase the efficacy of the profiles synthesised by search.

关键词： grammar-based testing search-based software testing statistical testing

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