Robust Dynamic Selection of Tested Modules in Software Testing for Maximizing Delivered Reliability

Software testing is aimed to improve the delivered reliability of the users. Delivered reliability is the reliability of using the software after it is delivered to the users. Usually the software consists of many modules. Thus, the delivered reliability is dependent on the operational profile which specifies how the users will use these modules as well as the defect number remaining in each module. Therefore, a good testing policy should take the operational profile into account and dynamically select tested modules according to the current state of the software during the testing process. This paper discusses how to dynamically select tested modules in order to maximize delivered reliability by formulating the selection problem as a dynamic programming problem. As the testing process is performed only once, risk must be considered during the testing process, which is described by the tester's utility function in this paper. Besides, since usually the tester has no accurate estimate of the operational profile, by employing robust optimization technique, we analysis the selection problem in the worst case, given the uncertainty set of operational profile. By numerical examples, we show the necessity of maximizing delivered reliability directly and using robust optimization technique when the tester has no clear idea of the operational profile. Moreover, it is shown that the risk averse behavior of the tester has a major influence on the delivered reliability.Comment: 19 pages, 4 figure

Structural reliability methods: Code development status

The Probabilistic Structures Analysis Method (PSAM) program integrates state of the art probabilistic algorithms with structural analysis methods in order to quantify the behavior of Space Shuttle Main Engine structures subject to uncertain loadings, boundary conditions, material parameters, and geometric conditions. An advanced, efficient probabilistic structural analysis software program, NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) was developed as a deliverable. NESSUS contains a number of integrated software components to perform probabilistic analysis of complex structures. A nonlinear finite element module NESSUS/FEM is used to model the structure and obtain structural sensitivities. Some of the capabilities of NESSUS/FEM are shown. A Fast Probability Integration module NESSUS/FPI estimates the probability given the structural sensitivities. A driver module, PFEM, couples the FEM and FPI. NESSUS, version 5.0, addresses component reliability, resistance, and risk

A Probabilistic Risk Analysis for Taipei Seismic Hazards: An Application of HAZ-Taiwan with its Pre-processor and Post-processor

This paper employs probabilistic risk analysis to estimate exceedance probability curves, average annual loss (AAL) and probable maximum loss (PML) for seismic hazards. It utilizes and event-driven loss estimation model, HAZ-Taiwan, and develops its pre-processing and post-processing software modules. First, the pre-processingmodule establishes a set of hazard-consistent scenarios. Then, the HAZ-Taiwan modelextimates hazards, vulnerabilities and economic losses for each scenario. Finally, the aggregate and occurrence exceedance probability curves for losses and theirconfidence intervals are simulated using the Monte Carlo simulation in thepost-processing module. The methodology is then applied to analyze seismic risks in Taipei. It is found that the exceedance probability of an aggregate loss of NT$40.398 billion is 0.001. This amount of loss is approximately 2.78$37.41-43.12 billion. The average annual loss of buildings in Taipei is NT$1.06 billion r approximately 0.07% of the total stock.probabilistic risk analysis, Hazard analysis, vulnerability analysis, exceedance probability curve, HAZ-Taiwan

ARIPAR 5.0: Reference Manual: Software Tool for Area Risk Assessment and Management

ARIPAR is a quantitative area risk assessment tool used to evaluate the risk resulting from major accidents in industrial areas where hazardous substances are stored, proc-essed and transported. It is based on a geographical information system platform (GIS). This tool has already been applied to perform a quantitative area risk assess-ment in several industrial areas, and it has been demonstrated to be a very powerful tool also for managing industrial risk. ARIPAR 5.0 is the new release of the software, which embeds several new features and improvements, such as a completely new de-velopment platform based on ArcGIS and a much more powerful module for dealing with consequence assessment data. The present document represents the Reference Manual of ARIPAR 5.0, which describes all commands, dialogs, risk analysis equa-tions, input data format and reporting available in this software package.JRC.G.6-Security technology assessmen

The dChip survival analysis module for microarray data

International audienceBACKGROUND: Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer. Similar predictions have recently been carried out using genome-wide copy number alterations and microRNAs. Existing software packages for microarray data analysis provide functions to define expression-based survival gene signatures. However, there is no software that can perform survival analysis using SNP array data or draw survival curves interactively for expression-based sample clusters. RESULTS: We have developed the survival analysis module in the dChip software that performs survival analysis across the genome for gene expression and copy number microarray data. Built on the current dChip software's microarray analysis functions such as chromosome display and clustering, the new survival functions include interactive exploring of Kaplan-Meier (K-M) plots using expression or copy number data, computing survival p-values from the log-rank test and Cox models, and using permutation to identify significant chromosome regions associated with survival. CONCLUSIONS: The dChip survival module provides user-friendly way to perform survival analysis and visualize the results in the context of genes and cytobands. It requires no coding expertise and only minimal learning curve for thousands of existing dChip users. The implementation in Visual C++ also enables fast computation. The software and demonstration data are freely available at http://dchip-surv.chenglilab.org

Risk determination for the implantation process of software systems

From the analysis of software companies in Argentina, weaknesses in risk management have been observed. This impacts in quality management because risk planning is a requirement specified by all standards. As part of a general study about the implantation of software systems, the aim of this work is to analyze the risks associated to such process. This proposal envisages the activities and tasks of the ISO/IEC 12207 standard transition process. For the assessment of the proposed risks, the ISO/IEC 31010 standard is adopted. Furthermore, associated procedures are suggested to either avoid or mitigate risks. The work was tested in a real environment to determine its viability. The case study consisted of the risk analysis of the implantation of the management system module of a multinational company’s advertising agency. This revealed flaws in the management of the analyzed risks and provided feedback for the study.XVI Workshop Ingeniería de Software.Red de Universidades con Carreras en Informátic

Ризико-операційний підхід до вирішення проблеми оптимального випуску програмних систем

Запропоновано підхід до вирішення задачі оптимального випуску програмних систем, базований на аналізі ризику відмов програмних компонентів і врахуванні операційного профілю функціонування системи при формуванні критерію оптимізації. Розроблено метод оцінки ризику відмов програмних компонентів та модель для визначення оптимального часу тестування програмних модулів, яка враховує ризики відмов модулів під час експлуатації.The approach to the decision of task of optimal software systems release is represented. It is based on the software failure risk analysis and of operational profile of system functioning for building the optimization criteria. The method of modules risks evaluation has been developed. A model for the determination of the optimum time of the system’s modules testing has been developed. It takes into account risks of module failures during the system operation