Abstract—This paper gives the main definitions relating to dependability, a generic concept including as special case such attributes as reliability, availability, safety, integrity, maintainability, etc. Security brings in concerns for confidentiality, in addition to availability and integrity. Basic definitions are given first. They are then commented upon, and supplemented by additional definitions, which address the threats to dependability and security (faults, errors, failures), their attributes, and the means for their achievement (fault prevention, fault tolerance, fault removal, fault forecasting). The aim is to explicate a set of general concepts, of relevance across a wide range of situations and, therefore, helping communication and cooperation among a number of scientific and technical communities, including ones that are concentrating on particular types of system, of system failures, or of causes of system failures.

This paper analyzes the effect of input profile selection on software testing using the concept of fault detectability profile. It shows that optimality of the input profile during testing depends on factors such as the planned testing effort and the error detectability profile. To achieve ultra-reliable software, selecting test input uniformly among different input domains is preferred. On the other hand, if testing effort is limited due to cost or schedule constraints, one should test only the highly used input domains. Use of operational profile is also needed for accurate determination of operational reliability.

Assessing the reliability of a software system has always been an elusive target. A program may work very well for a number of years and this same program may suddenly become quite unreliable if its mission is changed by the user. This has led to the conclusion that the failure of a software system is dependent only on what the software is currently doing. If a program is always executing a set of fault free modules, it will certainly execute indefinitely without any likelihood of failure. A program may execute a sequence of fault prone modules and still not fail. In this particular case, the faults may lie in a region of the code that is not likely to be expressed during the execution of that module. A failure event can only occur when the software system executes a module that contains faults. If an execution pattern that drives the program into a module that contains faults is never selected, then the program will never fail. Alternatively, a program may execute successfully a module that contains faults just as long as the faults are in code subsets that are not executed.

In the statistical sampling method, as in any other statistical approaches for measuring software reliability, the inputs to the program are chosen according to the estimated probability with which they occur in field use, forming the operational profile. However, in practice it is very difficult to accurately assess the operational distribution of input points. Furthermore, a variety of factors can cause the operational distribution to change during field use making the estimation even more difficult. Musa has suggested that reducing the size of the input domain simplifies the task of determining operational profiles. In this paper, we present a class of techniques that reduce the dimensionality of input domains and describe their application. These techniques do not limit the functionality or change the input-output behavior of the program. An additional benefit of these techniques is the insensitivity of the reliability estimate to variations in the operational profile of variables ...

This paper presents an approach for generating test data for unit-level, and possibly integration-level, testing based on sampling over intervals of the input probability distribution, i.e., one that has been divided or layered according to criteria. Our approach is termed "spathic" as it selects random values felt to be most likely or least likely to occur from a segmented input probability distribution. Also, it allows the layers to be further segmented if additional test data is required later in the test cycle.

It is a cruel reality that the goal of producing "perfect software " remains elusive. When software is part of a critical system, it is necessary to estimate the risk associated with its use. Software reliability is defined as the probability of failure free execution given a specific environment and a fixed time interval. The goal of reliability assessment is not just to estimate the failure probability of the program, `, but to gain the statistical confidence that ` is realistic. The transformational approach to software reliability assessment is a novel methodology which combines the strengths of formal verification and statistical testing in a unified and original reliability assessment framework. Program transformations and partial program proofs are used to amplify the effect of test cases; that is, they allow us to infer the behavior of the program on many inputs based on its behavior on one input. The main effect of the application of these transformations is the reduction in t...

Abstract. This paper proposes a conceptual framework for the reliability assessment of software components that incorporates test case execution and output evaluation. Determining an operational profile and test output evaluation are two difficult and important problems that must be addressed in such a framework. Determining an operational profile is difficult, because it requires anticipating the future use of the component. An expected result is needed for each test case to evaluate the test result and a test oracle is used to generate these expected results. The framework combines statistical testing and test oracles implemented as self-checking versions of the implementations. The framework is illustrated using two examples that were chosen to identify the issues that must be addressed to provide tool support for the framework. 1

This paper will describe our experience with collecting and analyzing data for the reliability prediction and estimation of a safety critical system and will discuss the issues encountered. Possible solutions will be briefly addressed. The reliability prediction is based on a set of indirect indicators of reliability such as defects, complexity measures, process measures, etc. These indicators are then linked to reliability through predictive models. Estimation is based on collection and analysis of 10 years of operational data of the system. 1 1.