scholarly journals Bad Smells of Gang of Four Design Patterns: A Decade Systematic Literature Review

2021 ◽  
Vol 13 (18) ◽  
pp. 10256
Author(s):  
Sara H. S. Almadi ◽  
Danial Hooshyar ◽  
Rodina Binti Ahmad
Keyword(s):  
Software Design ◽  
Design Patterns ◽  
State Of The Art ◽  
Future Research ◽  
Code Smells ◽  
Research Gaps ◽  
Design Problems ◽  
Code Smell ◽  
Analysis Design ◽  
And Behavior

Gang of Four (GoF) design patterns are widely approved solutions for recurring software design problems, and their benefits to software quality are extensively studied. However, the occurrence of bad smells in design patterns increases the crisis of degenerating design patterns’ structure and behavior. Their occurrences are detrimental to the benefits of design patterns and they influence software sustainability by increasing maintenance costs and energy consumption. Despite the destructive roles of bad smells in such designs, there are an absence of studies systematically reviewing bad smells of GoF design patterns. This study systematically reviews a 10-year state of the art sample, identifying 16 studies investigating this phenomenon. Following a thorough evaluation of the full contents, we observed that the occurrence of bad smells have been investigated in proportion to four granularity levels of analysis: Design level, category level, pattern level, and role level. We identified 28 bad smells, categorized under code smells and grime symptoms, and emphasized their relationship with GoF pattern types and categories. The utilization of design pattern bad smell detection approaches and datasets were also discussed. Consequently, we observed that the research phenomenon is growing intensively, with a prominent focus of studies analyzing code smell occurrences rather than grime occurrences, at various granularity levels. Finally, we uncovered research gaps and areas with significant potentials for future research.

scholarly journals INTEREST-FREE FINANCING IN AGRO-INDUSTRY: CONCEPTS, THEORIES, METHODS AND RESEARCH GAPS

2021 ◽  
Vol 9 (03) ◽  
pp. 84-94
Author(s):  
Kiki Yulianto ◽  
◽  
Sukardi a ◽  
Nastiti Siswi Indrasti ◽  
Sapta Raharja ◽  
...  
Keyword(s):  
Literature Review ◽  
Systematic Literature Review ◽  
State Of The Art ◽  
Secondary Data ◽  
Future Research ◽  
Literature Study ◽  
Research Gaps ◽  
The Road ◽  
Road Map ◽  
Conference Papers

Interest-free financing in agro-industry is an exciting topic that has been developed by many researchers, but there is no clarity regarding the road map for future research. Therefore, formulations such as concepts, theories, methods, and research gaps, focusing on interest-free financing in agro-industry, are essential. This literature study was conducted using a systematic literature review method. The data used are secondary data from textbooks, theses/dissertations, conference papers, journals, scientific articles, and working papers. This study resulted in the formulation of the theory, concepts, and methods studied in the form of an explanation of 8 sub-topics of research gaps supported by references and explanations of state of the art. They are making it easier for researchers who have the same interest in developing and looking for novelties with the topic of interest-free financing research in the agro-industry.

Persuasive technology for health and wellness: State-of-the-art and emerging trends

2016 ◽  
Vol 24 (1) ◽  
pp. 66-91 ◽  
Author(s):  
Rita Orji ◽  
Karyn Moffatt
Keyword(s):  
Health Behaviors ◽  
Design Research ◽  
State Of The Art ◽  
Persuasive Technology ◽  
Future Research ◽  
Health And Wellness ◽  
Motivational Strategies ◽  
Emerging Trends ◽  
Technological Interventions ◽  
And Behavior

The evolving field of persuasive and behavior change technology is increasingly targeted at influencing behavior in the area of health and wellness. This paper provides an empirical review of 16 years (85 papers) of literature on persuasive technology for health and wellness to: (1.) answer important questions regarding the effectiveness of persuasive technology for health and wellness, (2.) summarize and highlight trends in the technology design, research methods, motivational strategies, theories, and health behaviors targeted by research to date, (3.) uncover pitfalls of existing persuasive technological interventions for health and wellness, and (4.) suggest directions for future research.

Personality Traits and Consumer Behavior in the Mobile Context

2013 ◽  
pp. 1-21
Author(s):  
Kaan Varnali
Keyword(s):  
Consumer Behavior ◽  
Personality Traits ◽  
Value Creation ◽  
State Of The Art ◽  
Mobile Services ◽  
The State ◽  
Future Research ◽  
Mobile Context ◽  
And Behavior

Research focusing on consumer behavior in the mobile context is rapidly accumulating. However, the role of personality traits in explaining and predicting users’ perceptions regarding mobile services and behavior within the mobile context is conspicuously under-researched. If consumers are considered as dispositional entities, this lack of researcher interest on the role of personality traits on the value creation processes of mobile consumers should be scrutinized. Striving to provide guidance as to why and how to incorporate personality-based variables within prospective research models attempting to explain and predict consumer behavior in the mobile context, this research critically assesses the-state-of-the-art and presents a conceptual discussion regarding related future research avenues.

Python Code Smell Refactoring Route Generation Based on Association Rule and Correlation

2021 ◽  
Vol 31 (09) ◽  
pp. 1329-1347
Author(s):  
Guanglei Wang ◽  
Junhua Chen ◽  
Jianhua Gao ◽  
Zijie Huang
Keyword(s):  
Association Rules ◽  
Software Quality ◽  
Software Design ◽  
Association Rule ◽  
Strongly Correlated ◽  
Code Smells ◽  
Software Maintainability ◽  
Code Smell ◽  
Spearman’S Correlation ◽  
Java Code

Code smell is a software quality problem caused by software design flaws. Refactoring code smells can improve software maintainability. While prior works mostly focused on Java code smells, only a few prior researches detect and refactor code smells of Python. Therefore, we intend to outline a route (i.e. sequential refactoring operation) for refactoring Python code smells, including LC, LM, LMC, LPL, LSC, LBCL, LLF, MNC, CCC and LTCE. The route could instruct developers to save effort by refactoring the smell strongly correlated with other smells in advance. As a result, more smells could be resolved by a single refactoring. First, we reveal the co-occurrence and the inter-causation between smells. Then, we evaluate the smells’ correlation. Results highlight seven groups of smells with high co-occurrence. Meanwhile, 10 groups of smells correlate with each other in a significant level of Spearman’s correlation coefficient at 0.01. Finally, we generate the refactoring route based on the association rules, we exploit an empirical verification with 10 developers involved. The results of Kendall’s Tau show that the proposed refactoring route has a high inter-agreement with the developer’s perception. In conclusion, we propose four refactoring routes to provide guidance for practitioners, i.e. {LPL [Formula: see text] LLF}, {LPL [Formula: see text] LBCL}, {LPL [Formula: see text] LMC} and {LPL [Formula: see text] LM [Formula: see text] LC [Formula: see text] CCC [Formula: see text] MNC}.

scholarly journals Credit Scoring: A Review on Support Vector Machines and Metaheuristic Approaches

2019 ◽  
Vol 2019 ◽  
pp. 1-30 ◽  
Author(s):  
R. Y. Goh ◽  
L. S. Lee
Keyword(s):  
Support Vector Machines ◽  
State Of The Art ◽  
Credit Scoring ◽  
Future Research ◽  
Support Vector ◽  
Research Gaps ◽  
Hybrid Modelling ◽  
Vector Machines ◽  
Assessment Procedures ◽  
Credit Granting

Development of credit scoring models is important for financial institutions to identify defaulters and nondefaulters when making credit granting decisions. In recent years, artificial intelligence (AI) techniques have shown successful performance in credit scoring. Support Vector Machines and metaheuristic approaches have constantly received attention from researchers in establishing new credit models. In this paper, two AI techniques are reviewed with detailed discussions on credit scoring models built from both methods since 1997 to 2018. The main discussions are based on two main aspects which are model type with issues addressed and assessment procedures. Then, together with the compilation of past experiments results on common datasets, hybrid modelling is the state-of-the-art approach for both methods. Some possible research gaps for future research are identified.

scholarly journals Food Insecurity and Child Development: A State-of-the-Art Review

2021 ◽  
Vol 18 (17) ◽  
pp. 8990
Author(s):  
Danielle Gallegos ◽  
Areana Eivers ◽  
Peter Sondergeld ◽  
Cassandra Pattinson
Keyword(s):  
Child Development ◽  
Food Insecurity ◽  
State Of The Art ◽  
Ecological Factors ◽  
Future Research ◽  
Ecological Framework ◽  
Household Food ◽  
Development Outcomes ◽  
And Behavior ◽  
The Impact

Converging research indicates that household food insecurity impedes children from reaching their full physical, cognitive, and psychosocial potential. This state-of-the-art review examines the last decade of research to: (1) describe the impact of the severity and persistence of food insecurity on child development; (2) use a socio-ecological framework to examine significant proximal and distal factors which may interplay; and (3) outline directions for future research. We conducted a systematic review of six databases of published papers from 2011 to June 2021. The search was limited to high-income countries and children aged from birth to 12 years. From 17,457 papers, 17 studies were included in the final review. Transitioning between food security and food insecurity had a significant and lasting effect on academic/cognitive function and behavior (i.e., externalizing), however less clear relationships were seen for psychosocial outcomes and other behaviors examined (i.e., internalizing). There was significant variation in the measurement and thresholds used to define both food insecurity and child development outcomes. Subsequently, comparisons across studies are difficult. Several future recommendations, including incorporation of socio-ecological factors, is provided. In conclusion, this review supports the link between food insecurity and sub-optimal child development; however, there is an imperative to improve and extend current understanding to ameliorate the causes of food insecurity.

Personality Traits and Consumer Behavior in the Mobile Context

2011 ◽  
Vol 3 (4) ◽  
pp. 1-20 ◽  
Author(s):  
Kaan Varnali
Keyword(s):  
Consumer Behavior ◽  
Personality Traits ◽  
Value Creation ◽  
State Of The Art ◽  
Mobile Services ◽  
The State ◽  
Future Research ◽  
Mobile Context ◽  
And Behavior

Research focusing on consumer behavior in the mobile context is rapidly accumulating. However, the role of personality traits in explaining and predicting users’ perceptions regarding mobile services and behavior within the mobile context is conspicuously under-researched. If consumers are considered as dispositional entities, this lack of researcher interest on the role of personality traits on the value creation processes of mobile consumers should be scrutinized. Striving to provide guidance as to why and how to incorporate personality-based variables within prospective research models attempting to explain and predict consumer behavior in the mobile context, this research critically assesses the-state-of-the-art and presents a conceptual discussion regarding related future research avenues.

Detection of Shotgun Surgery and Message Chain Code Smells using Machine Learning Techniques

2019 ◽  
Vol 6 (2) ◽  
pp. 34-50
Author(s):  
Thirupathi Guggulothu ◽  
Salman Abdul Moiz
Keyword(s):  
High Performance ◽  
Machine Learning Techniques ◽  
Classification Algorithms ◽  
Code Smells ◽  
Design Problems ◽  
Chain Code ◽  
Learning Techniques ◽  
Machine Leaning ◽  
Code Smell ◽  
Better Than

Code smell is an inherent property of software that results in design problems which makes the software hard to extend, understand, and maintain. In the literature, several tools are used to detect code smell that are informally defined or subjective in nature due to varying results of the code smell. To resolve this, machine leaning (ML) techniques are proposed and learn to distinguish the characteristics of smelly and non-smelly code elements (classes or methods). However, the dataset constructed by the ML techniques are based on the tools and manually validated code smell samples. In this article, instead of using tools and manual validation, the authors considered detection rules for identifying the smell then applied unsupervised learning for validation to construct two smell datasets. Then, applied classification algorithms are used on the datasets to detect the code smells. The researchers found that all algorithms have achieved high performance in terms of accuracy, F-measure and area under ROC, yet the tree-based classifiers are performing better than other classifiers.

scholarly journals Network Brokerage: An Integrative Review and Future Research Agenda

2020 ◽  
Vol 46 (6) ◽  
pp. 1092-1120 ◽  
Author(s):  
Seok-Woo Kwon ◽  
Emanuela Rondi ◽  
Daniel Z. Levin ◽  
Alfredo De Massis ◽  
Daniel J. Brass
Keyword(s):  
Research Agenda ◽  
Research Area ◽  
Future Research ◽  
Important Research ◽  
Research Gaps ◽  
Comprehensive Review ◽  
Research Areas ◽  
Future Research Agenda ◽  
And Behavior ◽  
Over Time

Network brokerage research has grown rapidly in recent decades, spanning the boundaries of multiple social science disciplines as well as diverse research areas within management. Accordingly, we take stock of the literature on network brokerage and provide guidance on ways to move this burgeoning research area forward. We provide a comprehensive review of this literature, including crucial dimensions of the concept itself in terms of brokerage structure and behavior, a set of key categories of factors surrounding the brokerage concept (antecedents, outcomes, and moderators), and an overview of brokerage dynamics over time. We use these dimensions and categories to depict network brokerage’s theoretical and empirical underpinnings as well as evaluate prior research efforts. In so doing, we offer a means to summarize and synthesize this large, interdisciplinary literature, identify important research gaps, and offer promising directions for future research.

Modeling Design Patterns for Semi-Automatic Reuse in System Design

2010 ◽  
Vol 21 (1) ◽  
pp. 29-57 ◽  
Author(s):  
Galia Shlezinger ◽  
Iris Reinhartz-Berger ◽  
Dov Dori
Keyword(s):  
Software Quality ◽  
Software Design ◽  
Design Pattern ◽  
Design Patterns ◽  
Object Oriented ◽  
Design Problems ◽  
Suggested Approach ◽  
Analysis And Design ◽  
Correct Usage

Design patterns provide reusable solutions for recurring design problems. They constitute an important tool for improving software quality. However, correct usage of design patterns depends to a large extent on the designer. Design patterns often include models that describe the suggested solutions, while other aspects of the patterns are neglected or described informally only in text. Furthermore, design pattern solutions are usually described in an object-oriented fashion that is too close to the implementation, masking the essence of and motivation behind a particular design pattern. We suggest an approach to modeling the different aspects of design patterns and semi-automatically utilizing these models to improve software design. Evaluating our approach on commonly used design patterns and a case study of an automatic application for composing, taking, checking, and grading analysis and design exams, we found that the suggested approach successfully locates the main design problems modeled by the selected design patterns.

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