As many models as there are and many more emerging, none of the models can capture a satisfying amount of the complexity of software; constraints and assumptions have to be made for the quantifying process. Therefore, there is no single model that can be used in all situations.
No model is complete or even representative. One model may work well for a set of certain software, but may be completely off track for other kinds of problems. Most software models contain the following parts: assumptions, factors, and a mathematical function that relates the reliability with the factors. The mathematical function is usually higher order exponential or logarithmic. Software modeling techniques can be divided into two subcategories: prediction modeling and estimation modeling.
The major difference of the two models are shown in Table 1. Table 1. Difference between software reliability prediction models and software reliability estimation models. Using prediction models, software reliability can be predicted early in the development phase and enhancements can be initiated to improve the reliability.
Representative estimation models include exponential distribution models, Weibull distribution model, Thompson and Chelson's model, etc. The field has matured to the point that software models can be applied in practical situations and give meaningful results and, second, that there is no one model that is best in all situations.
Only limited factors can be put into consideration. By doing so, complexity is reduced and abstraction is achieved, however, the models tend to specialize to be applied to only a portion of the situations and a certain class of the problems.
We have to carefully choose the right model that suits our specific case. Furthermore, the modeling results can not be blindly believed and applied. Measurement is commonplace in other engineering field, but not in software engineering. Though frustrating, the quest of quantifying software reliability has never ceased. Until now, we still have no good way of measuring software reliability.
Measuring software reliability remains a difficult problem because we don't have a good understanding of the nature of software. There is no clear definition to what aspects are related to software reliability. We can not find a suitable way to measure software reliability, and most of the aspects related to software reliability.
Even the most obvious product metrics such as software size have not uniform definition. It is tempting to measure something related to reliability to reflect the characteristics, if we can not measure reliability directly. The current practices of software reliability measurement can be divided into four categories: [RAC96].
Software size is thought to be reflective of complexity, development effort and reliability. But there is not a standard way of counting. This method can not faithfully compare software not written in the same language. The advent of new technologies of code reuse and code generation technique also cast doubt on this simple method. Function point metric is a method of measuring the functionality of a proposed software development based upon a count of inputs, outputs, master files, inquires, and interfaces.
The method can be used to estimate the size of a software system as soon as these functions can be identified. It is a measure of the functional complexity of the program. It measures the functionality delivered to the user and is independent of the programming language.
It is used primarily for business systems; it is not proven in scientific or real-time applications. Complexity is directly related to software reliability, so representing complexity is important. Complexity-oriented metrics is a method of determining the complexity of a program's control structure, by simplify the code into a graphical representation. Representative metric is McCabe's Complexity Metric.
Test coverage metrics are a way of estimating fault and reliability by performing tests on software products, based on the assumption that software reliability is a function of the portion of software that has been successfully verified or tested.
Detailed discussion about various software testing methods can be found in topic Software Testing. Researchers have realized that good management can result in better products. Research has demonstrated that a relationship exists between the development process and the ability to complete projects on time and within the desired quality objectives. Costs increase when developers use inadequate processes. Higher reliability can be achieved by using better development process, risk management process, configuration management process, etc.
Based on the assumption that the quality of the product is a direct function of the process, process metrics can be used to estimate, monitor and improve the reliability and quality of software. ISO certification, or "quality management standards", is the generic reference for a family of standards developed by the International Standards Organization ISO.
The goal of collecting fault and failure metrics is to be able to determine when the software is approaching failure-free execution. Minimally, both the number of faults found during testing i. Test strategy is highly relative to the effectiveness of fault metrics, because if the testing scenario does not cover the full functionality of the software, the software may pass all tests and yet be prone to failure once delivered.
To discover the main cause of failure. To conduct performance testing of various modules of software product after fixing defects. Types of Reliability Testing: There are three types of reliability testing:- Feature Testing: Following three steps are involved in this testing: Each function in the software should be executed at least once. Interaction between two or more functions should be reduced. Each function should be properly executed.
Regression Testing: Regression testing is basically performed whenever any new functionality is added, old functionalities are removed or the bugs are fixed in an application to make sure with introduction of new functionality or with the fixing of previous bugs, no new bugs are introduced in the application.
Skip to content. Reliability Testing Reliability Testing is a software testing process that checks whether the software can perform a failure-free operation for a specified time period in a particular environment. Report a Bug. Previous Prev. Next Continue. Home Testing Expand child menu Expand. SAP Expand child menu Expand. Web Expand child menu Expand.
Must Learn Expand child menu Expand. Big Data Expand child menu Expand. Live Project Expand child menu Expand. AI Expand child menu Expand. Toggle Menu Close. Search for: Search. There is no individual model that can be used in all situations. No model is complete or even representative.
A mathematical function that includes the reliability with the elements. The mathematical function is generally higher-order exponential or logarithmic. Both kinds of modeling methods are based on observing and accumulating failure data and analyzing with statistical inference.
A reliability growth model is a numerical model of software reliability, which predicts how software reliability should improve over time as errors are discovered and repaired. These models help the manager in deciding how much efforts should be devoted to testing. The objective of the project manager is to test and debug the system until the required level of reliability is reached. JavaTpoint offers too many high quality services.
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