Spreadsheet quality assurance: a literature review

Spreadsheets are very common for information processing to support decision making by both professional developers and non-technical end users. Moreover, business intelligence and artificial intelligence are increasingly popular in the industry nowadays, where spreadsheets have been used as, or integrated into, intelligent or expert systems in various application domains. However, it has been repeatedly reported that faults often exist in operational spreadsheets, which could severely compromise the quality of conclusions and decisions based on the spreadsheets. With a view to systematically examining this problem via survey of existing work, we have conducted a comprehensive literature review on the quality issues and related techniques of spreadsheets over a 35.5-year period (from January 1987 to June 2022) for target journals and a 10.5-year period (from January 2012 to June 2022) for target conferences. Among other findings, two major ones are: (a) Spreadsheet quality is best addressed throughout the whole spreadsheet life cycle, rather than just focusing on a few specific stages of the life cycle. (b) Relatively more studies focus on spreadsheet testing and debugging (related to fault detection and removal) when compared with spreadsheet specification, modeling, and design (related to development). As prevention is better than cure, more research should be performed on the early stages of the spreadsheet life cycle. Enlightened by our comprehensive review, we have identified the major research gaps as well as highlighted key research directions for future work in the area.     

Social media prediction: a literature review

Multimedia Tools and Applications - Social Media Prediction (SMP) is an emerging powerful tool attracting the attention of researchers and practitioners alike. Despite its many merits, SMP has also...     

社会控制论及其进展

本文综述控制论应用于社会系统和社会过程的研究及其取得的成就; 介绍社会控制论的诞生、定义和定位; 叙述社会控制论的发展沿革; 小结了社会系统控制论研究的主要方法; 阐明社会控制论的有关主要理论、原理和技术. 在几个实例中, 介绍了自反控制模型、人类活动理论应用、人类前景的研究、基于人工社会的教室行为动态研究和中美知识产权谈判研究等. 最后本文给出分析和评论.     

Competence-based recommender systems: a systematic literature review

ABSTRACT

Competence-based learning is increasingly widespread in many institutions since it provides flexibility, facilitates the self-learning and brings the academic and professional worlds closer together. Thus, the competence-based recommender systems emerged taking the advantages of competences to offer suggestions (performance of a learning experience, assistance of an expert or recommendation of a learning resource) to the user (learner or instructor). The objective of this work is to conduct a new Systematic Literature Review (SLR) concerning competence-based recommender systems to analyse in relation to their nature and assessment of competences an others key factors that provide more flexible and exhaustive recommendations. To do so, a SLR research methodology was followed in which 25 competence-based recommender systems related to learning or instruction environments were classified according to multiple criteria. We evaluate the role of competences in these proposals and enumerate the emerging challenges. Also a critical analysis of current proposals is carried out to determine their strengths and weakness. Finally, future research paths to be explored are grouped around two main axes closely interlinked; first about the typical challenges related to recommender systems and second, concerning ambitious emerging challenges.     

Automatic software refactoring: a systematic literature review

Refactoring a software artifact is an embedded task in the maintenance phase of the software life cycle. To reduce the time and effort required for this task, researchers proposed methods to automate the software refactoring process at the design and code levels. In this paper, we conducted a systematic literature review of papers that suggest, propose, or implement an automated refactoring process. Using different phases, setting several quality measures, and snowballing, only 41 papers passed to the last stage to be analyzed and reviewed. We observe an increase in the number of papers that propose automatic refactoring. The results show that while most of the papers discuss code refactoring, only a few recent papers are focused on model refactoring. Search-based refactoring is gaining more popularity, and several researchers have used it to perform refactoring in a quick and efficient manner.     

文本情感分析方法研究综述

文本情感是信息挖掘的一个新兴领域,近年受到管理学等相关领域的广泛关注。目前,文本情感分析使用的方法主要有情感词典方法和机器学习方法。由于文本情感分析的结果对优化政府、企业以及消费者决策具有重大意义,以文本情感分析的方法为视角,对情感词典的方法、有监督的机器学习方法和弱监督的深度学习方法以及其他方法的相关文献进行了梳理并做出评述。此外,指出虽然文本情感分析领域的学者基于情感词典和有监督的机器学习方法已提出许多情感分析模型,但准确率和效率普遍不高,进一步的研究重点应在于使用深度学习的方法处理文本情感,并提出未来的研究方向。     

Data management in digital twins: a systematic literature review

Knowledge and Information Systems - The Internet of Things (IoT) and continuous advances in data-gathering devices and techniques have significantly increased the amount of relevant data that can...     

Software requirements testing approaches: a systematic literature review

Requirements Engineering - Testing a software system is an important step approach to ensuring quality, safety, and reliability in safety-critical systems (SCS). Several authors have published new...     

Analysis of variability models: a systematic literature review

Software and Systems Modeling - Dealing with variability, during Software Product Line Engineering (SPLE), means trying to allow software engineers to develop a set of similar applications based on...     

Risk factors in software development projects: a systematic literature review

Software Quality Journal - Risks are an inherent part of any software project. The presence of risks in environments of software development projects requires the perception so that the associated...     

Intervention practices in musculoskeletal disorder prevention: a critical literature review

Musculoskeletal disorders (MSDs) affect much of the workforce and remain a major form of occupational ill health. With a view to improving the efficacy of interventions, this review examined preventative actions relating to these disorders. A detailed analysis grid was used to classify the information contained in the 47 reviewed articles whose common aspect was to report actions carried out in the workplace that led to the implementation of changes to prevent MSDs. The analysis identified and characterized three major categories of intervention processes in MSD prevention: the complete type (n=17), the shortened type (n=16), and the turnkey type (n=14). These three groups of intervention processes were differentiated by their approaches and their contexts of application. The result was important differences in the changes implemented. Because of the variability in intervention processes and possible impacts on MSD prevention, a proposal to "delimit" these processes so as to improve their effectiveness is presented.     

Exploring service-oriented system engineering challenges: a systematic literature review

Service-oriented system engineering (SOSE) has drawn increasing attention since service-oriented computing was introduced in the beginning of this decade. A large number of SOSE challenges that call for special software engineering efforts have been proposed in the research community. Our goal is to gain insight into the current status of SOSE research issues as published to date. To this end, we conducted a systematic literature review exploring SOSE challenges that have been claimed between January 2000 and July 2008. This paper presents the results of the systematic review as well as the empirical research method we followed. In this review, of the 729 publications that have been examined, 51 were selected as primary studies, from which more than 400 SOSE challenges were elicited. By applying qualitative data analysis methods to the extracted data from the review, we proved our hypotheses about the classification scheme. We are able to conclude that the SOSE challenges can be classified along two dimensions: (a) based on themes (or topics) that they cover and (b) based on characteristics (or types) that they reveal. By analyzing the distribution of the SOSE challenges on the topics and types in the years 2000–2008, we are able to point out the trend in SOSE research activities. The findings of this review further provide empirical evidence for establishing future SOSE research agendas.     

Empirical evidence about the UML: a systematic literature review

The Unified Modeling Language (UML) was created on the basis of expert opinion and has now become accepted as the ‘standard’ object‐oriented modelling notation. Our objectives were to determine how widely the notations of the UML, and their usefulness, have been studied empirically, and to identify which aspects of it have been studied in most detail. We undertook a mapping study of the literature to identify relevant empirical studies and to classify them in terms of the aspects of the UML that they studied. We then conducted a systematic literature review, covering empirical studies published up to the end of 2008, based on the main categories identified. We identified 49 relevant publications, and report the aggregated results for those categories for which we had enough papers— metrics, comprehension, model quality, methods and tools and adoption. Despite indications that a number of problems exist with UML models, researchers tend to use the UML as a ‘given’ and seem reluctant to ask questions that might help to make it more effective. Copyright © 2010 John Wiley & Sons, Ltd.     

Quality control expert systems: a review of pertinent literature

Statistical quality control (SQC) is an effective tool that ensures quality products and services by means of control charts, the essence of SQC, and sampling plans. While the computation of sample statistics and the development of control charts are routine exercises, the interpretation of chart patterns, trends and the associated diagnosis of assignable causes requires expert knowledge. The present trend is to develop a quality control system and apply it throughout the company (company-wide quality control CWQC or total quality control - TQC). This frequently means involvement of non-quality personnel in QC teams. Additionally, many companies are faced with a shortage of experienced quality controllers and individuals who can train and educate others on statistical quality control techniques. Quality control expert systems (QCESs) are considered as one way to alleviate these difficulties. In recent years, quality control expert systems have attracted the attention of both quality researchers and practitioners. This paper reviews existing quality control expert systems and recommends a set of quality engineering techniques that should be used to form a knowledge base, the heart of an expert system.     

Hierarchical classification of data streams: a systematic literature review

The classification task usually works with flat and batch learners, assuming problems as stationary and without relations between class labels. Nevertheless, several real-world problems do not assume these premises, i.e., data have labels organized hierarchically and are made available in streaming fashion, meaning that their behavior can drift over time. Existing studies on hierarchical classification do not consider data streams as input of their process, and thus, data is assumed as stationary and handled through batch learners. The same can be said about works on streaming data, as the hierarchical classification is overlooked. Studies concerning each area individually are promising, yet, do not tackle their intersection. This study analyzes the main characteristics of the state-of-the-art works on hierarchical classification for streaming data concerning five aspects: (i) problems tackled, (ii) datasets, (iii) algorithms, (iv) evaluation metrics, and (v) research gaps in the area. We performed a systematic literature review of primary studies and retrieved 3,722 papers, of which 42 were identified as relevant and used to answer the aforementioned research questions. We found that the problems handled by hierarchical classification of data streams include mainly classification of images, human activities, texts, and audio; the datasets are mostly created or synthetic data; the algorithms and evaluation metrics are well-known techniques or based on those; and research gaps are related to dynamic context, data complexity, and computational resources constraints. We also provide implications for future research and experiments to consider common characteristics shared amongst hierarchical classification and data stream classification.

     

End-user adaptable technologies for rehabilitation: a systematic literature review

Universal Access in the Information Society - Studies on end-user adaptable applications for rehabilitation aim to offer exercises to patients based on their therapeutic goals and individual...     

Performance prediction of parallel applications: a systematic literature review

The Journal of Supercomputing - Different techniques for estimating the execution time of parallel applications have been studied for the last 25 years. These approaches have proposed different...