H. Yin, Z. Lebne-Denge and Y. K. Malaiya, "Automatic Test Generation using Checkpoint Encoding and AntirandomTesting" Int. Symp. on Software Reliability Engineering, 1997, pp. 84-95. 3  Home/Search Document Details and Download
Summary Related Articles Check |
This paper is cited in the following contexts:
Fast Antirandom (FAR) Test Generation - von Mayrhauser, Chen, Hajjar.. (1998) (Correct)
....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 ....
....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 vectors. Computations become too expensive. Enumeration is not required when starting from a single seed vector [6, 7], but this limits the applicability of the technique. 2. The input vectors on which the anti random vectors are computed have to be binary. The current way around this problem is to use checkpoint encoding [7] Nonbinary inputs are grouped into partitions which are then given a binary encoding. ....
[Article contains additional citation context not shown here]
H. Yin, Z. Lebnedengel, Y. K. Malaiya, "Automatic Test Generation using Checkpoint Encoding and Antirandom Testing", Procs. ISSRE `97, Albuquerque, NM, Oct. 1997, p. 84-95.
Automated Software Test Data Generation for Complex Programs - Michael, McGraw (1998) (1 citation) (Correct)
....containing up to 2000 lines of source code with complex, nested conditionals. To our knowledge, these are the most complex programs for which results have been reported. By contrast standard programs reported in the literature average 30 lines of code and have relatively simple conditionals [Yin et al. 1997,Korel, 1996,Chang et al. 1996] Results of GADGET runs on small programs can be found in [McGraw et al. 1997] We take advantage of GADGET s capability for processing complex programs by examining the impact of program complexity on the problem of dynamic test data generation. Our gradient ....
....with about 2,000 lines of code. B737 includes both complex control structures and deeply nested conditionals. 3. 1 Simple programs, including triangle We begin our GADGET experimentation on a set of simple functions much like those reported in the literature [Chang et al. 1996, Korel, 1990, Yin et al. 1997] These programs are roughly of the same complexity order, averaging 30 lines of code and all having relatively simple decisions. Complete results for: Binary search, Bubble sort, Date range, Euclidean greatest common denominator, Insertion sort, Computing the median, Quadratic formula, and ....
Yin, H., Lebne-Dengel, Z., and Malaiya, Y. (1997). Automatic test generation using checkpoint encoding and antirandom testing. In Proceedings of the 8th International Symposium on Software Reliability Engineering (ISSRE), pages 84--95.
Antirandom vs. Psuedorandom Testing - Shenhui Wu Yashwant Self-citation (Malaiya) (Correct)
No context found.
H. Yin, Z. Lebne-Denge and Y. K. Malaiya, "Automatic Test Generation using Checkpoint Encoding and AntirandomTesting" Int. Symp. on Software Reliability Engineering, 1997, pp. 84-95. 3
Automatic Test Software - Yashwant Malaiya Computer Self-citation (Malaiya) (Correct)
....with the operational profile, so that the tests replicate the normal operation. On the other hand, the strategy, at reach step, may choose to probe the functionality that has been relatively untouched by testing so far. The second approach may be implemented in the form of antirandom testing [yin97]. A combinatorial design based test generation can significantly reduce the number of combinations to be considered. This is the approach used in AETG (Bellcore) coh97] It is also possible to generate tests using the software implementation formation. Some tools can use this approach termed ....
H. Yin, Z. Lebne-Dengal and Y.K. Malaiya, "Automatic Test Generation using Checkpoint encoding and Antirandom Testing", Proc. Int. Symp. Software Reliability Engineering, 1997, pp. 84-95.
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