Improving Software Reliability Forecasting

This work investigates some methods for software reliability forecasting. A supermodel is presented as a suited tool for prediction of reliability in software project development. Also, times series forecasting for cumulative interfailure time is proposed and illustrated

Software reliability perspectives

Software which is used in life critical functions must be known to be highly reliable before installation. This requires a strong testing program to estimate the reliability, since neither formal methods, software engineering nor fault tolerant methods can guarantee perfection. Prior to the final testing software goes through a debugging period and many models have been developed to try to estimate reliability from the debugging data. However, the existing models are poorly validated and often give poor performance. This paper emphasizes the fact that part of their failures can be attributed to the random nature of the debugging data given to these models as input, and it poses the problem of correcting this defect as an area of future research

Statistical modelling of software reliability

During the six-month period from 1 April 1991 to 30 September 1991 the following research papers in statistical modeling of software reliability appeared: (1) A Nonparametric Software Reliability Growth Model; (2) On the Use and the Performance of Software Reliability Growth Models; (3) Research and Development Issues in Software Reliability Engineering; (4) Special Issues on Software; and (5) Software Reliability and Safety

Software reliability and dependability: a roadmap

Shifting the focus from software reliability to user-centred measures of dependability in complete software-based systems. Influencing design practice to facilitate dependability assessment. Propagating awareness of dependability issues and the use of existing, useful methods. Injecting some rigour in the use of process-related evidence for dependability assessment. Better understanding issues of diversity and variation as drivers of dependability. Bev Littlewood is founder-Director of the Centre for Software Reliability, and Professor of Software Engineering at City University, London. Prof Littlewood has worked for many years on problems associated with the modelling and evaluation of the dependability of software-based systems; he has published many papers in international journals and conference proceedings and has edited several books. Much of this work has been carried out in collaborative projects, including the successful EC-funded projects SHIP, PDCS, PDCS2, DeVa. He has been employed as a consultant t

Rigorously assessing software reliability and safety

This paper summarises the state of the art in the assessment of software reliability and safety ("dependability"), and describes some promising developments. A sound demonstration of very high dependability is still impossible before operation of the software; but research is finding ways to make rigorous assessment increasingly feasible. While refined mathematical techniques cannot take the place of factual knowledge, they can allow the decision-maker to draw more accurate conclusions from the knowledge that is available

An experiment in software reliability

The results of a software reliability experiment conducted in a controlled laboratory setting are reported. The experiment was undertaken to gather data on software failures and is one in a series of experiments being pursued by the Fault Tolerant Systems Branch of NASA Langley Research Center to find a means of credibly performing reliability evaluations of flight control software. The experiment tests a small sample of implementations of radar tracking software having ultra-reliability requirements and uses n-version programming for error detection, and repetitive run modeling for failure and fault rate estimation. The experiment results agree with those of Nagel and Skrivan in that the program error rates suggest an approximate log-linear pattern and the individual faults occurred with significantly different error rates. Additional analysis of the experimental data raises new questions concerning the phenomenon of interacting faults. This phenomenon may provide one explanation for software reliability decay

Experiments in fault tolerant software reliability

The reliability of voting was evaluated in a fault-tolerant software system for small output spaces. The effectiveness of the back-to-back testing process was investigated. Version 3.0 of the RSDIMU-ATS, a semi-automated test bed for certification testing of RSDIMU software, was prepared and distributed. Software reliability estimation methods based on non-random sampling are being studied. The investigation of existing fault-tolerance models was continued and formulation of new models was initiated