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Analyzing Test Performance.- Defect Level Motivation.- ATPG Model Development.- Fault Set Selectability.- Probabilistic Non-Target Defect .
Table of contents
- Standardizing on defect/fault definitions
- Fault Identification and Reliability Assessment Tool Based on Deep Learning for Fault Big Data
- Fault injection
- MODELS 12222 Accepted Papers
Classes of Boolean functions which exploit the efficiencies inherent in OBDDs to a very great extent are examined in Chapter 7.
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Standardizing on defect/fault definitions
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Write a product review. Back to top. It is often used with stress testing and is widely considered to be an important part of developing robust software. The propagation of a fault through to an observable failure follows a well defined cycle.
Fault Identification and Reliability Assessment Tool Based on Deep Learning for Fault Big Data
When executed, a fault may cause an error, which is an invalid state within a system boundary. An error may cause further errors within the system boundary, therefore each new error acts as a fault, or it may propagate to the system boundary and be observable. When error states are observed at the system boundary they are termed failures.
This mechanism is termed the fault-error-failure cycle  and is a key mechanism in dependability.
Technique of fault injection dates back to the s  when it was first used to induce faults at a hardware level. The first experiments in hardware fault involved nothing more than shorting connections on circuit boards and observing the effect on the system bridging faults. It was used primarily as a test of the dependability of the hardware system. Later specialised hardware was developed to extend this technique, such as devices to bombard specific areas of a circuit board with heavy radiation. It was soon found that faults could be induced by software techniques and that aspects of this technique could be useful for assessing software systems.
By increasing complexity of Cyber-Physical Systems, applying traditional fault injection's methods are not efficient anymore, so tester trying to use fault injection in the model level. SWIFI techniques for software fault injection can be categorized into two types: compile-time injection and runtime injection.
Compile-time injection is an injection technique where source code is modified to inject simulated faults into a system. One method is called mutation testing which changes existing lines of code so that they contain faults. Code mutation produces faults which are very similar to those unintentionally added by programmers. A refinement of code mutation is Code Insertion Fault Injection which adds code, rather than modifying existing code. This is usually done through the use of perturbation functions which are simple functions which take an existing value and perturb it via some logic into another value, for example.
In this case pFunc is the perturbation function and it is applied to the return value of the function that has been called introducing a fault into the system.
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Runtime Injection techniques use a software trigger to inject a fault into a running software system. Faults can be injected via a number of physical methods and triggers can be implemented in a number of ways, such as: Time Based triggers When the timer reaches a specified time an interrupt is generated and the interrupt handler associated with the timer can inject the fault.
Runtime injection techniques can use a number of different techniques to insert faults into a system via a trigger. These techniques are often based around the debugging facilities provided by computer processor architectures. Fuzzing is an especially useful form of Black-box testing since the various invalid inputs that are submitted to the software system do not depend on, and are not created based on knowledge of, the details of the code running inside the system. This technique was applied on hardware's prototype. Testers inject fault by changing voltage of some parts in circuit, increasing or decreasing temperature, bombard the board by high energy radiation and etc.
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Although these types of faults can be injected by hand the possibility of introducing an unintended fault is high, so tools exist to parse a program automatically and insert faults. In contrast to traditional mutation testing where mutant faults are generated and injected into the code description of the model, application of a series of newly defined mutation operators directly to the model properties rather than to the model code has also been investigated. Therefore, adding these newly identified properties to the existing list of properties improves the coverage metric of the formal verification and consequently lead to a more reliable design.
Fault injection can take many forms. In the testing of operating systems for example, fault injection is often performed by a driver kernel -mode software that intercepts system calls calls into the kernel and randomly returning a failure for some of the calls.
MODELS 12222 Accepted Papers
This type of fault injection is useful for testing low level user mode software. For higher level software, various methods inject faults. In managed code , it is common to use instrumentation. Although fault injection can be undertaken by hand, a number of fault injection tools exist to automate the process of fault injection. Depending on the complexity of the API for the level where faults are injected, fault injection tests often must be carefully designed to minimize the number of false positives.
Even a well designed fault injection test can sometimes produce situations that are impossible in the normal operation of the software.