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CUTE: a concolic unit testing engine for C

Authors:

Gul AghaAuthors Info & Claims

ACM SIGSOFT Software Engineering Notes, Volume 30, Issue 5

Pages 263 - 272

https://doi.org/10.1145/1095430.1081750

Published: 01 September 2005 Publication History

Abstract

In unit testing, a program is decomposed into units which are collections of functions. A part of unit can be tested by generating inputs for a single entry function. The entry function may contain pointer arguments, in which case the inputs to the unit are memory graphs. The paper addresses the problem of automating unit testing with memory graphs as inputs. The approach used builds on previous work combining symbolic and concrete execution, and more specifically, using such a combination to generate test inputs to explore all feasible execution paths. The current work develops a method to represent and track constraints that capture the behavior of a symbolic execution of a unit with memory graphs as inputs. Moreover, an efficient constraint solver is proposed to facilitate incremental generation of such test inputs. Finally, CUTE, a tool implementing the method is described together with the results of applying CUTE to real-world examples of C code.

References

[1]

T. Ball. Abstraction-guided test generation: A case study. Technical Report MSR-TR-2003-86, Microsoft Research.

[2]

C. W. Barrett and S. Berezin. CVC Lite: A new implementation of the cooperating validity checker. In Proc. 16th International Conference on Computer Aided Verification, pages 515--518, July 2004.

[3]

D. Beyer, A. J. Chlipala, T. A. Henzinger, R. Jhala, and R. Majumdar. Generating Test from Counterexamples. In Proc. of the 26th ICSE, pages 326--335, 2004.

Digital Library

[4]

D. Bird and C. Munoz. Automatic Generation of Random Self-Checking Test Cases. IBM Systems Journal, 22(3):229--245, 1983.

Digital Library

[5]

C. Boyapati, S. Khurshid, and D. Marinov. Korat: Automated testing based on Java predicates. In Proc. of International Symposium on Software Testing and Analysis, pages 123--133, 2002.

Digital Library

[6]

C. Cadar and D. Engler. Execution generated test cases: How to make systems code crash itself. In Proc. of SPIN Workshop, 2005.

Digital Library

[7]

K. Claessen and J. Hughes. Quickcheck: A lightweight tool for random testing of Haskell programs. In Proc. of 5th ACM SIGPLAN International Conference on Functional Programming (ICFP), pages 268--279, 2000.

Digital Library

[8]

C. Csallner and Y. Smaragdakis. JCrasher: an automatic robustness tester for Java. Software: Practice and Experience, 34:1025--1050, 2004.

Digital Library

[9]

C. Csallner and Y. Smaragdakis. Check 'n' Crash: Combining static checking and testing. In 27th International Conference on Software Engineering, 2005.

Digital Library

[10]

J. E. Forrester and B. P. Miller. An Empirical Study of the Robustness of Windows NT Applications Using Random Testing. In Proceedings of the 4th USENIX Windows System Symposium, 2000.

Digital Library

[11]

P. Godefroid, N. Klarlund, and K. Sen. DART: Directed automated random testing. In Proc. of the ACM SIGPLAN 2005 Conference on Programming Language Design and Implementation (PLDI), 2005.

Digital Library

[12]

W. Grieskamp, Y. Gurevich, W. Schulte, and M. Veanes. Generating finite state machines from abstract state machines. In Proc. International Symposium on Software Testing and Analysis, pages 112--122, 2002.

Digital Library

[13]

N. Gupta, A. P. Mathur, and M. L. Soffa. Generating test data for branch coverage. In Proc. of the International Conference on Automated Software Engineering, pages 219--227, 2000.

Digital Library

[14]

S. Khurshid, C. S. Pasareanu, and W. Visser. Generalized symbolic execution for model checking and testing. In Proc. 9th Int. Conf. on TACAS, pages 553--568, 2003.

Digital Library

[15]

B. Korel. A dynamic Approach of Test Data Generation. In IEEE Conference on Software Maintenance, pages 311--317, November 1990.

[16]

E. Larson and T. Austin. High coverage detection of input-related security faults. In Proc. of the 12th USENIX Security Symposium (Security '03), Aug. 2003.

Digital Library

[17]

lp_solve. http://groups.yahoo.com/group/lp_solve/.

[18]

J. McCarthy and J. Painter. Correctness of a compiler for arithmetic expressions. In Proceedings of Symposia in Applied Mathematics. AMS, 1967.

[19]

G. C. Necula, S. McPeak, S. P. Rahul, and W. Weimer. CIL: Intermediate Language and Tools for Analysis and transformation of C Programs. In Proceedings of Conference on compiler Construction, pages 213--228, 2002.

Digital Library

[20]

J. Offut and J. Hayes. A Semantic Model of Program Faults. In Proc. of ISSTA'96, pages 195--200, 1996.

Digital Library

[21]

C. Pacheco and M. D. Ernst. Eclat: Automatic generation and classification of test inputs. In 19th European Conference Object-Oriented Programming, 2005.

Digital Library

[22]

Parasoft. Jtest manuals version 6.0. Online manual, February 2005. http://www.parasoft.com/.

[23]

C. S. Pasareanu, M. B. Dwyer, and W. Visser. Finding feasible counter-examples when model checking abstracted java programs. In Proc. of TACAS'01, pages 284--298, 2001.

Digital Library

[24]

K. Sen, D. Marinov, and G. Agha. CUTE: A concolic unit testing engine for C. Technical Report UIUCDCS-R-2005-2597, UIUC, 2005.

[25]

SGLIB. http://xref-tech.com/sglib/main.html.

[26]

Valgrind. http://valgrind.org/.

[27]

W. Visser, C. S. Pasareanu, and S. Khurshid. Test input generation with Java PathFinder. In Proc. 2004 ACM SIGSOFT International Symposium on Software Testing and Analysis, pages 97--107, 2004.

Digital Library

[28]

S. Visvanathan and N. Gupta. Generating test data for functions with pointer inputs. In 17th IEEE International Conference on Automated Software Engineering, 2002.

Digital Library

[29]

T. Xie, D. Marinov, and D. Notkin. Rostra: A framework for detecting redundant object-oriented unit tests. In Proc. 19th IEEE International Conference on Automated Software Engineering, pages 196--205, Sept. 2004.

Digital Library

[30]

T. Xie, D. Marinov, W. Schulte, and D. Notkin. Symstra: A framework for generating object-oriented unit tests using symbolic execution. In Proc. of the Tools and Algorithms for the Construction and Analysis of Systems, 2005.

Digital Library

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https://doi.org/10.1007/s10515-025-00496-7
Zlatkin IFedyukovich G(2025)Leveraging Program Structure for Test Case GenerationAutomated Technology for Verification and Analysis10.1007/978-3-031-78750-8_7(137-157)Online publication date: 12-Feb-2025
https://doi.org/10.1007/978-3-031-78750-8_7
Erdei ZTóth MBozó I(2024)Supporting the debugging of Erlang programs by symbolic executionActa Universitatis Sapientiae, Informatica10.47745/ausi-2024-000416:1(44-61)Online publication date: 2-Oct-2024
https://doi.org/10.47745/ausi-2024-0004
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Index Terms

CUTE: a concolic unit testing engine for C
1. Software and its engineering
  1. Software creation and management
    1. Software verification and validation
      1. Software defect analysis
        Software testing and debugging

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Published In

cover image ACM SIGSOFT Software Engineering Notes

ACM SIGSOFT Software Engineering Notes Volume 30, Issue 5

September 2005

462 pages

ISSN:0163-5948

DOI:10.1145/1095430

Issue’s Table of Contents

ESEC/FSE-13: Proceedings of the 10th European software engineering conference held jointly with 13th ACM SIGSOFT international symposium on Foundations of software engineering
September 2005
402 pages
ISBN:1595930140
DOI:10.1145/1081706
General Chair:
Michel Wermelinger
The Open University, UK
,
Program Chair:
Harald C. Gall
University of Zurich, Switzerland

Copyright © 2005 ACM.

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Publication History

Published: 01 September 2005

Published in SIGSOFT Volume 30, Issue 5

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https://doi.org/10.1007/978-3-031-78750-8_7
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https://doi.org/10.47745/ausi-2024-0004
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