Download Dependable Computing for Critical Applications by Mel Barnes (auth.), Prof. Dr. Algirdas Avižienis, Dr. PDF
By Mel Barnes (auth.), Prof. Dr. Algirdas Avižienis, Dr. Jean-Claude Laprie (eds.)
The overseas operating convention on accountable Computing for serious functions was once the 1st convention equipped via IFIP operating crew 10. four "Dependable Computing and Fault Tolerance", in cooperation with the Technical Committee on Fault-Tolerant Computing of the IEEE machine Society, and the Technical Committee 7 on structures Reliability, security and safety of EWlCS. the explanation for the operating convention is better expressed through the goals of WG 10. four: " more and more, members and corporations are constructing or purchasing refined computing platforms on whose providers they should position nice reliance. In differing situations, the focal point may be on differing houses of such prone - e. g. continuity, functionality, real-time reaction, skill to prevent catastrophic mess ups, prevention of planned privateness intrusions. The inspiration of dependability, outlined as that estate of a computing approach which permits reliance to be justifiably put on the carrier it grants, allows those a number of issues to be subsumed inside of a unmarried conceptual framework. Dependability hence contains as designated situations such attributes as reliability, availability, defense, safety. The operating team is aimed toward selecting and integrating techniques, equipment and methods for specifying, designing, development, assessing, validating, working and preserving computers which may still show a few or all of those attributes. " the idea that of WG 10. four used to be formulated in the course of the IFIP operating convention on trustworthy Computing and Fault Tolerance on September 27-29, 1979 in London, England, held at the side of the Europ-IFIP seventy nine convention. Profs A. Avi~ienis (UCLA, la, united states) and A.
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Additional resources for Dependable Computing for Critical Applications
Example text
The test quality QN is then a measure of the test hardness wrt current software test criteria and p is a function of both the criterion to be covered and the input probability distribution. 2. But the theoretical assessment of p from such criteria requires complex calculations for large programs. Moreover, the acute question must be 40 Thivenod-Fosse raised whether the obtained value is representative of the actual software failure probability per test case. 3, we outline a different approach based on a functional model of the software.
1. Statistical coverage wrt test criteria In order to select deterministic test input sets, several structural orland functional test criteria have been defined and compared [30, 33]. For example, let us take the well known structural criterion of "branch testing", which requires that each program branch is executed. In deterministic testing, the criterion coverage is obtained by creating an input data set that executes each branch at least once. In statistical testing, we will say that the coverage is reached with probability QN if each branch has a probability equal to or greater than QN to be executed at least once during test runs with random inputs.
This leads to the following property which is due to the fact that, whatever be the criterion: 1) the test quality QN is an increasing function of the number of executions with random data, and 2) the choice of test data is not related to the criterion (only the minimum number of data for a target QN depends on the criterion). Property. If a test quality QN is reached for a criterion Ci, then QN is also reached for any other criterion Cj such that PCj ~ PCi. a In practice, to cover a set of criteria C = {Ck}, one has only to cover Ci such that PCi =min {PCk, Ck E C}.