DYNAMIC PROGRAMMING APPROACH TO TESTING RESOURCE ALLOCATION PROBLEM FOR MODULAR SOFTWARE

Testing phase of a software begins with module testing. During this period modules are tested independently to remove maximum possible number of faults within a specified time limit or testing resource budget. This gives rise to some interesting optimization problems, which are discussed in this paper. Two Optimization models are proposed for optimal allocation of testing resources among the modules of a Software. In the first model, we maximize the total fault removal, subject to budgetary Constraint. In the second model, additional constraint representing aspiration level for fault removals for each module of the software is added. These models are solved using dynamic programming technique. The methods have been illustrated through numerical examples

Effect of Introduction of Fault and Imperfect Debugging on Release Time

One of the most important decisions related to the efficient management of testing phase of software development life cycle is to determine when to stop testing and release the software in the market. Most of the testing processes are imperfect once. In this paper first we have discussed an optimal release time problem for an imperfect faultdebugging model due to Kapur et al considering effect of perfect and imperfect debugging separately on the total expected software cost. Next, we proposed a SRGM incorporating the effect of imperfect fault debugging and error generation. The proposed model is validated on a data set cited in literature and a release time problem is formulated minimizing the expected cost subject to a minimum reliability level to be achieved by the release time using the proposed model. Solution method is discussed to solve such class of problem. A numerical illustration is given for both type of release problem and finally a sensitivity analysis is performed

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

FLEXIBLE SOFTWARE RELIABILITY GROWTH MODELS

<p>ENGLISH ABSTRACT: Numerous Software Reliability Growth Models (SRGMs) have been discussed in the literature. These models are used to predict fault content and reliability of software. It has been observed that the relationship between testing time and the corresponding number of faults removed is either exponential or S-shaped, or a mix of the two. Another important class of SRGMs, known as flexible SRGMs, can depict both exponential and S-shaped growth curves. The paper introduces a new concept of power logistic learning function that proves to be very flexible, in the sense that it represents various curve types – exponential, Rayleigh, Weibull or simple logistic. The flexible nature of the power logistic function gives the flexible SRGM a higher degree of accuracy and wider applicability.</p><p>AFRIKAANSE OPSOMMING: Verskeie voorbeelde van Betroubaarheidsgroeimodelle vir programmatuur word in die literatuur beskryf. Die modelle word gebruik vir die voorspelling van foutinhoud en programmatuurbetroubaarheid. Daar word waargeneem dat die verband tussen toetstyd en die resulterende foutverwydering eksponensiaal of S-vormig of ‘n kombinasie daarvan is. Aanpasbare modelle insluitende diskrete ekwivalente word ook behandel. Die publikasie ontleed vervolgens algemene plooibare maglogistieke leerkromme met wye toepasbaarheid wat slaan op eksponensiële, Rayleigh-, Weilbull- en logistieke funksies. Die plooibaarheid van die model waarborg akkuraatheid en wye toepasbaarheid met die verlangde gehalte van voorspelbaarheid.</p&gt

Panel discussion on cost reduction

This item was scanned with a HP 4850 Scanjet at 300 dpi and consists of 35 pages