Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00048
Wen-Xin Zhang
Coverage-Guided fuzzing is the type of fuzzing which focuses on the code or branch coverage. It is mainly efficient in detecting buffer overflow. For the code coverage, it is an important parameter of performance evaluation of the Coverage-Guided fuzzing tools, since the higher coverage means higher possibility of bug detection. However, the timeout set for the fuzzing also affects the efficiency, due to the fact that the growth rate of code coverage will gradually become slower as the running time becoming longer. Setting a timeout that is too long cannot help improving the coverage nor the bug detected, and it will be a complete waste of time. Since selecting the fuzzing time might be quite confusing for testers, in this paper, the author decided to discover the relationship of the growth of the coverage and the running time of the. AFL and FuzzFactory were used for the evaluation and the timeout were set as 1 second, 1 minute, 1 hour, 6 hours and 12 hours respectively. The results showed the relationship between fuzzing time and the performance, for all fuzzers and the effect between different fuzzers.
{"title":"Obtaining Fuzzing Results with Different Timeouts","authors":"Wen-Xin Zhang","doi":"10.1109/ICSTW55395.2022.00048","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00048","url":null,"abstract":"Coverage-Guided fuzzing is the type of fuzzing which focuses on the code or branch coverage. It is mainly efficient in detecting buffer overflow. For the code coverage, it is an important parameter of performance evaluation of the Coverage-Guided fuzzing tools, since the higher coverage means higher possibility of bug detection. However, the timeout set for the fuzzing also affects the efficiency, due to the fact that the growth rate of code coverage will gradually become slower as the running time becoming longer. Setting a timeout that is too long cannot help improving the coverage nor the bug detected, and it will be a complete waste of time. Since selecting the fuzzing time might be quite confusing for testers, in this paper, the author decided to discover the relationship of the growth of the coverage and the running time of the. AFL and FuzzFactory were used for the evaluation and the timeout were set as 1 second, 1 minute, 1 hour, 6 hours and 12 hours respectively. The results showed the relationship between fuzzing time and the performance, for all fuzzers and the effect between different fuzzers.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123118387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00051
J. Hagar
This paper presents definitions of test architecture views, viewpoints, and containers. The paper encourages debate within the modelling and architecture community and builds on previous work and papers. There are job postings for test architects. However, many testers and system architects do not consider test modeling and planning to include test architectures, views, viewpoints, and contents. The world of standards, particularly test standards, has not yet reached a consensus on software test architectures. This paper also presents definitions and considerations for architectural elements and concepts within a test perspective.
{"title":"Software Architecture Elements Applied to Software Test: View, Viewpoints and Containers","authors":"J. Hagar","doi":"10.1109/ICSTW55395.2022.00051","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00051","url":null,"abstract":"This paper presents definitions of test architecture views, viewpoints, and containers. The paper encourages debate within the modelling and architecture community and builds on previous work and papers. There are job postings for test architects. However, many testers and system architects do not consider test modeling and planning to include test architectures, views, viewpoints, and contents. The world of standards, particularly test standards, has not yet reached a consensus on software test architectures. This paper also presents definitions and considerations for architectural elements and concepts within a test perspective.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"325 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115761985","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00021
Zujany Salazar, A. Cavalli, Wissam Mallouli, Filip Sebek, Fatiha Zaïdi, M. Rakoczy
Safety monitoring of Industrial Control Systems (ICS) is a must for optimal operation of safe manufacturing facilities. Failures and miss-behaviours seldomly occur without prior warning, but these warnings are often subtle, requiring careful analysis of data by experienced personnel for early detection. Monitoring function allows to promptly take adequate corrective actions in order to maximize uptime and increase trust of running industrial systems. In this paper, we present two main approaches of monitoring techniques implemented in the Montimage MMT tool. The first approach is a signature-based approach, where there are safety properties to be checked on the ICS logs, and the other relies on Machine Learning (ML) to detect anomalies. Both methods have been applied to check safety on an industrial system: a crane load position system provided by ABB. Several experiments have been performed to check if the information provided by a system’s PLC is correct, guarantying the safety of the system.
{"title":"Monitoring Approaches for Security and Safety Analysis: Application to a Load Position System","authors":"Zujany Salazar, A. Cavalli, Wissam Mallouli, Filip Sebek, Fatiha Zaïdi, M. Rakoczy","doi":"10.1109/ICSTW55395.2022.00021","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00021","url":null,"abstract":"Safety monitoring of Industrial Control Systems (ICS) is a must for optimal operation of safe manufacturing facilities. Failures and miss-behaviours seldomly occur without prior warning, but these warnings are often subtle, requiring careful analysis of data by experienced personnel for early detection. Monitoring function allows to promptly take adequate corrective actions in order to maximize uptime and increase trust of running industrial systems. In this paper, we present two main approaches of monitoring techniques implemented in the Montimage MMT tool. The first approach is a signature-based approach, where there are safety properties to be checked on the ICS logs, and the other relies on Machine Learning (ML) to detect anomalies. Both methods have been applied to check safety on an industrial system: a crane load position system provided by ABB. Several experiments have been performed to check if the information provided by a system’s PLC is correct, guarantying the safety of the system.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121927060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/icstw55395.2022.00007
{"title":"Message from the AIST 2022 Chair","authors":"","doi":"10.1109/icstw55395.2022.00007","DOIUrl":"https://doi.org/10.1109/icstw55395.2022.00007","url":null,"abstract":"","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124837583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00022
Rui Huang, Chang Rao, Yu Lei, Jin Guo, Yadong Zhang
The onboard Automatic Train Protection System (ATP) is one of the key components of the Chinese high-speed railway train control system. ATP is a safety-critical system since a failure of ATP could result in serious accidents. This paper reports a combinatorial testing practice performed in testing one of the major ATP functions, i.e. Balise Information Processing (BIP). We created one input model for each of the total 7 application scenarios of BIP. We generated a total of 178 pair-wise tests using the ACTS tool. We executed all these 178 tests, among which 172 tests passed and 6 tests failed. We found a total of 5 new faults, including 2 critical faults, and 3 major faults. We believe that combinatorial testing can be a very effective approach to testing large and complex real-world systems such as ATP.
{"title":"Applying Combinatorial Testing to High-Speed Railway Automatic Train Protection System","authors":"Rui Huang, Chang Rao, Yu Lei, Jin Guo, Yadong Zhang","doi":"10.1109/ICSTW55395.2022.00022","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00022","url":null,"abstract":"The onboard Automatic Train Protection System (ATP) is one of the key components of the Chinese high-speed railway train control system. ATP is a safety-critical system since a failure of ATP could result in serious accidents. This paper reports a combinatorial testing practice performed in testing one of the major ATP functions, i.e. Balise Information Processing (BIP). We created one input model for each of the total 7 application scenarios of BIP. We generated a total of 178 pair-wise tests using the ACTS tool. We executed all these 178 tests, among which 172 tests passed and 6 tests failed. We found a total of 5 new faults, including 2 critical faults, and 3 major faults. We believe that combinatorial testing can be a very effective approach to testing large and complex real-world systems such as ATP.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134036226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00058
Aftab Hussain, Mohammad Amin Alipour
Software fuzzing mutates bytes in test seeds to explore different behaviors of a program under test. Initial seeds can have great impact on the performance of fuzzing campaigns. Mutating a lot of uninteresting bytes in a large seed wastes the fuzzing resources and slows down the exploration of important parts of the program. However, identifying "uninteresting" bytes is difficult. In this paper, we propose and evaluate Diar, a simple approach for mitigating the problem of uninteresting bytes in the seeds. In this approach, we call a byte uninteresting if its removal does not substantially change the coverage of a seed. Next, we use the non-adequate test reduction technique to remove such bytes in the seeds. We performed a preliminary study by applying this approach on the initial seeds in two fuzzing campaigns. Our results suggest fuzzing campaigns that start with reduced seeds, find new paths faster, and can produce higher coverage overall.
{"title":"Removing Uninteresting Bytes in Software Fuzzing","authors":"Aftab Hussain, Mohammad Amin Alipour","doi":"10.1109/ICSTW55395.2022.00058","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00058","url":null,"abstract":"Software fuzzing mutates bytes in test seeds to explore different behaviors of a program under test. Initial seeds can have great impact on the performance of fuzzing campaigns. Mutating a lot of uninteresting bytes in a large seed wastes the fuzzing resources and slows down the exploration of important parts of the program. However, identifying \"uninteresting\" bytes is difficult. In this paper, we propose and evaluate Diar, a simple approach for mitigating the problem of uninteresting bytes in the seeds. In this approach, we call a byte uninteresting if its removal does not substantially change the coverage of a seed. Next, we use the non-adequate test reduction technique to remove such bytes in the seeds. We performed a preliminary study by applying this approach on the initial seeds in two fuzzing campaigns. Our results suggest fuzzing campaigns that start with reduced seeds, find new paths faster, and can produce higher coverage overall.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134539620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00036
Vahana Dorcis, F. Bouquet, Frédéric Dadeau
Our objective is to define a regression testing approach that relies on usage traces that capture the behaviours of the system when exploited by the users. We achieve that by studying and evaluating clustering techniques applied to usage traces for regression tests selection. We first evaluate the existing vectorization methods and the clusters computed by the classical algorithms, and then, evaluate the clusters using existing state-of-the-art validation methods. We conclude that neither the existing clustering algorithms, nor the seminal clustering evaluation techniques are well-suited for identifying representative behaviours of the system when applied to usage traces. Thus, we propose a custom clustering algorithm and a dedicated cluster evaluation index for selecting usage trace to be used as regression tests.
{"title":"Clustering of Usage Traces for Regression Test Cases Selection","authors":"Vahana Dorcis, F. Bouquet, Frédéric Dadeau","doi":"10.1109/ICSTW55395.2022.00036","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00036","url":null,"abstract":"Our objective is to define a regression testing approach that relies on usage traces that capture the behaviours of the system when exploited by the users. We achieve that by studying and evaluating clustering techniques applied to usage traces for regression tests selection. We first evaluate the existing vectorization methods and the clusters computed by the classical algorithms, and then, evaluate the clusters using existing state-of-the-art validation methods. We conclude that neither the existing clustering algorithms, nor the seminal clustering evaluation techniques are well-suited for identifying representative behaviours of the system when applied to usage traces. Thus, we propose a custom clustering algorithm and a dedicated cluster evaluation index for selecting usage trace to be used as regression tests.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133864988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00018
J. Peltomäki, Ivan Porres
We consider the problem of falsifying safety requirements of Cyber-Physical Systems expressed in signal temporal logic (STL). This problem can be turned into an optimization problem via STL robustness functions. In this paper, our focus is in falsifying systems with multiple requirements. We propose to solve such conjunctive requirements using online generative adversarial networks (GANs) as test generators. Our main contribution is an algorithm which falsifies a conjunctive requirement φ1 ∧•⋯•∧φn by using a GAN for each requirement φi separately. Using ideas from multi-armed bandit algorithms, our algorithm only trains a single GAN at every step, which saves resources. Our experiments indicate that, in addition to saving resources, this multi-armed bandit algorithm can falsify requirements with fewer number of executions on the system under test when compared to (i) an algorithm training a single GAN for the complete conjunctive requirement and (ii) an algorithm always training n GANs at each step.
{"title":"Falsification of Multiple Requirements for Cyber-Physical Systems Using Online Generative Adversarial Networks and Multi-Armed Bandits","authors":"J. Peltomäki, Ivan Porres","doi":"10.1109/ICSTW55395.2022.00018","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00018","url":null,"abstract":"We consider the problem of falsifying safety requirements of Cyber-Physical Systems expressed in signal temporal logic (STL). This problem can be turned into an optimization problem via STL robustness functions. In this paper, our focus is in falsifying systems with multiple requirements. We propose to solve such conjunctive requirements using online generative adversarial networks (GANs) as test generators. Our main contribution is an algorithm which falsifies a conjunctive requirement φ1 ∧•⋯•∧φn by using a GAN for each requirement φi separately. Using ideas from multi-armed bandit algorithms, our algorithm only trains a single GAN at every step, which saves resources. Our experiments indicate that, in addition to saving resources, this multi-armed bandit algorithm can falsify requirements with fewer number of executions on the system under test when compared to (i) an algorithm training a single GAN for the complete conjunctive requirement and (ii) an algorithm always training n GANs at each step.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"335 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115843525","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00049
Yasuaki Hiruta, Hidetoshi Suhara, Y. Nishi
Model-based Testing (MBT), is an important testing technology to generate test cases automatically by MBT tools. While a single MBT tool supports a single MBT model, it is necessary to integrate implicitly multiple models to detect failures manually such as exploratory testing in industry. A single-model-MBT lacks fidelity which means the ability to generate the required test cases. In this research, we analyse such failures to identify implicit multiple models. Several patterns on integration of multiple models are discovered. This paper introduces the patterns and examples of test case generation to improve fidelity.
{"title":"Patterns to Improve Fidelity for Model-Based Testing","authors":"Yasuaki Hiruta, Hidetoshi Suhara, Y. Nishi","doi":"10.1109/ICSTW55395.2022.00049","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00049","url":null,"abstract":"Model-based Testing (MBT), is an important testing technology to generate test cases automatically by MBT tools. While a single MBT tool supports a single MBT model, it is necessary to integrate implicitly multiple models to detect failures manually such as exploratory testing in industry. A single-model-MBT lacks fidelity which means the ability to generate the required test cases. In this research, we analyse such failures to identify implicit multiple models. Several patterns on integration of multiple models are discovered. This paper introduces the patterns and examples of test case generation to improve fidelity.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"350 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123328887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-04-01DOI: 10.1109/ICSTW55395.2022.00046
Marko Savić, M. Mäntylä, Maëlick Claes
Despite the widespread of test automation, automatic testing of graphical user interfaces (GUI) remains a challenge. This is partly due to the difficulty of reliably identifying GUI elements over different versions of a given software system. Machine vision techniques could be a potential way of addressing this issue by automatically identifying GUI elements with the help of machine learning. However, developing a GUI testing tool relying on automatic identification of graphical elements first requires to acquire large amount of labeled data. In this paper, we present Win GUI Crawler, a tool for automatically gathering such data from Microsoft Windows GUI applications. The tool is based on Microsoft Windows Application Driver and performs actions on the GUI using a depth-first traversal of the GUI element tree. For each action performed by the crawler, screenshots are taken and metadata is extracted for each of the different screens. Bounding boxes of GUI elements are then filtered in order to identify what GUI elements are actually visible on the screen. Win GUI Crawler is then evaluated on several popular Windows applications and the current limitations are discussed.
尽管自动化测试的普及，图形用户界面(GUI)的自动化测试仍然是一个挑战。这部分是由于难以在给定软件系统的不同版本上可靠地识别GUI元素。机器视觉技术可以通过在机器学习的帮助下自动识别GUI元素来解决这个问题。然而，开发依赖于图形元素自动识别的GUI测试工具首先需要获取大量的标记数据。在本文中，我们介绍了Win GUI Crawler，一个从Microsoft Windows GUI应用程序自动收集此类数据的工具。该工具基于Microsoft Windows Application Driver，并使用GUI元素树的深度优先遍历在GUI上执行操作。对于爬虫执行的每个操作，都会截取屏幕截图，并为每个不同的屏幕提取元数据。然后过滤GUI元素的边界框，以确定哪些GUI元素在屏幕上实际可见。然后在几种流行的Windows应用程序上对Win GUI Crawler进行了评估，并讨论了当前的限制。
{"title":"Win GUI Crawler: A tool prototype for desktop GUI image and metadata collection","authors":"Marko Savić, M. Mäntylä, Maëlick Claes","doi":"10.1109/ICSTW55395.2022.00046","DOIUrl":"https://doi.org/10.1109/ICSTW55395.2022.00046","url":null,"abstract":"Despite the widespread of test automation, automatic testing of graphical user interfaces (GUI) remains a challenge. This is partly due to the difficulty of reliably identifying GUI elements over different versions of a given software system. Machine vision techniques could be a potential way of addressing this issue by automatically identifying GUI elements with the help of machine learning. However, developing a GUI testing tool relying on automatic identification of graphical elements first requires to acquire large amount of labeled data. In this paper, we present Win GUI Crawler, a tool for automatically gathering such data from Microsoft Windows GUI applications. The tool is based on Microsoft Windows Application Driver and performs actions on the GUI using a depth-first traversal of the GUI element tree. For each action performed by the crawler, screenshots are taken and metadata is extracted for each of the different screens. Bounding boxes of GUI elements are then filtered in order to identify what GUI elements are actually visible on the screen. Win GUI Crawler is then evaluated on several popular Windows applications and the current limitations are discussed.","PeriodicalId":147133,"journal":{"name":"2022 IEEE International Conference on Software Testing, Verification and Validation Workshops (ICSTW)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122920165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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