An address mapping approach for test data generation of dynamic linked structures

Sai-ngern, Sittisak; Lursinsap, Chidchanok; Sophatsathit, Peraphon

doi:10.1016/j.infsof.2004.08.004

Cited by 10 publications

(7 citation statements)

References 19 publications

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“…Although some research has been proposed some EFSM-based testing techniques, automated test case generation on an EFSM suffers from a number of problems. [38,39] all-uses -Expanding EFSM to FSM --Bourhfir [45] du-path UIO Symbolic evaluation Random -Ural [42] [60] all-transition -Heuristics Search Symbolic Execution structural program testing [14][15][16][17][18], However, the case of EFSM is more complexity than structural program since a transition in an EFSM may be triggered by three types of enabling conditions: the input event, the current state and a boolean expression involving the context variables [19], and multi-transitions or self-loops may be exist between two states or single state, respectively. This feature also results in a somehow different between EFSM-based and traditional structure-based test case generation.…”

Section: Efsm-based Test Case Generationmentioning

confidence: 99%

EFSM-Based Test Case Generation: Sequence, Data, and Oracle

Yang

Chen

Zhang

et al. 2015

Int. J. Soft. Eng. Knowl. Eng.

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Model-based testing has been intensively and extensively studied in the past decades. Extended Finite State Machine (EFSM) is a widely used model of software testing in both academy and industry. This paper provides a survey on EFSM-based test case generation techniques in the last two decades. All techniques in EFSM-based test case generation are mainly classified into three parts: test sequence generation, test data generation, and test oracle construction. The key challenges, such as coverage criterion and feasibility analysis in EFSM-based test case generation are discussed. Finally, we summarize the research work and present several possible research areas in the future.

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Section: Efsm-based Test Case Generationmentioning

confidence: 99%

EFSM-Based Test Case Generation: Sequence, Data, and Oracle

Yang

Chen

Zhang

et al. 2015

Int. J. Soft. Eng. Knowl. Eng.

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“…Williams et al [5], Sai-ngern et al [21] and Sen [7] address the problem of generating test data for C functions with dynamic structures by using symbolic execution and constraint solving techniques. In their approaches, constraints on input values, representing preconditions, force pointing relationships in generated tests.…”

Section: Related Workmentioning

confidence: 99%

Modelling Dynamic Memory Management in Constraint-Based Testing

Charreteur

Botella

Gotlieb

2007

Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (TAICPART-MUTATION 2007)

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Constraint-Based Testing (CBT) is the process of generating test cases against a testing objective by using constraint solving techniques. When programs contain dynamic memory allocation and loops, constraint reasoning becomes challenging as new variables and new constraints are created during the test data generation process. In this paper, we address this problem by proposing a new constraint model of C programs based on operators that model dynamic memory management. These operators apply deduction rules on abstract states of the memory allowing so to enhance the constraint reasoning process that permits to generate test data for these programs. We illustrate our approach on structural testing of a complex program that contains dynamic memory allocation/deallocation, structures and loops. An implementation is in progress and first experimental results obtained on this program show the highly deductive potential of the approach.

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“…As a drawback, this approach cannot detect unsatisfiability of selected paths. More recently, Visvanathan and Gupta in [28], Marre et al in [29] and Sai-ngern et al [30] addressed the problem of generating test data for C functions with pointers as input parameters by using symbolic execution and constraint solving techniques. In their approaches, pointer relationships are handled with constraints on input values and aliasing problems occur only within input data structures.…”

Section: Related Workmentioning

confidence: 99%

Goal-oriented test data generation for pointer programs

Gotlieb

Denmat

Botella³

2007

Information and Software Technology

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Goal-oriented test data generation; Constraint Logic Programming; Static Single Assignment formInternational audienceAutomatic test data generation leads to the identification of input values on which a selected path or a selected branch is executed within a program (path-oriented vs goal-oriented methods). In both cases, several approaches based on constraint solving exist, but in the presence of pointer variables only path-oriented methods have been proposed. Pointers are responsible for the existence of conditional aliasing problems that usually provoke the failure of the goal-oriented test data generation process. In this paper, we propose an overall constraint-based method that exploits the results of an intraprocedural points-to analysis and provides two specific constraint combinators for automatically generating goal-oriented test data. This approach correctly handles multi-levels stack-directed pointers that are mainly used in C programs. The method has been fully implemented in the test data generation tool INKA and first experiences in applying it to a variety of existing programs are presented

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An address mapping approach for test data generation of dynamic linked structures

Cited by 10 publications

References 19 publications

EFSM-Based Test Case Generation: Sequence, Data, and Oracle

EFSM-Based Test Case Generation: Sequence, Data, and Oracle

Modelling Dynamic Memory Management in Constraint-Based Testing

Goal-oriented test data generation for pointer programs

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