Y. K. Malaiya, "Antirandom Testing: Getting the most out of black-box testing," Proc. International Symposium On Software Reliability Engineering, Oct. 1995, pp. 86-95.  Home/Search   Document Details and Download   Summary   Related Articles   Check

....(statements, branches, defuse pairs, and so on) with different criterion varying in effectiveness to uncover bugs but also in difficulty to achieve coverage. When branch coverage is sought, coverage figures ranging in the 70 85 are often considered acceptable because of infeasible paths [18, 25]. Our research concerns the automation of test data generation based on the white box approach and symbolic execution [14, 4, 5] The presented approach could be used to generate regression test data which is an expensive maintenance process directed at validating modified software [22] 1 ....

Y. K. Malaiya. "Antirandom testing : getting the most out of black-box testing", ISSRE'95 (Sixth int. symp. on soft. reliability engineering), 1995, pp.86-- 95.

....using branch coverage as the testing criterion. 1. Introduction Testing techniques employ a variety of mechanisms, automated, tool assisted, and manual, for test generation. One of the techniques that has gained support and has shown to be useful in a series of empirical evaluations [6, 7] is antirandom testing. The basic premise of anti random testing is that in order to achieve higher coverage (of whatever type) one should, after having exercised a set of tests, now choose tests that are as different as possible from the tests previously used. The distance measure is Hamming and ....

....as possible from the tests previously used. The distance measure is Hamming and Cartesian distance. New test patterns are chosen that maximize this distance. In previous analyses, this approach has improved code coverage for boundary conditions, and has proved more efficient than random testing [6, 5]. The basic method has the following two disadvantages, when used on an arbitrary set of given test vectors: 1. The method essentially requires enumeration of the input space and computation of distance for each potential input vector. This prevents scale up to large test sets and or long input ....

[Article contains additional citation context not shown here]

Y. K. Malaiya, "Antirandom Testing: Getting the Most out of Black-Box Testing", Procs. ISSRE `95, Toulouse, Oct. 1995, p. 86-95.

....6, The analysis for the fault coverage diagrams. Section 7, Conclusion. 2 Some definitions in Antirandom Test patterns Generation Tool Dr. Malaiya formally define the antirandom testing algorithm using two kinds of distances Hamming distance and Cartesian distance as the measures of difference [1]. Then he proposed the antirandom algorithm to construct the test sequences. 2.1 Some terminology in Antirandom Tool Antirandom test sequence (ATS) A test sequence such that a test t i is chosen such that it satisfies some criterion with respect to all tests t 0 ; t 1 ; t i Gamma1 applied ....

Y. K. Malaiya, "Antirandom Testing: Getting the most out of black-box testing," Proc. International Symposium On Software Reliability Engineering, Oct. 1995, pp. 86-95.

No context found.

Y. K. Malaiya, "Antirandom Testing: Getting the most out of black-box testing," Proc. International Symposium On Software Reliability Engineering, Oct. 1995, pp. 86-95.

....Guided Black Box Testing Harish V. Kantamneni Sanjay R. Pillai Yashwant K. Malaiya Department of Computer Science Colorado State University Ft. Collins, Colorado 80523 Tel. 970) 491 7031 Email : fkantamne, pillai, malaiyag cs.colostate.edu Abstract Black box testing [1, 13, 11] can be easily automated and involves less processing than white box testing because it does not use information about the program structure. However it is very hard to achieve high coverage with black box testing. Some branches can be very hard to reach. These branches influence the ....

....any realistic software system. By automating the test generation process, the overall cost can be significantly reduced. There are several ways of classifying software testing techniques. One way is to classify them by the the amount of program information they use. Black box or functional testing [1, 13, 11] strategy uses the specifications or the required behaviour of the software as a starting point to design test cases. White box testing[1, 13] on the other hand, uses internal structure of the program to derive test cases. Black box testing is conceptually simpler and can be easily automated. It ....

[Article contains additional citation context not shown here]

Y. K. Malaiya. Antirandom testing: Getting the most out of black-box testing. Technical Report 96-129, Computer Science Department, Colorado State University, Fort Collins, CO, 1996.

....circuit. We extend the antirandom concept further by proposing a functional test generation scheme in which we find input vectors that would cause antirandom patterns at the output of a circuit. This scheme is evaluated on a popular ALU circuit. 2 Binary Antirandom Sequences Antirandom testing [6] is a black box strategy like psuedo random testing, meaning that it assumes no information about the internal implementation of the circuit. Here we start with formal definitions of the terms used and then examine construction of antirandom sequences. We assume that the input variables are all ....

....two choices for t 2 , we could have constructed 16 distinct MHDATSs using all of the later choices available. We can verify that all of these are also MCDATSs. A large number of experiments with construction of MHDATSs and MCDATSs have been done. Based on these, the following results can be stated [6]. Definition: If a sequence B is obtained by reordering the variables of sequence A, then B is a variable order variant (VOV) of A. Theorem 1: If a sequence B is variable order variant of a MHDATS (MCDATS) A, then B is also a MHDATS (MCDATS) The theorem follows from the fact that Hamming or ....

Y. K. Malaiya, "Antirandom Testing: Getting the most out of black-box testing," Proc. International Symposium On Software Reliability Engineering, Oct. 1995, pp. 86-95.

....testing, checkpoint encoding, test coverage, software testing. 1 Introduction Testing of software requires a significant commitment of resources [12, 17] It is of considerable practical and theoretical importance to explore ways to reduce the testing effort while maximizing test effectiveness [3, 6, 13, 15]. There are many testing techniques discussed in the literature that can be termed black box testing [6, 8, 9, 13, 20] Random testing [8] chooses tests randomly based on some input distribution, without attempting to exploit information gained by tests applied earlier. It considers the program s ....

.... commitment of resources [12, 17] It is of considerable practical and theoretical importance to explore ways to reduce the testing effort while maximizing test effectiveness [3, 6, 13, 15] There are many testing techniques discussed in the literature that can be termed black box testing [6, 8, 9, 13, 20]. Random testing [8] chooses tests randomly based on some input distribution, without attempting to exploit information gained by tests applied earlier. It considers the program s input domain as a single whole and randomly selects test inputs from this domain. There are different opinions ....

[Article contains additional citation context not shown here]

Y. K. Malaiya, "Antirandom Testing: Getting the most out of black-box testing," Proc. International Symposium On Software Reliability Engineering, Oct. 1995, pp. 86-95.

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC