Computer based systems have increased dramatically in scope, complexity, pervasiveness. Most industries are highly dependent on computers for their basic day to day functioning. Safe & reliable software operations are an essential requirement for many systems across different industries. The number of functions to be included in a software system is decided during the software development. Any software system must be constructed in such a way that execution can resume even after the occurrence of failure with minimal loss of data and time. Such software systems which can continue execution even in presence of faults are called fault tolerant software. When failure occurs one of the redundant software modules get executed and prevent system failure. The fault tolerant software systems are usually developed by integrating COTS (commercial off-the-shelf) software components. The motivation for using COTS components is that they will reduce overall system development costs and reduce development time. In this paper, reliability models for fault tolerant consensus recovery blocks are analyzed. In first optimization model, we formulate joint optimization problem in which reliability maximization of software system and execution time minimization for each function of software system are considered under budgetary constraint. In the second model the issue of compatibility among alternatives available for different modules, is discussed. Numerical illustrations are provided to demonstrate the developed models.

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Application Package Software (APS) has emerged as a ready-to-use solution for the software industry. The software system comprises of a number of components which can be either purchased from the vendor in the form of COTS (Commercial Off-the-Shelf) or can be built in-house. Such a decision is known as Build-or-Buy decision. Under the situations wherein the software has the responsibility of supervising life-critical systems, the inception of errors in software due to inadequate or incomplete testing, is not acceptable. Such life-critical systems enforces upon meeting the quality standards of the software as unforbiddenable. This can be achieved by incorporating a fault-tolerant design that enables a system to continue its intended operation rather than failing completely when some part of the system fails. Moreover, while designing a fault-tolerant system, it must be apprehended that 100% fault tolerance can never be achieved and the closer we try to get to 100%, the more costly the system will be. The proposed model shall incorporate consensus recovery block scheme of fault tolerant techniques. Through this paper, we shall focus on build-or-buy decision for an APS in order to facilitate optimal component selection thereby, maximizing the reliability and minimizing the overall cost and source lines of code of the entire system. Further, since the proposed problem has incompleteness and unreliability of input information such as execution time and cost, hence, the environment in the proposed model is taken as fuzzy.

PurposeRecently, blockchain technology (BT) has resolved healthcare data management challenges. It helps healthcare providers automate medical records and mining to aid in data sharing and making more accurate diagnoses. This paper attempts to identify the critical success factors (CSFs) for successfully implementing BT in healthcare.Design/methodology/approachThe paper is methodologically structured in four phases. The first phase leads to identifying success factors by reviewing the extant literature. In the second phase, expert opinions were solicited to authenticate the critical success factors required to implement BT in the healthcare sector. Decision Making Trial and Evaluation Laboratory (DEMATEL) method was employed to find the cause-and-effect relationship among the third phase’s critical success factors. In phase 4, the authors resort to validating the final results and findings.FindingsBased on the analysis, 21 CSFs were identified and grouped under six dimensions. After applying the DEMATEL technique, nine factors belong to the causal group, and the remaining 12 factors fall under the effect group. The top three influencing factors of blockchain technology implementation in the healthcare ecosystem are data transparency, track and traceability and government support, whereas; implementation cost was the least influential.Originality/valueThis study provides a roadmap and may facilitate healthcare professionals to overcome contemporary challenges with the help of BT.