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Scalable satisfiability checking and test data generation from modeling diagrams

AUTOMATED SOFTWARE ENGINEERING 2009年第1期16卷 73-99页

作者： Smaragdakis, Yannis Csallner, Christoph Subramanian, Ranjith Univ Massachusetts Amherst MA 01003 USA Univ Texas Arlington Arlington TX 76019 USA Find Com Mountain View CA USA

We explore the automatic generation of test data that respect constraints expressed in the Object-Role Modeling (ORM) language. ORM is a popular conceptual modeling language, primarily targeting database applications, with significant uses in practice. The general problem of even checking whether an ORM diagram is satisfiable is quite hard: restricted forms are easily NP-hard and the problem is undecidable for some expressive formulations of ORM. Brute-force mapping to input for constraint and SAT solvers does not scale: state-of-the-art solvers fail to find data to satisfy uniqueness and mandatory constraints in realistic time even for small examples. We instead define a restricted subset of ORM that allows efficient reasoning yet contains most constraints overwhelmingly used in practice. We show that the problem of deciding whether these constraints are consistent (i.e., whether we can generate appropriate test data) is solvable in polynomial time, and we produce a highly efficient (interactive speed) checker. Additionally, we analyze over 160 ORM diagrams that capture data models from industrial practice and demonstrate that our subset of ORM is expressive enough to handle their vast majority.

关键词： ORM Modeling testing databases NP-hardness ORM- test data generation

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Effective test data generation using probabilistic networks

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INTERNATIONAL JOURNAL OF COMPUTING SCIENCE AND MATHEMATICS 2020年第4期11卷 357-371页

作者： Feyzi, Farid Parsa, Saeed Iran Univ Sci & Technol Dept Comp Engn Tehran Iran

This paper presents a novel test data generation method called Bayes-TDG. It is based on principles of Bayesian networks (BNs) and provides the possibility of making inference from probabilistic data in the model to increase the prime path coverage ratio (PPCR) for a given program under test (PUT). In this regard, a new program structure-based probabilistic network, TDG-NET, is proposed that is capable of modelling the conditional dependencies among the program basic blocks (BBs) in one hand and conditional dependencies of the transitions between its BBs and input parameters on the other hand. To achieve failure-detection effectiveness, we propose a path selection strategy that works based on the predicted outcome of generated test cases. So, we mitigate the need for a human oracle, and the generated test suite could be directly used in fault localisation. Several experiments are conducted to evaluate the performance of Bayes-TDG. The results reveal that the method is promising and the generated test suite could be quite effective.

关键词： software testing Bayesian net test data generation adaptive random testing fault detection

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Application of Dynamic Slicing in test data generation

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Tsinghua Science and Technology 2007年第S1期12卷 150-155页

作者：郭涑炜赵瑞莲李立健 Computer Science Department Beijing University of Chemical Technology Information Technique Academe Tsinghua UniversityBeijing 100084China Institute of Automation Chinese Academy of Sciences

The program slicing technique is employed to calculate the current values of the variables at some interest points in software test data generation. This paper introduces the concept of statement domination to represent the multiple nests, and presents a dynamic program slice algorithm based on forward analysis to generate dynamic slices. In the approach, more attention is given to the statement itself or its domination node, so computing program slices is more easy and accurate, especially for those programs with multiple nests. In addition, a case study is discussed to illustrate our algorithm. Experimental results show that the slicing technique can be used in software test data generation to enhance the effectiveness.

关键词： dynamic program slicing test data generation forward analysis

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Dynamic input domain reduction for test data generation with iterative partitioning

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INTERNATIONAL JOURNAL OF COMPUTATIONAL SCIENCE AND ENGINEERING 2020年第1期21卷 60-68页

作者： Nikravan, Esmaeel Parsa, Saeed Iran Univ Sci & Technol Dept Comp Engn Tehran Iran

A major difficulty concerning test data generation for white box testing is to detect the domain of input variables covering a certain path. With this aim, a new concept, domain coverage, is introduced in this article. In search of appropriate input variable subdomains, covering a desired path, the domains are randomly partitioned as far as subdomains whose boundaries satisfy the path constraints are found. When partitioning, the priority is given to those subdomains whose boundary variables do not satisfy the path constraints. Representing the relation between the subdomains and their parents as a directed acyclic graph, an Euler/Venn reasoning system could be applied to select the most appropriate subdomains. To evaluate our proposed path oriented test data generation method, the results of applying the method to six known benchmark programs, triangle, GCD, calday, shellsort, quicksort and heapsort, is presented.

关键词： random testing test data generation Euler Venn diagram directed acyclic graph DAG

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test data generation for program units using a game with a purpose

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SCIENTIA IRANICA 2023年第5期30卷 1670-1686页

作者： Moosavi, Sh. Vahidi-Asl, M. Haghighi, H. Shahid Beheshti Univ Fac Comp Sci & Engn Tehran Iran

Today, several methods have been presented to automate test data generation;because of the low maturity level of automatic methods, this is still widely carried out by humans in industry. Hence, the challenge is finding approaches in which humans could generate test data through more attractive, faster, and cheaper ways. To achieve this, one approach is using a Game With A Purpose (GWAP) in test data generation. In our previous work, we introduced two games called Rings and Greenify, by which many inexpensive players with no special technical abilities become engaged in test data generation. This paper presents an entirely new GWAP for test data generation called Quest Of Treasure Explorer (QOTE). QOTE provides a different gameplay and has certain advantages compared to prior games, including faster generation of test data, easier puzzles, narration, etc. Experimental results have shown that QOTE outperforms prior games in two aspects: game quality and capability of test data generation. We have also conducted an experiment based on mutation analysis to further evaluate the test data generation capabilities of QOTE compared to four automatic approaches. According to this experiment, QOTE outperforms the four competitors regarding average mutation scores. (c) 2023 Sharif University of Technology. All rights reserved.

关键词： Software testing test data generation Serious game Game with a purpose Human-based computation game

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Design-Model-Based test data generation for database Applications

Design-Model-Based Test Data Generation for Database Applica...

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23rd IEEE International Symposium on Software Reliability Engineering Workshops (ISSREW)

作者： Tanno, Haruto Zhang, Xiaojing Hoshino, Takashi NTT Software Innovat Ctr Minato Ku Tokyo 1080075 Japan

ISBN: (纸本)9780769549286;9781467350488

This research focuses on testing enterprise systems, more concretely on how to automatically generate the initial test data to be entered into the relational database to support each test case. Existing approaches cannot generate initial database entries to suit complicated business logic states such as reading the database more than once, searching the database by partial string matching, or setting primary and foreign key constraints on the database scheme. To solve these limitations, we propose a method for initial database generation. This method adopts a design model that can handle the complicated business logic states given above, and from this design model, our method generates appropriate initial database entries;it employs a step-by-step approach using the constraints extracted from the design model. The proposed method enables us to automatically generate initial database entries for a wide range of test cases and thus supports the testing of industrial-level enterprise systems. Using three industrial-level enterprise systems as case studies, we confirm that our method properly generated initial databases for 72% to 100% of the test cases in which an initial database was needed.

关键词： test data generation model based testing database application test case generation design model

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On How Characteristics that Hinder test data generation Using Symbolic Execution Combine: An Analysis of the SF100 Benchmark 35

On How Characteristics that Hinder Test Data Generation Usin...

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35th International Conference of the Chilean-Computer-Science-Society (SCCC)

作者： Eler, Marcelo Medeiros Endo, Andre Takeshi Durelli, Vinicius H. S. Eler, Danilo Medeiros EACH USP Sao Paulo SP Brazil UTFPR Cornelio Procopio PR Brazil Univ Sao Paulo Sao Carlos SP Brazil FCT UNESP Presidente Prudente SP Brazil

ISBN: (纸本)9781509033393

Symbolic execution has made great strides in the last two decades. However, some characteristics of programs still pose significant challenges to test data generation techniques that use symbolic execution and constraint solving. These challenges present themselves in the form of path explosion, constraint complexity, dependency, and exception-dependent paths. The few studies conducted to date to examine the distribution of such characteristics only investigate them separately. We posit that understanding how the combination of these characteristics appear in real world software may provide a more in-depth knowledge of the limitations of current tools and test data generation techniques. Thus, we analyzed a benchmark comprising 100 open source Java programs to get some insight into the frequency of methods that have combinations of the studied characteristics and the distribution of methods whose path constraints share similar structures.

关键词： symbolic execution test data generation visualization metric analysis

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GA-based Automatic test data generation for UML State Diagrams with Parallel Paths

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13th International Conference on Advanced Design and Manufacture

作者： Doungsa-ard, C. Dahal, K. Hossain, A. Suwannasart, T. Chiang Mai Univ Coll Art Media & Technol Chiang Mai 50000 Thailand Univ Bradford Sch Informat Bradford W Yorkshire England Chulalongkorn Univ Dept Comp Engn Bangkok Thailand

ISBN: (纸本)9781848002401

Automatic test data generation from a software specification prepares test cases for software developers before their code development phase. Having test cases before coding, helps the developers to control their code to conform to the specification. In state-based specifications, paths from the initial state to the final state may be varied, this is called parallel paths. In order to generate test data which cover all behaviors in the specification, test data for each parallel path should be generated. This paper proposes an enhanced genetic algorithm(GA)-based approach to resolve the parallel paths from the UML state machine diagram. The proposed approach is improved from our previous study which uses a GA based test data generation method for only one path. The approach identifies parallel paths to cover all transitions. GA evolves a number of suitable test data sets - one test data set for each parallel path. The best test data for each parallel path are picked and used for calculating the overall coverage test data. The experimental results show improved coverage results with the enhanced approach for a number of case studies with parallel paths.

关键词： test data generation UML state machine diagram Genetic algorithm

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A test data generation tool for unit testing of C programs

A test data generation tool for unit testing of C programs

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6th International Conference on Quality Software

作者： Xu, Zhongxing Zhang, Jian Chinese Acad Sci Grad Univ Inst Software State Key Lab Comp Sci Beijing 100864 Peoples R China

ISBN: (纸本)0769527183

This paper describes a prototype tool, called SimC, which automatically generates test data for unit testing of C programs. The tool symbolically simulates the execution of the given program. It simulates pointer operations precisely. This makes it capable of generating test data for programs involving pointer and structure operations. Experiments on real-world programs including the GNU coreutils are presented. Some trade-offs of simulation schemes are also discussed.

关键词： test data generation symbolic execution pointer operation unit testing

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A test data generation for Performance testing in Massive data Processing Systems 13th

A Test Data Generation for Performance Testing in Massive Da...

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13th International Scientific Conference on Future Information Technology (FutureTech)

作者： Kim, Sunkyung Park, JiSu Kim, Kang Hyoun Shon, Jin Gon Korea Natl Open Univ Grad Sch Dept Comp Sci Seoul South Korea Kyonggi Univ Div Gen Studies Suwon South Korea

ISBN: (纸本)9789811313288;9789811313271

Whether a computer system can process its intended load can be checked through performance testing. The test can be done most accurately in the real system. However, it is impossible to test directly to the real system because of the possibility of corrupting or leaking data. Consequently, the tests have been carried out on the other system which is called a test system. In order to obtain correct results from the tests, the test system has to behave like the real system. There are many factors for the test system to act like the real one. The important factors regarding data are the amount and distribution of the test data stored in the system. This paper provides the method that generates the proper test data using frequency distribution and also implements and experiments a test data generator.

关键词： test data generation Performance testing Automatic data generation

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