Pub Date : 2018-10-01DOI: 10.1109/VLHCC.2018.8506514
Christopher J. Mendez, Zoe Steine-Hanson, A. Oleson, Amber Horvath, Charles Hill, C. Hilderbrand, A. Sarma, M. Burnett
How can we support software professionals who want to build human-adaptive sociotechnical systems? Building such systems requires skills some developers may lack, such as applying human-centric concepts to the software they develop and/or mentally modeling other people. Effective socio-technical methods exist to help, but most are manual and cognitively burdensome. In this paper, we investigate ways semi-automating a socio-technical method might help, using as our lens GenderMag, a method that requires people to mentally model people with genders different from their own. Toward this end, we created the GenderMag Recorder's Assistant, a semi-automated visual tool, and conducted a small field study and a 92-participant controlled study. Results of our investigation revealed ways the tool helped with cognitive load and ways it did not; unforeseen advantages of the tool in increasing participants' engagement with the method; and a few unforeseen advantages of the manual approach as well.
{"title":"Semi-Automating (or not) a Socio-Technical Method for Socio-Technical Systems","authors":"Christopher J. Mendez, Zoe Steine-Hanson, A. Oleson, Amber Horvath, Charles Hill, C. Hilderbrand, A. Sarma, M. Burnett","doi":"10.1109/VLHCC.2018.8506514","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506514","url":null,"abstract":"How can we support software professionals who want to build human-adaptive sociotechnical systems? Building such systems requires skills some developers may lack, such as applying human-centric concepts to the software they develop and/or mentally modeling other people. Effective socio-technical methods exist to help, but most are manual and cognitively burdensome. In this paper, we investigate ways semi-automating a socio-technical method might help, using as our lens GenderMag, a method that requires people to mentally model people with genders different from their own. Toward this end, we created the GenderMag Recorder's Assistant, a semi-automated visual tool, and conducted a small field study and a 92-participant controlled study. Results of our investigation revealed ways the tool helped with cognitive load and ways it did not; unforeseen advantages of the tool in increasing participants' engagement with the method; and a few unforeseen advantages of the manual approach as well.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124229672","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506526
Darius Cepulis, Nan Niu
Work in information foraging theory presumes that software developers have a predefined patch of information (e.g., a Java class) within which they conduct a search task. However, not all tasks have easily delineated patches. Requirements traceability, where a developer must traverse a combination of technical artifacts and social structures, is one such task. We examine requirements socio-technical graphs to describe the key relationships that a patch should encode to assist in a requirements traceability task. We then present an algorithm, based on spreading activation, which extracts a relevant set of these relationships as a patch. We test this algorithm in requirements repositories of four open-source software projects. Our results show that applying this algorithm creates useful patches with reduced superfluous information.
{"title":"Creating Socio-Technical Patches for Information Foraging: A Requirements Traceability Case Study","authors":"Darius Cepulis, Nan Niu","doi":"10.1109/VLHCC.2018.8506526","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506526","url":null,"abstract":"Work in information foraging theory presumes that software developers have a predefined patch of information (e.g., a Java class) within which they conduct a search task. However, not all tasks have easily delineated patches. Requirements traceability, where a developer must traverse a combination of technical artifacts and social structures, is one such task. We examine requirements socio-technical graphs to describe the key relationships that a patch should encode to assist in a requirements traceability task. We then present an algorithm, based on spreading activation, which extracts a relevant set of these relationships as a patch. We test this algorithm in requirements repositories of four open-source software projects. Our results show that applying this algorithm creates useful patches with reduced superfluous information.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"34 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113958281","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506555
Mary Beth Kery
Although a wide range of professional and end-user programmers want to engage today with data science programming, this form of programming presents unique challenges. For instance, data science tasks typically require exploratory iterations: coding and running many different approaches to reach a desired result [1]–[3]. In a body of research building towards my thesis, I have interleaved behavioral studies of data scientists with systems building research towards scaffolding new forms of support for keeping track of iterations during this experiment-driven form of work.
{"title":"Towards Scaffolding Complex Exploratory Data Science Programming Practices","authors":"Mary Beth Kery","doi":"10.1109/VLHCC.2018.8506555","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506555","url":null,"abstract":"Although a wide range of professional and end-user programmers want to engage today with data science programming, this form of programming presents unique challenges. For instance, data science tasks typically require exploratory iterations: coding and running many different approaches to reach a desired result [1]–[3]. In a body of research building towards my thesis, I have interleaved behavioral studies of data scientists with systems building research towards scaffolding new forms of support for keeping track of iterations during this experiment-driven form of work.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124140998","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506548
Tanmaya Mahapatra, C. Prehofer, I. Gerostathopoulos, Ioannis Varsamidakis
Consumption of data streams generated from IoT devices during IoT application development is gaining prominence as the data insights are paramount for building high-impact applications. IoT mashup tools, i.e. tools that aim to reduce the development effort in the context of IoT via graphical flow-based programming, suffer from various architectural limitations which prevent the usage of data analytics as part of the application logic. Moreover, the approach of flow-based programming is not conducive for stream processing. We introduce our new mashup tool aFlux based on actor system with concurrent and asynchronous execution semantics to overcome the prevalent architectural limitations and support in-built user-configurable stream processing capabilities. Furthermore, parametrizing the control points of stream processing in the tool enables non-experts to use various stream processing styles and deal with the subtle nuances of stream processing effortlessly. We validate the effectiveness of parametrization in a real-time traffic use case.
{"title":"Stream Analytics in IoT Mashup Tools","authors":"Tanmaya Mahapatra, C. Prehofer, I. Gerostathopoulos, Ioannis Varsamidakis","doi":"10.1109/VLHCC.2018.8506548","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506548","url":null,"abstract":"Consumption of data streams generated from IoT devices during IoT application development is gaining prominence as the data insights are paramount for building high-impact applications. IoT mashup tools, i.e. tools that aim to reduce the development effort in the context of IoT via graphical flow-based programming, suffer from various architectural limitations which prevent the usage of data analytics as part of the application logic. Moreover, the approach of flow-based programming is not conducive for stream processing. We introduce our new mashup tool aFlux based on actor system with concurrent and asynchronous execution semantics to overcome the prevalent architectural limitations and support in-built user-configurable stream processing capabilities. Furthermore, parametrizing the control points of stream processing in the tool enables non-experts to use various stream processing styles and deal with the subtle nuances of stream processing effortlessly. We validate the effectiveness of parametrization in a real-time traffic use case.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130832373","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506540
Rahul Pandita, Chris Parnin, F. Hermans, E. Murphy-Hill
The popularity of end-user programming has lead to diverse end-user development environments. Despite accurate and efficient tools available in such environments, end-user programmers often manually complete tasks. What are the consequences of rejecting these tools? In this paper, we answer this question by studying end-user programmers completing four tasks with and without tools. In analyzing 111 solutions to each of these tasks, we observe that neither tool use nor tool rejection was consistently more accurate or efficient. In some cases, tool users took nearly twice as long to solve problems and over-relied on tools, causing errors in 95% of solutions. Compared to manual task completion, the primary benefit of tool use was narrowing the kinds of errors that users made. We also observed that partial tool use can be worse than no tool use at all.
{"title":"No half-measures: A study of manual and tool-assisted end-user programming tasks in Excel","authors":"Rahul Pandita, Chris Parnin, F. Hermans, E. Murphy-Hill","doi":"10.1109/VLHCC.2018.8506540","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506540","url":null,"abstract":"The popularity of end-user programming has lead to diverse end-user development environments. Despite accurate and efficient tools available in such environments, end-user programmers often manually complete tasks. What are the consequences of rejecting these tools? In this paper, we answer this question by studying end-user programmers completing four tasks with and without tools. In analyzing 111 solutions to each of these tasks, we observe that neither tool use nor tool rejection was consistently more accurate or efficient. In some cases, tool users took nearly twice as long to solve problems and over-relied on tools, causing errors in 95% of solutions. Compared to manual task completion, the primary benefit of tool use was narrowing the kinds of errors that users made. We also observed that partial tool use can be worse than no tool use at all.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127808907","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506497
D. Long, Kun Wang, Jason Carter, P. Dewan
Automatic detection of programmer difficulty can help programmers receive timely assistance. Aggregate statistics are often used to evaluate difficulty detection algorithms, but this paper demonstrates that a more human-centered analysis can lead to additional insights. We have developed a novel visualization tool designed to assist researchers in improving difficulty detection algorithms. Assuming that data exists from a study in which both predicted programmer difficulties and ground truth were recorded while running an online algorithm for detecting difficulties, the tool allows researchers to interactively travel through a timeline showing the correlation between values of the features used to make predictions, difficulty predictions made by the online algorithm, and ground truth. We used the tool to improve an existing online algorithm based on a study involving the development of a GUI in Java. Episodes of difficulty predicted by the previously developed algorithm were correlated with features extracted from participant logs of interaction with the programming environment and web browser. The visualizations produced from the tool contribute to a better understanding of programmer actions during periods of difficulty, help to identify specific issues with the previous prediction algorithm, and suggest potential solutions to these issues. Thus, the information gained using this novel tool can be used to improve algorithms that help developers receive assistance at appropriate times.
{"title":"Graphical Visualization of Difficulties Predicted from interaction Logs","authors":"D. Long, Kun Wang, Jason Carter, P. Dewan","doi":"10.1109/VLHCC.2018.8506497","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506497","url":null,"abstract":"Automatic detection of programmer difficulty can help programmers receive timely assistance. Aggregate statistics are often used to evaluate difficulty detection algorithms, but this paper demonstrates that a more human-centered analysis can lead to additional insights. We have developed a novel visualization tool designed to assist researchers in improving difficulty detection algorithms. Assuming that data exists from a study in which both predicted programmer difficulties and ground truth were recorded while running an online algorithm for detecting difficulties, the tool allows researchers to interactively travel through a timeline showing the correlation between values of the features used to make predictions, difficulty predictions made by the online algorithm, and ground truth. We used the tool to improve an existing online algorithm based on a study involving the development of a GUI in Java. Episodes of difficulty predicted by the previously developed algorithm were correlated with features extracted from participant logs of interaction with the programming environment and web browser. The visualizations produced from the tool contribute to a better understanding of programmer actions during periods of difficulty, help to identify specific issues with the previous prediction algorithm, and suggest potential solutions to these issues. Thus, the information gained using this novel tool can be used to improve algorithms that help developers receive assistance at appropriate times.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131882642","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506527
Giuliano Ragusa, Henrique Henriques
Code review is a common practice in the software industry, in contexts spanning from open to close source, and from free to proprietary software. Modern code reviews are essentially conducted using cloud-based dedicated tools. Existing review tools focus in textual code. In contrast, support of low-code software languages, namely Visual Programming Languages (VPLs), is not readily available. This presents a challenge for the effectiveness of the review process with a VPL. This showpiece will present VPLreviewer, a code review tool for VPLs. VPLreviewer provides a wide range of mechanisms previously not available to a VPL. It is expected to improve of communication among the stakeholders who have to review artifacts constructed with VPLs, with mechanisms that are easy to learn, use and understand.
{"title":"Code review tool for Visual Programming Languages","authors":"Giuliano Ragusa, Henrique Henriques","doi":"10.1109/VLHCC.2018.8506527","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506527","url":null,"abstract":"Code review is a common practice in the software industry, in contexts spanning from open to close source, and from free to proprietary software. Modern code reviews are essentially conducted using cloud-based dedicated tools. Existing review tools focus in textual code. In contrast, support of low-code software languages, namely Visual Programming Languages (VPLs), is not readily available. This presents a challenge for the effectiveness of the review process with a VPL. This showpiece will present VPLreviewer, a code review tool for VPLs. VPLreviewer provides a wide range of mechanisms previously not available to a VPL. It is expected to improve of communication among the stakeholders who have to review artifacts constructed with VPLs, with mechanisms that are easy to learn, use and understand.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114696142","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506537
Damian Nicolalde-Rodriguez, J. Urquiza-Fuentes
This work studies the effect of using software visualization to teach syntax directed translation, a complex topic within compiler subjects. A trial was conducted with 34 students using LISA as the visualization tool. It was divided in two phases. Firstly, student's experience during compilers construction labs was studied, comparing LISA versus CUP. All participants used both tools and answered a questionnaire. LISA was scored as more motivational and easier to use. Moreover, key theoretical concepts were better identified with LISA. Secondly, a typical lecture (control group) was compared against a lecture using LISA (treatment group). Students were randomly distributed between both groups and answered a knowledge test following the lectures. Results showed that the treatment group significantly outperformed the control group. However, areas for improvement have been detected even in the treatment group. These improvements could be addressed by enhancing the visualization tool with features to increase student engagement.
{"title":"Educational Impact of Syntax Directed Translation Visualization, a Preliminary Study","authors":"Damian Nicolalde-Rodriguez, J. Urquiza-Fuentes","doi":"10.1109/VLHCC.2018.8506537","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506537","url":null,"abstract":"This work studies the effect of using software visualization to teach syntax directed translation, a complex topic within compiler subjects. A trial was conducted with 34 students using LISA as the visualization tool. It was divided in two phases. Firstly, student's experience during compilers construction labs was studied, comparing LISA versus CUP. All participants used both tools and answered a questionnaire. LISA was scored as more motivational and easier to use. Moreover, key theoretical concepts were better identified with LISA. Secondly, a typical lecture (control group) was compared against a lecture using LISA (treatment group). Students were randomly distributed between both groups and answered a knowledge test following the lectures. Results showed that the treatment group significantly outperformed the control group. However, areas for improvement have been detected even in the treatment group. These improvements could be addressed by enhancing the visualization tool with features to increase student engagement.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123603616","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506542
Benjamin T. Jones
Despite the increasing need for computer assistance in solving problems involving complex systems and large amount of data, professional mathematicians, scientists, and engineers currently avoid the use of computer algebra systems during creative problem-solving phases of their work due to problems with transparency, familiarity, and inflexibility in input. I have designed and prototyped a new approach to interaction with computer algebra systems that is compatible with current working styles, flexible in its input and output. I propose a user study to validate this tool, and tool extensions to allow creative problem solvers to interactively define their own notation as they work.
{"title":"Human-AI Interaction in Symbolic Problem Solving","authors":"Benjamin T. Jones","doi":"10.1109/VLHCC.2018.8506542","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506542","url":null,"abstract":"Despite the increasing need for computer assistance in solving problems involving complex systems and large amount of data, professional mathematicians, scientists, and engineers currently avoid the use of computer algebra systems during creative problem-solving phases of their work due to problems with transparency, familiarity, and inflexibility in input. I have designed and prototyped a new approach to interaction with computer algebra systems that is compatible with current working styles, flexible in its input and output. I propose a user study to validate this tool, and tool extensions to allow creative problem solvers to interactively define their own notation as they work.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130136515","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 : 2018-10-01DOI: 10.1109/VLHCC.2018.8506561
L. Lyon, C. Clayton, Emilv Green
Tinkering has been found to be beneficial to learning, yet women report being disinclined to tinker with software even though their tinkering can be more effective than men's. This paper reports on a real-world study of how female end-user programmers tinker with new and existing code and what makes their tinkering successful. Findings show that tinkering falls into two main categories: testing an educated guess (more successful) or haphazard trial and error (less successful). In addition, learners occasionally do not tinker to test a successful solution but rather wait to ask another for confirmation of their educated guess before proceeding. Conclusions from this work show that tinkering leads to success when participants are thinking critically about what the code is doing and have hypothesized expected results from code changes. These findings suggest that designers of end-user programmer instructional materials would assist learners by giving explicit tools and techniques that foster successful tinkering.
{"title":"Tinkering in the Wild: What Leads to Success for Female End-User Programmers?","authors":"L. Lyon, C. Clayton, Emilv Green","doi":"10.1109/VLHCC.2018.8506561","DOIUrl":"https://doi.org/10.1109/VLHCC.2018.8506561","url":null,"abstract":"Tinkering has been found to be beneficial to learning, yet women report being disinclined to tinker with software even though their tinkering can be more effective than men's. This paper reports on a real-world study of how female end-user programmers tinker with new and existing code and what makes their tinkering successful. Findings show that tinkering falls into two main categories: testing an educated guess (more successful) or haphazard trial and error (less successful). In addition, learners occasionally do not tinker to test a successful solution but rather wait to ask another for confirmation of their educated guess before proceeding. Conclusions from this work show that tinkering leads to success when participants are thinking critically about what the code is doing and have hypothesized expected results from code changes. These findings suggest that designers of end-user programmer instructional materials would assist learners by giving explicit tools and techniques that foster successful tinkering.","PeriodicalId":444336,"journal":{"name":"2018 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC)","volume":"61 26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126385947","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：