Open Access Open Access  Restricted Access Subscription or Fee Access

Fault Detection in Testing – A Survey Approach

S. Preetha, Dr. M. Punithavalli


Software testing is an important but expensive process because about fifty percent of the total development cost is spent for it. However, this part is the first one to miss by software developers if there is a limited time to complete the project. Tests are commonly generated from program source code, graphical models of software(such as control flow graphs), and specifications / requirements. Creating test cases manually is a huge work for software developers. It is time consuming and error prone. A solution which automatically generates test cases and test data can help the software developers to create test cases from software designs/models in early stage of the software development (before coding). High quality software cannot be done without high quality testing. Heuristic techniques can be applied for creating quality test data. A fault is defined as a textual problem with the code resulting from a mental mistake by the programmer or designer. A fault is also called a defect. Fault-based testing refers to the collection of information on whether classes of software faults (or defects) exist in a program. Since testing can only prove the existence of errors and not their absence, this testing approach is a very sound one. In this paper we describe the methods for evaluating the fault, methods for characterizing faults.


Software testing, Fault, Test cases.

Full Text:



ANDREWS, J. H., BRIAND, L. C., AND LABICHE, Y. Is mutation an appropriate tool for testing experiments? In Proceedings of the 27th International Conference on Software Engineering (2005), pp. 402–411.

ANDREWS, J. H., BRIAND, L. C., LABICHE, Y., AND NAMIN, A.S. Using mutation analysis for assessing and comparing testing coverage criteria. IEEE Trans. Softw. Eng. 32, 8 2006), 608–624.

BASILI, V. R., AND SELBY, R. W. Comparing the effectiveness of software testing strategies. IEEE Trans. Softw. Eng. 13, 12 (1987),1278–1296.

DINH-TRONG, T., GHOSH, S., FRANCE, R., BAUDRY, B., AND FLEURY, F. A taxonomy of faults for UML designs. In Proceedings of the 2nd MoDeVa workshop - Model design and validation (2005).

ELBAUM, S., GABLE, D., AND ROTHERMEL, G. Understanding and measuring the sources of variation in the prioritization of regression test suites. In Proceedings of the 7th IEEE International Software Metrics Symposium (Apr. 2001), pp. 169–179.

GRAVES, T. L., HARROLD, M. J., KIM, J. -M., PORTER, A., AND ROTHERMEL, G. An empirical study of regression test selection techniques. ACM Trans. Softw. Eng. Methodol. 10, 2 (2001), 184–208.

HARROLD, M. J., OFFUTT, A. J., AND TEWARY, K. An approach to fault modeling and fault seeding using the program dependence graph. J.Syst. Softw. 36, 3 (1997), 273–295.

HOWDEN, W. E. Reliability of the path analysis testing strategy. IEEE Trans. Softw. Eng. SE-2, 3 (1976), 208–215.

HUTCHINS, M., FOSTER, H., GORADIA, T., AND OSTRAND, T. Experiments on the effectiveness of dataflow- and control flow-based test adequacy criteria. In Proceedings of the16th International Conference on Software Engineering (1994), pp. 191–200.

MCMASTER, S., AND MEMON, A. M. Fault detection probability analysis for coverage based test suite reduction. In Proceedings of the 21st IEEE International Conference on Software Maintenance (Paris,France, 2007), IEEE Computer Society.

MICHAEL, C. C., AND VOAS, J. Problems of accuracy in the prediction of software quality from directed tests. In Proceedings of the International Conference on Testing Computer Software (1997).

MORELL, L. J. A theory of fault-based testing. IEEE Trans. Softw.Eng. 16, 8 (1990), 844–857.

MORGAN, J. A., KNAFL, G. J., AND WONG, W. E. Predicting fault detection effectiveness. In Proceedings of the 4th IEEE International Software Metrics Symposium (1997), p. 82.

MUNSON, J. C., AND NIKORA, A. P. Toward a quantifiable definition of software faults. In ISSRE ’02: Proceedings of the 13th International Symposium on Software Reliability Engineering (Washington, DC,USA, 2002), IEEE Computer Society, pp. 388–395.

MUSA, J. D. Operational profiles in software-reliability engineering.IEEE Softw. 10, 2 (1993), 14–32.

OFFUTT, A. J., AND HAYES, J. H. A semantic model of program faults. In Proceedings of the International Symposium on Software Testing and Analysis (1996), pp. 195–200.

RICHARDSON, D. J., AND THOMPSON, M. C. An analysis of test data selection criteria using the RELAY model of fault detection. IEEE Trans. Softw. Eng. 19, 6 (1993), 533–553.

ROTHERMEL, G., ELBAUM, S., MALISHEVSKY, A. G., KALLAKURI, P., AND QIU, X. On test suite composition and costeffective regression testing. ACM Trans. Softw. Eng. Methodol. 13, 3(2004), 277–331.

STRECKER, J., AND MEMON, A. M. Relationships between test suites, faults, and fault detection in GUI testing. In Proceedings of the 1st International Conference on Software Testing, Verification, and Validation (Apr. 2008).

VOAS, J. M. Pie: A dynamic failure-based technique. IEEE Trans.Softw. Eng. 18, 8 (1992), 717–727.

XIE, Q., AND MEMON, A. Studying the characteristics of a ‘good” GUI test suite. In Proceedings of the 17th IEEE International Symposium on Software Reliability engineering (Nov. 2006).

OSTRAND, T. J., WEYUKER, E. J., AND BELL, R. M. Predicting the location and number of faults in large software systems. IEEE Trans. Softw. Eng. 31, 4 (2005), 340–355.

R. DeMillo, R. Lipton, and F. Sayward, “Hints on Test Data Selection:Help for the Practicing Programmer, ” Computer, vol. 11, no. 4, 1978,pp. 34–41.

B. Baudry et al., “Trustable Components: Yet Another Mutation-Based Approach,” Proc. 1st Symp. Mutation Testing, Kluwer Academic Publishers, 2000, pp. 69–76.

S. -W. Kim, J. A. Clark, and J. A. McDermid, “Investigating the Effectiveness of Object- Oriented Testing Strategies Using the Mutation Method, ” Software Testing, Verification and Reliability, vol. 11, no. 4,2001, pp. 207–225.

A. J. Offutt et al., “An Experimental Evaluation of Data Flow and Mutation Testing, ” Software: Practice and Experience, vol. 26, no. 2,1996, pp. 165–176. {Fault revealing power]

B. J. Choi and A. P. Mathur. Use of fifth generation computers for high performance reliable software testing. Technical report SERC-TR-72- P,Software Engineering Research Center, Purdue University,WestLafayette IN, April 1990.

E. W. Krauser, A. P. Mathur, and V. Rego. High performance testing on SIMD machines. In Proceedings of the Second Workshop on Software.

Aditya P. Mathur and E. W. Krauser. Modeling mutation on a vector processor. In Proceedings of the 10th International Conference on Software Engineering, pages 154{161, Singapore, April 1988. IEEE Computer Society Press.

Aditya P. Mathur and E. W. Krauser. Mutant unification for improved vectorization. Technical report SERC-TR-14-P, Software Engineering Research Center, Purdue University, West Lafayette IN, April 1988.

R. A. DeMillo, E. W. Krauser, R. J. Martin, A. J. Offutt and E. H.Spafford, `The Mothra tool set', Proceedings of the Hawaii International Conference on System Sciences, Kailua-Kona, HI, January 1989.

J. Offutt, and E. J. Seaman, `Using symbolic execution to aid automatic test data generation', Proceedings of the IEEE 1990 Annual Conference on Computer Assurance (COMPASS 90), Gaithersburg, MD, June 1990.

W. M. Craft, `Detecting Equivalent Mutants Using Compiler Optimization Techniques', Master's thesis, Department of Computer Science, Clemson University, 1989.

R. A. DeMillo, D. S. Guindi, K. N. King, W. M. McCracken, and A. J.Offutt, `An extended overview of the Mothra software testing environment', Proceedings of the IEEE Second Workshop on Software Testing, Verification and Analysis, Banff Alberta, July 1988.

K. N. King and A. J. Offutt. A Fortran language system for mutationbased software testing. Software{Practice and Experience,21(7):685{718, July 1991.

L. J. Morell. A Theory of Error-Based Testing. PhD thesis, University of Maryland, College Park MD, 1984. Technical Report TR-1395.

B. Marick. The weak mutation hypothesis. In Proceedings of the Third Symposium on Software Testing, Analysis, and Verification, pages 190{199, Victoria, British Columbia, Canada, October 1991. IEEE Computer Society Press.

B. Marick. Using Weak Mutation with GCT. Testing Foundations,Champaign Illinois, 1993.

D. J. Richardson and M. C. Thompson. The relay model for error detection and its application. In Proceedings of the Second Workshop on Software Testing, Verification, and Analysis, pages 223{230, Ban_Alberta, July 1988. IEEE Computer Society Press.

J. R. Horgan and A. P. Mathur. Weak mutation is probably strong mutation. Technical report SERC-TR-83-P, Software Engineering Research Center, Purdue University, West Lafayette IN, December 1990.


  • There are currently no refbacks.

Creative Commons License
This work is licensed under a Creative Commons Attribution 3.0 License.