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Q. Explain Predictive validity?
Predictive validity: It is the potential of the model to predict future failure behaviour from present and past failure behaviour. This capability is important only when failure behaviour is changing. There are two universal ways of viewing predictive validity based on the two equivalent approaches to characterizing failure random process namely
1. The number of failure approach as well as
2. The failure time approach.
We can visually ensure the predictive validity by plotting the relative error against the normalised test time.
what are draw backs or disadvantages of waterfall model
What is data dictionary entry explain
Determine statement coverage and path coverage
Problem 1. Explain why the use of a standard high-level language does not guarantee that software will be portable across a range of machines 2. Draw possible data flow diag
TECHLIB Plus microcomputer based software package: This is yet another comprehensive package based on BASIS plus, one of the world's leading Document DBMS and Text Retrieval S
Define Data Dictionary The data dictionary can be explained as an organized collection of all the data elements of the system with precise and rigorous definitions so that user
System software
Go to Blackboard, and print the project scenariolocated under the Project folder. Using Visio, draw a Physical DFD ofall three business processes described in theproject scenario.
Question: (a) Consider that every software failure can be classified as either • Syntactic, • Semantic, • System crash. Suppose additionally that every system crash fa
Recovery/error testing is testing how well a system recovers from crashes, hardware failures, or other catastrophic problems.
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