{"title":"A systematic mapping study for graphical user interface testing on mobile apps","authors":"Liming Nie, Kabir Sulaiman Said, Lingfei Ma, Yaowen Zheng, Yangyang Zhao","doi":"10.1049/sfw2.12123","DOIUrl":"https://doi.org/10.1049/sfw2.12123","url":null,"abstract":"<p>Mobile apps with tested Graphical User Interface (GUI) tend to have higher downloads in the apps store. In recent years, few efforts were made to analyse the research community and research status of the literature for GUI testing on mobile apps, which brings an obstacle to characterise and understand this field. In this study, the authors propose a systematic mapping study to gain insights into the field. First, the authors conduct an extensive search of relevant literature over seven popular digital libraries. From 4427 candidate studies, 114 primary studies published between January 2011 and September 2022 were selected. Next, the authors analyse these primary studies from the perspectives of bibliometric and qualitative analysis. For the bibliometric analysis, first, the authors analyse the popular research topics and their relationships. Second, the authors study the authors' community. For the qualitative analysis, the authors analyse the objectives, approaches and evaluation metrics employed in these primary studies. Their investigation reports several major findings: (1) there are relatively more studies on two topics, that is, test case generation and the automated test; (2) the most productive authors tend to collaborate and often have relatively broad research interests; (3) the functionality is the main objective of GUI testing; the model-based approach is the most widely used.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 3","pages":"249-267"},"PeriodicalIF":1.6,"publicationDate":"2023-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12123","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50118310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-20DOI: 10.1049/sfw2.12104
Amir Sohail Habib, Saif Ur Rehman Khan, Ebubeogu Amarachukwu Felix
{"title":"A systematic review on search-based test suite reduction: State-of-the-art, taxonomy, and future directions","authors":"Amir Sohail Habib, Saif Ur Rehman Khan, Ebubeogu Amarachukwu Felix","doi":"10.1049/sfw2.12104","DOIUrl":"https://doi.org/10.1049/sfw2.12104","url":null,"abstract":"<p>Regression testing remains a promising research area for the last few decades. It is a type of testing that aims at ensuring that recent modifications have not adversely affected the software product. After the introduction of a new change in the system under test, the number of test cases significantly increases to handle the modification. Consequently, it becomes prohibitively expensive to execute all of the generated test cases within the allocated testing time and budget. To address this situation, the test suite reduction (TSR) technique is widely used that focusses on finding a representative test suite without compromising its effectiveness such as fault-detection capability. In this work, a systematic review study is conducted that intends to provide an unbiased viewpoint about TSR based on various types of search algorithms. The study's main objective is to examine and classify the current state-of-the-art approaches used in search-based TSR contexts. To achieve this, a systematic review protocol is adopted and, the most relevant primary studies (57 out of 210) published between 2007 and 2022 are selected. Existing search-based TSR approaches are classified into five main categories, including evolutionary-based, swarm intelligence-based, human-based, physics-based, and hybrid, grounded on the type of employed search algorithm. Moreover, the current work reports the parameter settings according to their category, the type of considered operator(s), and the probabilistic rate that significantly impacts on the quality of the obtained solution. Furthermore, this study describes the comparison baseline techniques that support the empirical comparison regarding the cost-effectiveness of a search-based TSR approach. Finally, it isconcluded that search-based TSR has great potential to optimally solve the TSR problem. In this regard, several potential research directions are outlined as useful for future researchers interested in conducting research in the TSR domain.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 2","pages":"93-136"},"PeriodicalIF":1.6,"publicationDate":"2023-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12104","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50138549","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-18DOI: 10.3390/software2010005
Conrad Stansbury, Alessandra Lanzara
{"title":"AutodiDAQt: Simple Scientific Data Acquisition Software with Analysis-in-the-Loop","authors":"Conrad Stansbury, Alessandra Lanzara","doi":"10.3390/software2010005","DOIUrl":"https://doi.org/10.3390/software2010005","url":null,"abstract":"Scientific data acquisition is a problem domain that has been underserved by its computational tools despite the need to efficiently use hardware, to guarantee validity of the recorded data, and to rapidly test ideas by configuring experiments quickly and inexpensively. High-dimensional physical spectroscopies, such as angle-resolved photoemission spectroscopy, make these issues especially apparent because, while they use expensive instruments to record large data volumes, they require very little acquisition planning. The burden of writing data acquisition software falls to scientists, who are not typically trained to write maintainable software. In this paper, we introduce AutodiDAQt to address these shortfalls in the scientific ecosystem. To ground the discussion, we demonstrate its merits for angle-resolved photoemission spectroscopy and high bandwidth spectroscopies. AutodiDAQt addresses the essential needs for scientific data acquisition by providing simple concurrency, reproducibility, retrospection of the acquisition sequence, and automated user interface generation. Finally, we discuss how AutodiDAQt enables a future of highly efficient machine-learning-in-the-loop experiments and analysis-driven experiments without requiring data acquisition domain expertise by using analysis code for external data acquisition planning.","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"120 1","pages":""},"PeriodicalIF":1.6,"publicationDate":"2023-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77154123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-14DOI: 10.1049/sfw2.12121
Santiago del Rey, Silverio Martínez-Fernández, Antonio Salmerón
{"title":"Bayesian Network analysis of software logs for data-driven software maintenance","authors":"Santiago del Rey, Silverio Martínez-Fernández, Antonio Salmerón","doi":"10.1049/sfw2.12121","DOIUrl":"https://doi.org/10.1049/sfw2.12121","url":null,"abstract":"<p>Software organisations aim to develop and maintain high-quality software systems. Due to large amounts of behaviour data available, software organisations can conduct data-driven software maintenance. Indeed, software quality assurance and improvement programs have attracted many researchers' attention. Bayesian Networks (BNs) are proposed as a log analysis technique to discover poor performance indicators in a system and to explore usage patterns that usually require temporal analysis. For this, an action research study is designed and conducted to improve the software quality and the user experience of a web application using BNs as a technique to analyse software logs. To this aim, three models with BNs are created. As a result, multiple enhancement points have been identified within the application ranging from performance issues and errors to recurring user usage patterns. These enhancement points enable the creation of cards in the Scrum process of the web application, contributing to its data-driven software maintenance. Finally, the authors consider that BNs within quality-aware and data-driven software maintenance have great potential as a software log analysis technique and encourage the community to deepen its possible applications. For this, the applied methodology and a replication package are shared.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 3","pages":"268-286"},"PeriodicalIF":1.6,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12121","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50132745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-11DOI: 10.1049/sfw2.12118
Peilin Zheng, Zibin Zheng, Liang Chen
{"title":"Selecting reliable blockchain peers via hybrid blockchain reliability prediction","authors":"Peilin Zheng, Zibin Zheng, Liang Chen","doi":"10.1049/sfw2.12118","DOIUrl":"https://doi.org/10.1049/sfw2.12118","url":null,"abstract":"<p>Blockchain and blockchain-based decentralised applications have been attracting increasing attention recently. In public blockchain systems, users usually connect to third-party peers or run a peer to join the P2P blockchain network. However, connecting to unreliable blockchain peers will lead to resource waste and even loss of cryptocurrencies by repeated transactions. In order to select reliable blockchain peers, it is urgently needed to evaluate and predict their reliability of them. Faced with this problem, we propose hybrid blockchain reliability prediction (H-BRP), a Hybrid Blockchain Reliability Prediction model, to extract the blockchain reliability factors and then make the personalised prediction for each user. Comprehensive experiments conducted on 100 blockchain requesters and 200 blockchain peers demonstrate the effectiveness of the proposed H-BRP model. Further, the implementation and dataset of 2,000,000 test cases are released.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"362-377"},"PeriodicalIF":1.6,"publicationDate":"2023-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12118","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50149031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-08DOI: 10.1049/sfw2.12120
Gaurav Dhiman, Marcello Carvalho dos Reis, Paulo C. S. Barbosa, Victor Hugo C. de Albuquerque, Sandeep Kautish
{"title":"Retracted: Blockchain-based covert software information transmission for bitcoin","authors":"Gaurav Dhiman, Marcello Carvalho dos Reis, Paulo C. S. Barbosa, Victor Hugo C. de Albuquerque, Sandeep Kautish","doi":"10.1049/sfw2.12120","DOIUrl":"https://doi.org/10.1049/sfw2.12120","url":null,"abstract":"<p>Retraction: [Gaurav Dhiman, Marcello Carvalho dos Reis, Paulo C. S. Barbosa, Victor Hugo C. de Albuquerque, Sandeep Kautish, Blockchain-based covert software information transmission for bitcoin, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12120)].</p><p>The above article from <i>IET Software</i>, published online on 8 February 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"822-831"},"PeriodicalIF":1.6,"publicationDate":"2023-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12120","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50124684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-07DOI: 10.1049/sfw2.12115
Vimal Shanmuganathan, Victor Hugo C. de Albuquerque, Paulo C. S. Barbosa, Marcello Carvalho dos Reis, Gaurav Dhiman, Mohd Asif Shah
{"title":"Retracted: Software based sentiment analysis of clinical data for healthcare sector","authors":"Vimal Shanmuganathan, Victor Hugo C. de Albuquerque, Paulo C. S. Barbosa, Marcello Carvalho dos Reis, Gaurav Dhiman, Mohd Asif Shah","doi":"10.1049/sfw2.12115","DOIUrl":"https://doi.org/10.1049/sfw2.12115","url":null,"abstract":"<p>Retraction: [Vimal Shanmuganathan, Victor Hugo C. de Albuquerque, Paulo C. S. Barbosa, Marcello Carvalho dos Reis, Gaurav Dhiman, Mohd Asif Shah, Software based sentiment analysis of clinical data for healthcare sector, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12115)].</p><p>The above article from <i>IET Software</i>, published online on 7 February 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"787-796"},"PeriodicalIF":1.6,"publicationDate":"2023-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12115","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50123680","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-05DOI: 10.1049/sfw2.12099
Fuyang Li, Wanpeng Lu, Jacky Wai Keung, Xiao Yu, Lina Gong, Juan Li
{"title":"The impact of feature selection techniques on effort-aware defect prediction: An empirical study","authors":"Fuyang Li, Wanpeng Lu, Jacky Wai Keung, Xiao Yu, Lina Gong, Juan Li","doi":"10.1049/sfw2.12099","DOIUrl":"https://doi.org/10.1049/sfw2.12099","url":null,"abstract":"<p>Effort-Aware Defect Prediction (EADP) methods sort software modules based on the defect density and guide the testing team to inspect the modules with high defect density first. Previous studies indicated that some feature selection methods could improve the performance of Classification-Based Defect Prediction (CBDP) models, and the Correlation-based feature subset selection method with the Best First strategy (CorBF) performed the best. However, the practical benefits of feature selection methods on EADP performance are still unknown, and blindly employing the best-performing CorBF method in CBDP to pre-process the defect datasets may not improve the performance of EADP models but possibly result in performance degradation. To assess the impact of the feature selection techniques on EADP, a total of 24 feature selection methods with 10 classifiers embedded in a state-of-the-art EADP model (CBS+) on the 41 PROMISE defect datasets were examined. We employ six evaluation metrics to assess the performance of EADP models comprehensively. The results show that (1) The impact of the feature selection methods varies in classifiers and datasets. (2) The four wrapper-based feature subset selection methods with forwards search, that is, AdaBoost with Forwards Search, Deep Forest with Forwards Search, Random Forest with Forwards Search, and XGBoost with Forwards Search (XGBF) are better than other methods across the studied classifiers and the used datasets. And XGBF with XGBoost as the embedded classifier in CBS+ performs the best on the datasets. (3) The best-performing CorBF method in CBDP does not perform well on the EADP task. (4) The selected features vary with different feature selection methods and different datasets, and the features <i>noc</i> (number of children), <i>ic</i> (inheritance coupling), <i>cbo</i> (coupling between object classes), and <i>cbm</i> (coupling between methods) are frequently selected by the four wrapper-based feature subset selection methods with forwards search. (5) Using AdaBoost, deep forest, random forest, and XGBoost as the base classifiers embedded in CBS+ can achieve the best performance. In summary, we recommend the software testing team should employ XGBF with XGBoost as the embedded classifier in CBS+ to enhance the EADP performance.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 2","pages":"168-193"},"PeriodicalIF":1.6,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12099","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50132134","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-05DOI: 10.1049/sfw2.12119
Shuo Cheng, Yao Lu
{"title":"Retracted: Intelligent design of rural residential environment guided by blockchain under the concept of green low carbon","authors":"Shuo Cheng, Yao Lu","doi":"10.1049/sfw2.12119","DOIUrl":"https://doi.org/10.1049/sfw2.12119","url":null,"abstract":"<p>Retraction: [Shuo Cheng, Yao Lu, Intelligent design of rural residential environment guided by blockchain under the concept of green low carbon, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12119)].</p><p>The above article from <i>IET Software</i>, published online on 5 February 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"809-821"},"PeriodicalIF":1.6,"publicationDate":"2023-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12119","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50130079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
IET SoftwarePub Date : 2023-02-03DOI: 10.1049/sfw2.12117
Tao Cheng, Lianjiang Li
{"title":"Retracted: Optimization of E-commerce platform marketing method and comment recognition model based on deep learning and intelligent blockchain","authors":"Tao Cheng, Lianjiang Li","doi":"10.1049/sfw2.12117","DOIUrl":"https://doi.org/10.1049/sfw2.12117","url":null,"abstract":"<p>Retraction: [Tao Cheng, Lianjiang Li, Optimization of E-commerce platform marketing method and comment recognition model based on deep learning and intelligent blockchain, <i>IET Software</i> 2023 (https://doi.org/10.1049/sfw2.12117)].</p><p>The above article from <i>IET Software</i>, published online on 3 February 2023 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the Editor-in-Chief, Hana Chockler, the Institution of Engineering and Technology (the IET) and John Wiley and Sons Ltd. This article was published as part of a Guest Edited special issue. Following an investigation, the IET and the journal have determined that the article was not reviewed in line with the journal’s peer review standards and there is evidence that the peer review process of the special issue underwent systematic manipulation. Accordingly, we cannot vouch for the integrity or reliability of the content. As such we have taken the decision to retract the article. The authors have been informed of the decision to retract.</p>","PeriodicalId":50378,"journal":{"name":"IET Software","volume":"17 4","pages":"797-808"},"PeriodicalIF":1.6,"publicationDate":"2023-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/sfw2.12117","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50123949","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}