Software Reliability Growth Model with Partial Differential Equation for Various Debugging Processes

Most Software Reliability Growth Models (SRGMs) based on the Nonhomogeneous Poisson Process (NHPP) generally assume perfect or imperfect debugging. However, environmental factors introduce great uncertainty for SRGMs in the development and testing phase. We propose a novel NHPP model based on partial differential equation (PDE), to quantify the uncertainties associated with perfect or imperfect debugging process. We represent the environmental uncertainties collectively as a noise of arbitrary correlation. Under the new stochastic framework, one could compute the full statistical information of the debugging process, for example, its probabilistic density function (PDF). Through a number of comparisons with historical data and existing methods, such as the classic NHPP model, the proposed model exhibits a closer fitting to observation. In addition to conventional focus on the mean value of fault detection, the newly derived full statistical information could further help software developers make decisions on system maintenance and risk assessment

Risk-Informed Safety Assurance and Probabilistic Assessment of Mission-Critical Software-Intensive Systems

This report validates and documents the detailed features and practical application of the framework for software intensive digital systems risk assessment and risk-informed safety assurance presented in the NASA PRA Procedures Guide for Managers and Practitioner. This framework, called herein the "Context-based Software Risk Model" (CSRM), enables the assessment of the contribution of software and software-intensive digital systems to overall system risk, in a manner which is entirely compatible and integrated with the format of a "standard" Probabilistic Risk Assessment (PRA), as currently documented and applied for NASA missions and applications. The CSRM also provides a risk-informed path and criteria for conducting organized and systematic digital system and software testing so that, within this risk-informed paradigm, the achievement of a quantitatively defined level of safety and mission success assurance may be targeted and demonstrated. The framework is based on the concept of context-dependent software risk scenarios and on the modeling of such scenarios via the use of traditional PRA techniques - i.e., event trees and fault trees - in combination with more advanced modeling devices such as the Dynamic Flowgraph Methodology (DFM) or other dynamic logic-modeling representations. The scenarios can be synthesized and quantified in a conditional logic and probabilistic formulation. The application of the CSRM method documented in this report refers to the MiniAERCam system designed and developed by the NASA Johnson Space Center

A Review of Software-Induced Failure Experience.

We present a review of software-induced failures in commercial nuclear power plants (NPPs) and in several non-nuclear industries. We discuss the approach used for connecting operational events related to these failures and the insights gained from this review. In particular, we elaborate on insights that can be used to model this kind of failure in a probabilistic risk assessment (PRA) model. We present the conclusions reached in these areas

Reliability improvement and assessment of safety critical software

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Nuclear Engineering; and, (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1998.Includes bibliographical references (leaves 95-101).In order to allow the introduction of safety-related Digital Instrumentation and Control (DI&C) systems in nuclear power plants, the software used by the systems must be demonstrated to be highly reliable. The most widely used and most powerful method for ensuring high software quality and reliability is testing. An integrated methodology is developed in this thesis for reliability assessment and improvement of safety critical software through testing. The methodology is based upon input domain-based reliability modeling and structural testing method. The purpose of the methodology is twofold: Firstly it can be used to control the testing process. The methodology provides path selection criteria and stopping criteria for the testing process with the aim to achieve maximum reliability improvement using available testing resources. Secondly, it can be used to assess and quantify the reliability of the software after the testing process. The methodology provides a systematic mechanism to quantify the reliability and estimate uncertainty of the software after testing.by Yu Sui.S.M

INTEGRATING SOFTWARE BEHAVIOR INTO DYNAMIC PROBABILISTIC RISK ASSESSMENT

Software plays an increasingly important role in modern safety-critical systems. Although research has been done to integrate software into the classical Probability Risk Assessment (PRA) framework, current PRA practice overwhelmingly neglects the contribution of software to system risk. The objective of this research is to develop a methodology to integrate software contributions in the Dynamic Probabilistic Risk Assessment (DPRA) environment. DPRA is considered to be the next generation of PRA techniques. It is a set of methods and techniques in which simulation models that represent the behavior of the elements of a system are exercised in order to identify risks and vulnerabilities of the system. DPRA allows consideration of dynamic interactions of system elements and physical variables. The fact remains, however, that modeling software for use in the DPRA framework is also quite complex and very little has been done to address the question directly and comprehensively. This dissertation describes a framework and a set of techniques to extend the DPRA approach to allow consideration of the software contributions on system risk. The framework includes a software representation, an approach to incorporate the software representation into the DPRA environment SimPRA, and an experimental demonstration of the methodology. This dissertation also proposes a framework to simulate the multi-level objects in the simulation based DPRA environment. This is a new methodology to address the state explosion problem. The results indicate that the DPRA simulation performance is improved using the new approach. The entire methodology is implemented in the SimPRA software. An easy to use tool is developed to help the analyst to develop the software model. This study is the first systematic effort to integrate software risk contributions into the dynamic PRA environment

Applying Reliability Models to the Space Shuttle

Real project experience shows that reliability models can predict reliability and help develop test strategies. This case study reports on IBM's approach to the space shuttle's on-board software.This research was supported by Wliliam Farr of the Naval Surface Warfare Center and Raymond Paul of the Army Operational Test and Evaluation Command