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The protection of original achievements including patents and copyrights is a significant and critical issue in today's knowledge-driven economy. In this article, we propose and develop a blockchain service architecture to enhance information traceability and protection effectiveness. Our proposed service architecture is enabled by the core functionalities of blockchain technology including distributed data storage, peer-to-peer transmission, consensus mechanisms, and encryption algorithms. Through this blockchain-based traceability system, we can record, secure, validate, and track original achievements’ registrations and other related transactions. The results of our simulation experiments further validate the effectiveness and robustness of the proposed traceability system design. Our experimental analysis shows that the proposed blockchain-based design can effectively enhance original achievements traceability with an embedded automatic incentive rewarding mechanism for both the creation and protection of original achievements. Moreover, our performance analysis and comparative analysis show that the proposed method has more advantages over several other methods. While our study provides an effective solution to address the existing challenges in intellectual property rights and achievements patents protection, the breadth of the blockchain concept and its applications require nuanced investigations in many different contexts. Thus, the proposed blockchain-based traceability system highlights the potential for broader applications of this disruptive technology in many other domains.

Empirical research aims to establish generalizable claims from data. Such claims involve concepts that often must be measured indirectly by using indicators. Construct validity is concerned with whether one can justifiably make claims at the conceptual level that are supported by results at the operational level. We report a quantitative analysis of the awareness of construct validity in the software engineering literature between 2000 and 2019 and a qualitative review of 83 articles about human-centric experiments published in five high-quality journals between 2015 and 2019. Over the two decades, the appearance in the literature of the term construct validity increased sevenfold. Some of the reviewed articles we reviewed employed various ways to ensure that the indicators span the concept in an unbiased manner. We also found articles that reuse formerly validated constructs. However, the articles disagree about how to define construct validity. Several interpret construct validity excessively by including threats to internal, external, or statistical conclusion validity. A few articles also include fundamental challenges of a study, such as cheating and misunderstandings of experiment material. The diversity of topics discussed makes us recommend a minimalist approach to construct validity. We propose seven guidelines to establish a common ground for addressing construct validity in software engineering.

In order to optimise the corporate HR information system, IoT first-off technology is used, together with the system demand phase, with edge control in mind. initially, the hardware and software system are set up, and only then the communication models between the edge layer of the system and other parties are created edge layer, and the business type-driven connection selection method are considered. To ensure communication reliability across various levels of the system, northbound multilink switching algorithms are created and implemented, accordingly. After implementing the functions described above, the edge control system may be implemented. Ensure IoT applications satisfy intelligence, expandability, and security needs. due diligence and due diligence are required The campaign was aimed primarily at the enterprise, with the goal of defining the functional and performance requirements of the product. Ensuring the fundamental logical structure in the system design phase; in the system architecture design phase, the other features of the system architecture Realization of design is accomplished. a set of system module functions exists planned down to the last detail. Pay and benefits management are only two aspects of the whole management function. Employee personnel change is one of the e system's modules. Payroll, benefits, and personnel administration are referred to as department management. Human resource management is a process system modules go through; as far as system implementation is concerned, system coding occurs. In addition, development tool and software development methodology support the creation of pages. The system has finally been realised the system design goals are set up to mimic the business's real needs, which are then put to the test.

UVM is the most important mechanism in the field of SoC Verification. But complex characteristics, implementation difficulties in UVM still persist which leads to at most challenging part for the improvisation. To solve this issue, a new verification methodology called VEDA (Verification Environment for IP Architectures) which integrates python as the verification language is proposed. The powerful features of Python are used to bring the most versatile environment for verification and to make the UVM as the user friendly mechanism. The paper proposes the verification mechanism for the different IP’s which plays asignificant role in all IoT applications. Further the proposed method is being compared to existing UVM and also other existing python HDL tools and proved to be more advantages when compared to the existing methodologies.

An emergency response process outlines the workflow of different activities that need to be performed in response to an emergency. Effective emergency response requires communication and coordination with the operational systems belonging to different collaborating organizations. Therefore, it is necessary to establish information sharing and system-level interoperability among the diverse operational systems. Unlike typical e-government processes that are well structured and have a well-defined outcome, emergency response processes are knowledge-centric and their workflow structure and execution may evolve as the incident unfolds. It is impractical to define static plans and response process workflows for every possible situation. Instead, a dynamic response should be adaptable to the changing situation. We present an integrated approach that facilitates the dynamic composition of an executable response process. The proposed approach employs ontology-based reasoning to determine the default actions and resource requirements for the given incident and to identify relevant response organizations based on their jurisdictional and mutual aid agreement rules. The Web service APIs of the identified response organizations are then used to generate an executable response process that evolves dynamically. The proposed approach is implemented and experimentally validated using an example scenario derived from the FEMA Hazardous Materials Tabletop Exercises Manual.

Software ecosystems are considered the natural evolution of software product lines. A software ecosystem provides a (software) product within a particular business and organizational context that supports the exchange of activities and services within a domain. However, the increasing degree of autonomy demanded by software ecosystems is elevating the system response to end users, while the existing software ecosystem architectures are not well prepared to deal with the dynamicity of context changes and autonomous behavior needs. In order to provide a transition toward an increased level of autonomy, in this article, we introduce the notion of autonomous dynamic ecosystems as representative of those software ecosystems able to support dynamic, smart, and autonomous features demanded by modern software systems. In this work, we further investigate and provide evidence of four industrial examples that have fully embodied the principles of autonomous dynamic ecosystems, and we characterize the main features and technology requirements of this kind of new ecosystems.

Due to their increasing complexity, today's software systems are frequently built by leveraging reusable code in the form of libraries and packages. Software ecosystems (e.g., npm) are the primary enablers of this code reuse, providing developers with a platform to share their own and use others' code. These ecosystems evolve rapidly: developers add new packages every day to solve new problems or provide alternative solutions, causing obsolete packages to decline in their importance to the community. Developers should avoid depending on packages in decline, as these packages are reused less over time and may become less frequently maintained. However, current popularity metrics (e.g., Stars, and Downloads) are not fit to provide this information to developers because their semantics do not aptly capture shifts in the community interest. In this paper, we propose a scalable approach that uses the package's centrality in the ecosystem to identify packages in decline. We evaluate our approach with the npm ecosystem and show that the trends of centrality over time can correctly distinguish packages in decline with an ROC-AUC of 0.9. The approach can capture 87% of the packages in decline, on average 18 months before the trend is shown in currently used package popularity metrics. We implement this approach in a tool that can be used to augment the npms metrics and help developers avoid packages in decline when reusing packages from npm., Accepted in the Special Issue on Collaboration and Innovation Dynamics in Software Ecosystems

Functional and nonfunctional characteristics of software systems are defined by their architecture. Therefore, research streams such as Internet-of-Things (IoT) or component-based software engineering provide researchers and practitioners with construction guidelines for selected architectural characteristics. Current systems can be categorized in delivering services to the user and being engineered in a smart way. For example, services being provided by IoT-Systems must fulfill users’ goals in a highly dynamic and ad-hoc way. Consequently, this survey aims at answering various research questions regarding the methodical composition of system components and services. Furthermore, new research opportunities are sketched that should be tackled to make the scientific progress available to practitioners. Based on a systematic literature review from a software architecture point of view, in this paper we identify 75 primary studies for domain-specific IoT component composition approaches and architectures. Initial results show that current integration approaches mainly focus on performance evaluation of their integration solutions, which may be too narrow for fulfilling user goals by utilizing of IoT architectures.

Security analysts rely on scenarios to assess vulnerabilities, project attacks, and decide on security requirements that mitigate the threat. However, eliciting natural language scenarios from stakeholders can be an ad-hoc process and subject to ambiguity and incompleteness. In this paper, we examine systematic scenario elicitation by introducing a method based on user stories that uses a simplified process model of iterative scenario refinement. The process consists of three steps: 1) eliciting an interaction statement that describes a critical action performed by a user or system process; 2) eliciting one or more descriptive statements about a technology that enables the interaction; and 3) refinement of the technology into technical variants that correspond to design alternatives. We empirically evaluated our method by implementing our prototype in a user study that collects 30 security scenarios from participants. Based on our analysis, our proposed method is shown effective. Participants had a 100% task completion rate with 57% of participants achieving complete task-success, and the remaining 43% of participants achieving partial task-success. We also show the effect of security domain knowledge, and the benefit of using structure when collecting security requirements in natural language text. Finally, we present lessons learned and future research directions.

Existing programming practices for building Android apps mainly follow the one-size-fits-all strategy to include lots of functions and adapt to most types of devices. However, this strategy can result in software bloat and many serious issues, such as slow download speed, and large attack surfaces. Existing solutions cannot effectively debloat an app as they either lack flexibility or require human efforts. This work proposes a novel feature-oriented debloating approach and builds a new tool, named XDebloat, to automate this process in a flexible manner. First, XDebloat supports feature location approaches at a fine granularity. It also makes the feature location results editable and changeable. Second, XDebloat considers several Android-oriented issues (i.e., callback, UI dependencies), which are not covered in the state-of-art approaches. Third, XDebloat support two major debloating strategies: pruning-based and module-based debloating. We evaluate XDebloat with 200 open-source and 1,000 commercial apps. The results show that XDebloat can successfully remove unwanted features from apps or transform them into on-demand modules within 10 minutes. For the pruning-based debloating strategy, on average, XDebloat can remove 32.1% code from an app. For the module-based debloating strategy, XDebloat can help developers build modules automatically.

The Internet of Things (IoT) aids an interconnection between systems, humans, and services to develop computation-intensive autonomous applications. Service-oriented architecture (SOA) concepts have been used as defacto software architecture to develop IoT-based systems. Though SOA facilitates various benefits, several challenges exist for integration with IoT-based systems, including configurability, interoperability, and manageability. The ontology-based approach provides a semantically enriched and rigorous platform for interoperating different heterogeneous IoT-based systems and applications. The semantic modelling research has focused on IoT resource management without concerning the method of accessing and utilizing IoT information. In this context, an IoT-based large-scale SOA (IoT-LSS) ontology is proposed that supports interoperability, heterogeneity, flexibility, manageability, extendibility, scalability. This ontology integrates the concept of large-scale SOA (LSS) with semantic sensor network (SSN) ontology. Clinical decision support system (CDSS) ontology has considered as a case study to illustrate the proposed ontology. A detailed comparative analysis between the proposed system and several existing IoT-based service ontologies has been performed based on different characteristics. This analysis shows that IoT-LSS supports dynamic features and exposes to service with its different mechanisms. This article presents an ontological framework for the IoT service-based environment to efficiently use for service composition mechanisms in the large service domain.

Grounded Theory (GT), a sociological research method designed to study social phenomena, is increasingly being used to investigate the human and social aspects of software engineering (SE). However, being written by and for sociologists, GT is often challenging for a majority of SE researchers to understand and apply. Additionally, SE researchers attempting ad hoc adaptations of traditional GT guidelines for modern socio-technical (ST) contexts often struggle in the absence of clear and relevant guidelines to do so, resulting in poor quality studies. To overcome these research community challenges and leverage modern research opportunities, this paper presents Socio-Technical Grounded Theory (STGT) designed to ease application and achieve quality outcomes. It defines what exactly is meant by an ST research context and presents the STGT guidelines that expand GT's philosophical foundations, provide increased clarity and flexibility in its methodological steps and procedures, define possible scope and contexts of application, encourage frequent reporting of a variety of interim, preliminary, and mature outcomes, and introduce nuanced evaluation guidelines for different outcomes. It is hoped that the SE research community and related ST disciplines such as computer science, data science, artificial intelligence, information systems, human computer/robot/AI interaction, human-centered emerging technologies (and increasingly other disciplines being transformed by rapid digitalisation and AI-based augmentation), will benefit from applying STGT to conduct quality research studies and systematically produce rich findings and mature theories with confidence., Comment: Accepted to IEEE Transactions on Software Engineering (Aug 2021); This author preprint is 26 pages, the final IEEE version is 25 pages due to reformatting, content is same. More details: https://rashina.com/