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From the point of view of computing environments, the paper aims to present a goal‐based contextual problem detection and management (GCPDM) method whose core benefit in its extendability of detection capability to deal with unpredicted problems.

Approaches the subject by designing a goal graph, designing actions, designing achievable relations between actions and goals, defining contextual factors of each action, defining CCGs and implementing the GCPD engine.

That self‐managed, as opposed to traditional, software is designed to avoid runtime failures by adapting to unpredictable situations.

This paper presents a GCPDM method.

As systems get complex, requirements elicitation and analysis are becoming increasingly difficult and important in software development. Even though various analysis methods have been proposed, including scenario‐based analysis, goal‐based analysis, combining goal with scenario and use case‐driven analysis – each method has its own strengths and weaknesses and do not support requirements elicitation and analysis efficiently. This paper proposes a multi‐view approach to analyze the requirements of complex software systems. The multi‐view approach comprises four views, which incorporate many factors that are part of existing methods. This paper discusses the need for these four views, the activities that are part of each view and how they are carried out. As a proof of concept, we apply the multi‐view approach to an automatic teller machine system development.

A software product line (SPL) captures commonalities and variations (C&V) within a family of systems. Although, feature‐oriented approaches have been proposed for building product lines, none of them provide a systematic approach for identifying features. This paper proposes a domain analysis method for creating SPL based on scenarios, goals and features. In particular, the paper presents a domain requirements model (DRM) that integrates features with goals and scenarios, and a domain requirements modeling method that uses the DRM. This approach has been applied to the home integration system (HIS) domain to demonstrate its feasibility. This approach makes it possible to systematically identify features and provide the rationale for both features and C&V.

This study aims to provide a more complete picture of blockchain development by combining numerous methodologies with diverse data sources, such as academic papers and news articles. This study displays the developmental status of each subject based on the interrelationships of each topic cluster by analyzing high-frequency keywords extracted from the collected data. Moreover, applying above methodologies will help understanding top research topics, authors, venues, institutes and countries. The differences of blockchain research and new are identified.

To identify and find blockchain development linkages, researchers have used search terms such as co-occurrence, bibliographic coupling, co-citation and co-authorship to help us understand the top research topics, authors, venues, institutes and countries. This study also used text mining analysis to identify blockchain articles' primary concepts and semantic structures.

The findings show the fundamental topics based on each topic cluster's links. While “technology”, “transaction”, “privacy and security”, “environment” and “consensus” were most strongly associated with blockchain in research, “platform”, “big data and cloud”, “network”, “healthcare and business” and “authentication” were closely tied to blockchain news. This article classifies blockchain principles into five patterns: hardware and infrastructure, data, networking, applications and consensus. These statistics helped the authors comprehend the top research topics, authors, venues, publication institutes and countries.

Since Web of Science (WoS) and LexisNexis Academic data are used, the study has few sources. Others advise merging foreign datasets. WoS is one of the world's largest and most-used databases for assessing scientific papers.

This study has several uses and benefits. First, key concept discoveries can help academics understand blockchain research trends so they can prioritize research initiatives. Second, bibliographic coupling links academic papers on blockchain. It helps information seekers search and classify the material. Co-citation analysis results can help researchers identify potential partners and leaders in their field. The network's key organizations or countries should be proactive in discovering, proposing and creating new relationships with other organizations or countries, especially those from the journal network's border, to make the overall network more integrated and linked. Prominent members help recruit new authors to organizations or countries and link them to the co-authorship network. This study also used concept-linking analysis to identify blockchain articles' primary concepts and semantic structures. This may lead to new authors developing research ideas or subjects in primary disciplines of inquiry.

The purpose of this paper is to make an overview of 474 publications and 512 patents of FTL from 1987 to 2020 in order to provide a conclusive and comprehensive analysis for researchers in this field, as well as a preliminary knowledge of FTL for interested researchers.

Firstly, the FTL algorithms are classified and its functions are introduced in detail. Secondly, the structures of the publications are analyzed in terms of the fundamental information and the publication of the most productive countries/regions, institutions and authors. After that, co-citation networks of institutions, authors and papers illustrated by VOS Viewer are given to show the relationship among those and the most influential of them is further analyzed. Then, the characteristics of the patent are analyzed based on the basic information and classification of the patent and the most productive inventors. In order to obtain research hotspots and trends in this field, the time-line review and citation burst detection of keywords carried out by Cite Space are made to be visual. Finally, based on the above analysis, it draws some other important conclusions and the development trend of this field.

The research on FTL algorithm is still the top priority in the future, and how to improve the performance of SSD in the era of big data is one of the research hotspots.

This paper makes a comprehensive analysis of FTL with the method of bibliometrics, and it is valuable for researchers can quickly grasp the hotspots in this area.

This article draws the structural characteristics of the publications in this field and summarizes the research hotspots and trends in this field in recent years, aiming to inspire new ideas for researchers.