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  1. Free, publicly-accessible full text available July 1, 2023
  2. Computerized systems and software, which allow optimizing and planning the processes of production, storage, transportation, sale, and distribution of goods, have emerged in the industry. Scheduling systems, in particular, are designed to control and optimize the manufacturing process. This tool can have a significant effect on the productivity of the industry because it reduces the time and cost through well-defined optimization algorithms. Recently, the applicability of blockchain technology has been demonstrated in scheduling systems to add decentralization, traceability, auditability, and verifiability of the immutable information that this technology provides. This is a novel contribution that provides scheduling systems with an additional layer of security. With the latest version of Hyperledger Fabric, the appropriate levels of permission and policies for access to information can be established with significant levels of privacy and security, which prevent malicious actors from trying to cheat or abuse the system. Different alternatives exist to manage all processes associated with the operation of a blockchain network, and among them, providers of blockchain as a service have emerged. Chainstack stands out for its simplicity and scalability features to deploy and operate a blockchain network. Our goal in this work is to create a solution for secure storage ofmore »and access to task-scheduling scheme on the consortium blockchain and inter-planetary file system as a proof of concept to demonstrate its potential and usability.« less
  3. As big data becomes an important part of business analytics for gaining insights about business practices, the quality of big data is an essential factor impacting the outcomes of business analytics. Although this is quite challenging, conceptual modelling has much potential to solve it since the good quality of data comes from good quality of models. However, existing data models at a conceptual level have limitations to incorporate quality aspects into big data models. In this paper, we focus on the challenges cause by Variety of big data propose IRIS, a conceptual modelling framework for big data models which enables us to define three modelling quality notions – relevance, comprehensiveness, and relative priorities and incorporate such qualities into a big data model in a goal-oriented approach. Explored big data models based on the qualities are integrated with existing data grounded on three conventional organizational dimensions creating a virtual big data model. An empirical study has been conducted using the shipping decision process of a worldwide retail chain, to gain an initial understanding of the applicability of this approach.
  4. Studies have shown that combinatorial testing (CT) can be effective for detecting faults in software systems. By focusing on the interactions between different factors of a system, CT shows its potential for detecting faults, especially those that can be revealed only by the specific combinations of values of multiple factors (multi-factor faults). However, is CT practical enough to be applied in the industry? Can it be more effective than other industry-favored techniques? Are there any challenges when applying CT in practice? These research questions remain in the context of industrial settings. In this paper, we present an empirical study of CT on five industrial systems with real faults. The details of the input space model (ISM) construction, such as factor identification and value assignment, are included. We compared the faults detected by CT with those detected by the inhouse testing teams using other methods, and the results suggest that despite some challenges, CT is an effective technique to detect real faults, especially multi-factor faults, of software systems in industrial settings. Observations and lessons learned are provided to further improve the fault detection effectiveness and overcome various challenges.
  5. The potential of blockchain technology is immense and is currently regarded as a new technological trend with a rapid growth rate. Blockchain platforms like Bitcoin are public, open, and permission-less. They are also decentralized, immutable, and append-only ledger; those ledgers can store any type of data and are shared among all the participants of the network. These platforms provide a high degree of anonymity for their users' identity and full transparency of the activities recorded on the ledger while simultaneously ensuring data security and tamper-resistance. All nodes on the network collectively work to validate the same set of data and to achieve group consensus. Blockchain platforms like Ethereum have the ability to develop smart contracts and embed business logic. This allows the use of blockchain beyond cryptocurrency as a business management solution. Besides the issues of scalability and the expensive nature of most blockchain systems, many attributes of traditional public blockchain are not desirable in a business or enterprise context such as anonymity, full transparency, and permissionless. Permissioned blockchain platforms like Hyperledger Fabric are designed and built with enterprise and business in mind, retaining the desirable qualities of blockchain for enterprise while replacing the qualities of blockchain that are undesirablemore »for the enterprise. In this paper, we present a comprehensive review on the Hyperledger enterprise blockchain technologies.« less
  6. After more than 30 years of development, combinatorial testing has become an essential method in the field of software testing, which has always been an active field. Through combined coverage, combinatorial testing can detect faults caused by various parameters and their interactions in a software under test. This paper aims to review the development of combinatorial testing and briefly introduce its basic applications. We classify today's combinatorial testing applications, including those of traditional industry and those of the IT industry. The research-and-application progress of combinatorial testing was investigated with respect to various fields of application, and potential application directions for the future were proposed to provide ideas its the extensive application.
  7. The term crowdsourcing – a compound contraction of crowd and outsourcing – is a new paradigm for utilizing the power of crowds of people to facilitate large-scale tasks that are costly or time consuming with traditional methods. This paradigm offers mobile application companies the possibility to outsource their testing activities to crowdsourced testers (crowdtesters) who have various testing facilities and environments, as well as different levels of skills and expertise. With this so-called Crowdsourced Mobile Application Testing (CMAT), some of the well-recognized issues in testing mobile applications, such as multitude of mobile devices, fragmentation of device models, variety of OS versions, and omnifariousness of testing scenarios, could be mitigated. However, how effective is CMAT in practice? What are the challenges and issues presented by the process of applying CMAT? How can these issues and challenges be overcome and CMAT be improved? Although CMAT has attracted attention from both academia and industry, these questions have not been addressed or researched in depth based on a large-scale and real-life industrial study. Since June 2015, we have worked with Mooctest, Inc., a CMAT intermediary, on testing five real-life Android applications using their CMAT platform – Kikbug. Throughout the process, we have collected 1013more »bug reports from 258 crowdtesters and found 247 bugs in total. This paper will present our industrial study thoroughly and give an insightful analysis to investigate the successes and challenges of applying CMAT.« less