Software Reliability Growth Models from the Perspective of Learning Effects and Change-Point.

Increased attention towards reliability of software systems has led to the thorough analysis of the process of reliability growth for prediction and assessment of software reliability in the testing or debugging phase. With many frameworks available in terms of the underlying probability distributions like Poisson process, Non-Homogeneous Poisson Process (NHPP), Weibull, etc, many researchers have developed models using the Non-Homogeneous Poisson Process (NHPP) analytical framework. The behavior of interest, usually, is S-shaped or exponential shaped. S-shaped behavior could relate more closely to the human learning. The need to develop different models stems from the fact that nature of the underlying environment, learning effect acquisition during testing, resource allocations, application and the failure data itself vary. There is no universal model that fits everywhere to be called an Oracle. Learning effects that stem from the experiences of the testing or debugging staff have been considered for the growth of reliability. Learning varies over time and this asserts need for conduct of more research for study of learning effects.Digital copy of ThesisUniversity of Kashmi

SOFTWARE RELIABILITY SIMULATION: PROCESS, APPROACHES AND METHODOLOGY

Reliability is probably the most crucial factor to put ones hand up for in any engineering process. Quantitatively, reliability gives a measure (quantity) of quality, and the quantity can be properly engineered using appropriate reliability engineering process. Software Reliability Modeling has been one of the much-attracted research domains in Software Reliability Engineering, to estimate the current state as well as predict the future state of the software system reliability. This paper aims to raise awareness about the usefulness and importance of simulation in support of software reliability modeling and engineering. Simulation can be applied in many critical and touchy areas and enables one to address issues before they these issues become problems. This paper brings to fore some key concepts in simulation-based software reliability modeling. This paper suggests that the software engineering community could exploit simulation to much greater advantage which include cutting down on software development costs, improving reliability, narrowing down the gestation period of software development, fore-seeing the software development process and the software product itself and so on

Reflecting on the Design and Implementation Issues of Virtual Environments

We present a candid reflection on the issues surrounding virtual environment design and implementation (VEDI) in order to: (1) motivate the topic as a research-worthy undertaking, and (2) attempt a comprehensive listing of impeding VEDI issues so they can be addressed. In order to structure this reflection, an idealized model of VEDI is presented. This model, investigated using mixed methods, resulted in 67 distinct issues along the model\u27s transitions and pathways. These were clustered into 11 themes and used to support five VEDI research challenges

Fault detection and correction modeling of software systems

Ph.DDOCTOR OF PHILOSOPH

Towards Accurate Estimation of Error Sensitivity in Computer Systems

Fault injection is an increasingly important method for assessing, measuringand observing the system-level impact of hardware and software faults in computer systems. This thesis presents the results of a series of experimental studies in which fault injection was used to investigate the impact of bit-flip errors on program execution. The studies were motivated by the fact that transient hardware faults in microprocessors can cause bit-flip errors that can propagate to the microprocessors instruction set architecture registers and main memory. As the rate of such hardware faults is expected to increase with technology scaling, there is a need to better understand how these errors (known as ‘soft errors’) influence program execution, especially in safety-critical systems.Using ISA-level fault injection, we investigate how five aspects, or factors, influence the error sensitivity of a program. We define error sensitivity as the conditional probability that a bit-flip error in live data in an ISA-register or main-memory word will cause a program to produce silent data corruption (SDC; i.e., an erroneous result). We also consider the estimation of a measure called SDC count, which represents the number of ISA-level bit flips that cause an SDC.The five factors addressed are (a) the inputs processed by a program, (b) the level of compiler optimization, (c) the implementation of the program in the source code, (d) the fault model (single bit flips vs double bit flips) and (e)the fault-injection technique (inject-on-write vs inject-on-read). Our results show that these factors affect the error sensitivity in many ways; some factors strongly impact the error sensitivity or SDC count whereas others show a weaker impact. For example, our experiments show that single bit flips tend to cause SDCs more than double bit flips; compiler optimization positively impacts the SDC count but not necessarily the error sensitivity; the error sensitivity varies between 20% and 50% among the programs we tested; and variations in input affect the error sensitivity significantly for most of the tested programs

Availability and Reliability Analysis of Computer Software Systems Considering Maintenance and Security Issues

Ph.DDOCTOR OF PHILOSOPH

The global vulnerability discovery and disclosure system: a thematic system dynamics approach

Vulnerabilities within software are the fundamental issue that provide both the means, and opportunity for malicious threat actors to compromise critical IT systems (Younis et al., 2016). Consequentially, the reduction of vulnerabilities within software should be of paramount importance, however, it is argued that software development practitioners have historically failed in reducing the risks associated with software vulnerabilities. This failure is illustrated in, and by the growth of software vulnerabilities over the past 20 years. This increase which is both unprecedented and unwelcome has led to an acknowledgement that novel and radical approaches to both understand the vulnerability discovery and disclosure system (VDDS) and to mitigate the risks associate with software vulnerability centred risk is needed (Bradbury, 2015; Marconato et al., 2012). The findings from this research show that whilst technological mitigations are vital, the social and economic features of the VDDS are of critical importance. For example, hitherto unknown systemic themes identified by this research are of key and include; Perception of Punishment; Vendor Interactions; Disclosure Stance; Ethical Considerations; Economic factors for Discovery and Disclosure and Emergence of New Vulnerability Markets. Each theme uniquely impacts the system, and ultimately the scale of vulnerability based risks. Within the research each theme within the VDDS is represented by several key variables which interact and shape the system. Specifically: Vender Sentiment; Vulnerability Removal Rate; Time to fix; Market Share; Participants within VDDS, Full and Coordinated Disclosure Ratio and Participant Activity. Each variable is quantified and explored, defining both the parameter space and progression over time. These variables are utilised within a system dynamic model to simulate differing policy strategies and assess the impact of these policies upon the VDDS. Three simulated vulnerability disclosure futures are hypothesised and are presented, characterised as depletion, steady and exponential with each scenario dependent upon the parameter space within the key variables