| Autor: |
Roger W. Elliott, Miner P. Marchbanks, Dick B. Simmons, Larry J. Ringer, Michael G. McWilliams |
| Rok vydání: |
1978 |
| Předmět: |
|
| Zdroj: |
Computers & Industrial Engineering. 2:141-151 |
| ISSN: |
0360-8352 |
| DOI: |
10.1016/0360-8352(78)90024-4 |
| Popis: |
Under certain conditions, traditional hypothesis-testing techniques may be used as a management tool by software developers or software purchasers who wish to insure that their packages have some specified reliability level. These conditions are: (1) the existence of independent collections of test data, (2) a way of determining the correctness of processing of these collections, and (3) a way of randomly selecting test data. Two basic approaches have been described. In a fixed sample size test, the user decides on the reliability desired. He can then determine the number of test cases which must be examined and the acceptance/rejection criteria. In a sequential test, the desired reliability level is again pre-determined, but samples are tested one at a time until an accept/reject decision can be made. Experiments with a large amount of error data derived from six separate systems indicate that reliability results derived from these models are consistent with actual reliability figures. Most current acceptance procedures are based on a naive assumption that a large program can be exhaustively tested and delivered in an error-free condition. Because these expectations cannot be fulfilled, the manager of a software development project or the purchaser of a software product is provided with no quantitative information on which to base an acceptance decision and is thus forced to make these decisions based mostly on intuition and his own experience in similar situations. These models allow one to replace these intuition-based decisions with quantitatively-based decisions and thus constitute an important contribution to the science of management of software development efforts. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
|
