Hierarchical Structure Modeling for the Analysis of I&C System Software Reliability

2017 ◽  
Author(s):  
Zou Bo-wen ◽  
Yang Ming ◽  
Yan Zhen-yu ◽  
Dai Xin-yu ◽  
Yoshikawa Hidekazu
Keyword(s):  
Hierarchical Structure ◽  
Software Reliability ◽  
Complexity Analysis ◽  
Development Stage ◽  
System Level ◽  
Structure Modeling ◽  
Software System ◽  
System Software ◽  
Software Analysis ◽  
Four Levels

A Software life cycle (SLC) is used to describe the phases of software cycle and ensure the good quality software is built. A software system can be regard as hierarchical and composed of a set of interacting system elements. The system elements will be implemented to fulfill its respective specified requirements. In this paper, as a complex software system, system element also is an entire system. Software hierarchical model has applied commonly in various software analysis areas like software complexity analysis, software reliability allocation analysis, etc. A software reliability hierarchical structure modeling (SRHSM) is proposed for the analysis of the software stages before it being used, which are concept stage, development stage and production stage. Based on the preliminary work, the concepts of SRSHM method is optimized, and increased some basic elements. RSHSM method comprises two processes in SLC, including Partition and Composition process, and is divided into four levels, System level, Subsystem level, Unit level, Code level. Particularly, under the less information condition, this method can be used in the initial stage of SLC to design and analyze the software.

scholarly journals On Estimation of Number of Detectable Software Faults under Budget Constraint

2017 ◽  
Vol 2 (3) ◽  
pp. 135-139 ◽  
Author(s):  
Shinji Inoue ◽  
Kenta Hotta ◽  
Shigeru Yamada
Keyword(s):  
Software Reliability ◽  
Budget Constraint ◽  
Testing Time ◽  
Software System ◽  
Software Faults ◽  
Testing Phase ◽  
Software Reliability Model ◽  
Software Reliability Growth ◽  
Reliable Software ◽  
Testing Plan

Checking software quality and reliability of developed software system is one of the important activities for developing highly-reliable software system. In software testing phase, which is located in the final stage of software development process, software faults remaining the developed software system must be eliminated as possible as the testing manager could. Further, it is also important to develop testing plan to conduct testing activities efficiently under the certain constraints because there are some constraints, such as cost and delivery, in the actual testing phase. This paper discusses method to estimate the number of detectable faults under constant budget constraint by applying a two-dimensional Weibull type software reliability model, in which the software reliability growth process depends on testing time and testing effort factors. We finally show numerical examples of our method by using actual data.

The Application of Genetic Algorithms to the Evaluation of Software Reliability

2010 ◽  
pp. 29-49
Author(s):  
Angel Fernando Kuri-Morales
Keyword(s):  
Genetic Algorithms ◽  
Software Reliability ◽  
Optimization Techniques ◽  
Software System ◽  
Adequate Measure ◽  
Practical Tool ◽  
Definition Of ◽  
Modern Optimization ◽  
The Way

The evaluation of software reliability depends on a) The definition of an adequate measure of correctness and b) A practical tool that allows such measurement. Once the proper metric has been defined it is needed to estimate whether a given software system reaches its optimum value or how far away this software is from it. Typically, the choice of a given metric is limited by the ability to optimize it: mathematical considerations traditionally curtail such choice. However, modern optimization techniques (such as Genetic Algorithms [GAs]) do not exhibit the limitations of classical methods and, therefore, do not limit such choice. In this work the authors describe GAs, the typical limitations for measurement of software reliability (MSR) and the way GAs may help to overcome them.

Empirical Studies on the Functional Complexity of Software in Large-Scale Software Systems

2011 ◽  
Vol 3 (3) ◽  
pp. 23-42 ◽  
Author(s):  
Yingxu Wang ◽  
Vincent Chiew
Keyword(s):  
Cognitive Complexity ◽  
Large Scale ◽  
Complexity Analysis ◽  
Software Systems ◽  
Development Effort ◽  
Analysis Tool ◽  
Software System ◽  
Time Space ◽  
Functional Complexity ◽  
Scope Problem

Functional complexity is one of the most fundamental properties of software because almost all other software attributes and properties such as functional size, development effort, costs, quality, and project duration are highly dependent on it. The functional complexity of software is a macro-scope problem concerning the semantic properties of software and human cognitive complexity towards a given software system; while the computational complexity is a micro-scope problem concerning algorithmic analyses towards machine throughput and time/space efficiency. This paper presents an empirical study on the functional complexity of software known as cognitive complexity based on large-scale samples using a Software Cognitive Complexity Analysis Tool (SCCAT). Empirical data are obtained with SCCAT on 7,531 programs and five formally specified software systems. The theoretical foundation of software functional complexity is introduced and the metric of software cognitive complexity is formally modeled. The functional complexities of a large-scale software system and the air traffic control systems (ATCS) are rigorously analyzed. A novel approach to represent software functional complexities and their distributions in software systems is developed. The nature of functional complexity of software in software engineering is rigorously explained. The relationship between the symbolic and functional complexities of software is quantitatively analyzed.

scholarly journals Integration and Verification Approach of ISTSat-1 CubeSat

Aerospace ◽  
2019 ◽  
Vol 6 (12) ◽  
pp. 131 ◽  
Author(s):  
João P. Monteiro ◽  
Rui M. Rocha ◽  
Alexandre Silva ◽  
Rúben Afonso ◽  
Nuno Ramos
Keyword(s):  
Ionizing Radiation ◽  
Large Scale ◽  
Scale Space ◽  
Development Stage ◽  
System Level ◽  
Thermal Vacuum ◽  
Battery Model ◽  
Engineering Costs ◽  
Space Projects ◽  
Radiation Testing

Large-scale space projects rely on a thorough Assembly, Integration, and Verification (AIV) process to provide the upmost reliability to spacecraft. While this has not traditionally been the case with CubeSats, their increasing role in space science and technology has led to new verification approaches, including in educational CubeSats. This work describes the integration and verification approach for ISTSat-1, which is an educational CubeSat from the Instituto Superior Técnico in Portugal that partially discards the typical stage-gate approach to spacecraft development in favor of a more iterative approach, allowing for the system-level verification of unfinished prototypes. Early verification included software functional testing on a flatsat model, thermal vacuum and vibration testing on a battery model, ionizing radiation testing on the on-board computer, and non-ionizing radiation (EMC) testing on all subsystems. The testing of functional prototypes at an early development stage led to uncovering system-level errors that would typically require hardware redesign at a later project stage. The team considers the approach to be useful for educational projects that employ a small, co-located team with low non-recurring engineering costs.

A Software Model by UML for Highway Monitoring System

2013 ◽  
Vol 336-338 ◽  
pp. 2147-2151
Author(s):  
Yong Liu ◽  
Li Yan Yuan
Keyword(s):  
Monitoring System ◽  
Global Analysis ◽  
System Modeling ◽  
Theory And Practice ◽  
Local Analysis ◽  
Software System ◽  
Monitor System ◽  
System Software ◽  
Whole Process ◽  
Software Model

In order to improve the efficiency of designing monitor system software and modeling with UML, the UML application of software system modeling was researched in theory and practice. The whole process is divided into four steps, which are the global analysis, the local analysis, the global design, and the local design, and the GUI of the system is described at last. A distributed highway monitoring system is analyzed and designed by UML.

A SOFTWARE RELIABILITY GROWTH MODEL WITH TESTING EFFORT DEPENDENT LEARNING FUNCTION FOR DISTRIBUTED SYSTEMS

2004 ◽  
Vol 11 (04) ◽  
pp. 365-377 ◽  
Author(s):  
P. K. KAPUR ◽  
D. N. GOSWAMI ◽  
AMIT GUPTA
Keyword(s):  
Software Reliability ◽  
Goodness Of Fit ◽  
Software Process Improvement ◽  
Software System ◽  
Reliability Growth ◽  
Development Environment ◽  
Testing Effort ◽  
Growth Phenomenon ◽  
Software Reliability Growth ◽  
Fault Removal

Effective software process improvement will not start until management insists that product development work be planned and properly managed. This becomes even more challenging in an increasing number of major system developments made up from distributed sub-system software projects. These sub-systems are integrated and validated to provide the final system and product release. The need is growing to estimate, risk assess, plan and manage the development of these distributed sub-systems and the final full system release. In this paper, an attempt has been made to model the software reliability growth phenomenon with testing effort in a distributed development environment. Proposed Non Homogeneous Poisson Process (NHPP) based model assumes that the software system consists of a finite number of reused and newly developed sub-systems. The reused sub-systems do not consider the effect of severity of the faults on the software reliability growth phenomenon because they stabilize over a period of time i.e., the growth is uniform whereas, the newly developed sub-system do consider that. Fault removal phenomenon for reused and newly developed sub-systems have been modeled separately and is summed up to get the total fault removal phenomenon of the software system. The applicability of our model is shown by validating it on software failure data sets obtained from different real software development projects. The comparisons with established models in terms of goodness of fit, the Akaike Information Criterion (AIC), Mean of Squared Errors (MSE) have been presented.

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