When developing the user interface code of a mobile application, in practice a big gap exists between the digital conceptual drawings of graphic artists and working user interface code. Currently, programmers bridge this gap manually, by reimplementing the conceptual drawings in code, which is cumbersome and expensive. To bridge this gap, we introduce the first technique to automatically Reverse Engineer Mobile Application User Interfaces (REMAUI). On a given input bitmap REMAUI identifies user interface elements such as images, texts, containers, and lists, via computer vision and optical character recognition (OCR) techniques. In our experiments on 488 screenshots of over 100 popular third-party Android and iOS applications, REMAUI-generated user interfaces were similar to the originals, both pixel-by-pixel and in terms of their runtime user interface hierarchies. REMAUI's average overall runtime on a standard desktop computer was 9 seconds.
{"title":"Reverse Engineering Mobile Application User Interfaces with REMAUI (T)","authors":"T. Nguyen, Christoph Csallner","doi":"10.1109/ASE.2015.32","DOIUrl":"https://doi.org/10.1109/ASE.2015.32","url":null,"abstract":"When developing the user interface code of a mobile application, in practice a big gap exists between the digital conceptual drawings of graphic artists and working user interface code. Currently, programmers bridge this gap manually, by reimplementing the conceptual drawings in code, which is cumbersome and expensive. To bridge this gap, we introduce the first technique to automatically Reverse Engineer Mobile Application User Interfaces (REMAUI). On a given input bitmap REMAUI identifies user interface elements such as images, texts, containers, and lists, via computer vision and optical character recognition (OCR) techniques. In our experiments on 488 screenshots of over 100 popular third-party Android and iOS applications, REMAUI-generated user interfaces were similar to the originals, both pixel-by-pixel and in terms of their runtime user interface hierarchies. REMAUI's average overall runtime on a standard desktop computer was 9 seconds.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"36 1","pages":"248-259"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79349571","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}
Dynamic specification mining extracts candidate specifications from logs of execution traces. Existing algorithms differ in the kinds of traces they take as input and in the kinds of candidate specification they present as output. One challenge common to all approaches relates to the faithfulness of the mining results: how can we be confident that the extracted specifications faithfully characterize the program we investigate? Since producing and analyzing traces is costly, how would we know we have seen enough traces? And, how would we know we have not wasted resources and seen too many of them?In this paper we address these important questions by presenting a novel, black box, probabilistic framework based on a notion of log completeness, and by applying it to three different well-known specification mining algorithms from the literature: k-Tails, Synoptic, and mining of scenario-based triggers and effects. Extensive evaluation over 24 models taken from 9 different sources shows the soundness, generalizability, and usefulness of the framework and its contribution to the state-of-the-art in dynamic specification mining.
{"title":"Have We Seen Enough Traces? (T)","authors":"Hila Cohen, S. Maoz","doi":"10.1109/ASE.2015.62","DOIUrl":"https://doi.org/10.1109/ASE.2015.62","url":null,"abstract":"Dynamic specification mining extracts candidate specifications from logs of execution traces. Existing algorithms differ in the kinds of traces they take as input and in the kinds of candidate specification they present as output. One challenge common to all approaches relates to the faithfulness of the mining results: how can we be confident that the extracted specifications faithfully characterize the program we investigate? Since producing and analyzing traces is costly, how would we know we have seen enough traces? And, how would we know we have not wasted resources and seen too many of them?In this paper we address these important questions by presenting a novel, black box, probabilistic framework based on a notion of log completeness, and by applying it to three different well-known specification mining algorithms from the literature: k-Tails, Synoptic, and mining of scenario-based triggers and effects. Extensive evaluation over 24 models taken from 9 different sources shows the soundness, generalizability, and usefulness of the framework and its contribution to the state-of-the-art in dynamic specification mining.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"2 1","pages":"93-103"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76868846","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}
Industry leaders provide concurrent libraries because asynchronous & parallel programming are increasingly in demand: responsiveness, scalability, and high-throughput are key elements of all modern applications. However, we know little about how developers use these concurrent libraries in practice and the developer's toolbox for concurrency is very limited. We present the first study that analyzes the usage of concurrent libraries in large codebases, such as 2258 open-source C# apps comprising 54M SLOC and 1378 open-source Windows Phone apps comprising 12M SLOC. Using this data, we find important problems about use and misuse of concurrency. Inspired by our findings, we designed, evaluated, and implemented several static analyses and refactoring tools.
{"title":"Understanding, Refactoring, and Fixing Concurrency in C#","authors":"Semih Okur","doi":"10.1109/ASE.2015.82","DOIUrl":"https://doi.org/10.1109/ASE.2015.82","url":null,"abstract":"Industry leaders provide concurrent libraries because asynchronous & parallel programming are increasingly in demand: responsiveness, scalability, and high-throughput are key elements of all modern applications. However, we know little about how developers use these concurrent libraries in practice and the developer's toolbox for concurrency is very limited. We present the first study that analyzes the usage of concurrent libraries in large codebases, such as 2258 open-source C# apps comprising 54M SLOC and 1378 open-source Windows Phone apps comprising 12M SLOC. Using this data, we find important problems about use and misuse of concurrency. Inspired by our findings, we designed, evaluated, and implemented several static analyses and refactoring tools.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"73 1","pages":"898-901"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77322973","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}
Florian Angerer, Andreas Grimmer, Herbert Prähofer, P. Grünbacher
Understanding variability is essential to allow the configuration of software systems to diverse requirements. Variability-aware program analysis techniques have been proposed for analyzing the space of program variants. Such techniques are highly beneficial, e.g., to determine the potential impact of changes during maintenance. This paper presents an interprocedural and configuration-aware change impact analysis (CIA) approach for determining possibly impacted products when changing source code of a product family. The approach further supports engineers, who are adapting specific product variants after an initial pre-configuration. The approach can be adapted to work with different variability mechanism, it provides more precise results than existing CIA approaches, and it can be implemented using standard control flow and data flow analysis. Using an industrial product line we report evaluation results on the benefit and performance of the approach.
{"title":"Configuration-Aware Change Impact Analysis (T)","authors":"Florian Angerer, Andreas Grimmer, Herbert Prähofer, P. Grünbacher","doi":"10.1109/ASE.2015.58","DOIUrl":"https://doi.org/10.1109/ASE.2015.58","url":null,"abstract":"Understanding variability is essential to allow the configuration of software systems to diverse requirements. Variability-aware program analysis techniques have been proposed for analyzing the space of program variants. Such techniques are highly beneficial, e.g., to determine the potential impact of changes during maintenance. This paper presents an interprocedural and configuration-aware change impact analysis (CIA) approach for determining possibly impacted products when changing source code of a product family. The approach further supports engineers, who are adapting specific product variants after an initial pre-configuration. The approach can be adapted to work with different variability mechanism, it provides more precise results than existing CIA approaches, and it can be implemented using standard control flow and data flow analysis. Using an industrial product line we report evaluation results on the benefit and performance of the approach.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"103 1","pages":"385-395"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91301066","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}
Manchun Zheng, Michael S. Rogers, Ziqing Luo, Matthew B. Dwyer, Stephen F. Siegel
CIVL is a framework for static analysis and verification of concurrent programs. One of the main challenges to practical application of these techniques is the large number of ways to express concurrency: MPI, OpenMP, CUDA, and Pthreads, for example, are just a few of many "concurrency dialects" in wide use today. These dialects are constantly evolving and it is increasingly common to use several of them in a single "hybrid" program. CIVL addresses these problems by providing a concurrency intermediate verification language, CIVL-C, as well as translators that consume C programs using these dialects and produce CIVL-C. Analysis and verification tools which operate on CIVL-C can then be applied easily to a wide variety of concurrent C programs. We demonstrate CIVL's error detection and verification capabilities on (1) an MPI+OpenMP program that estimates π and contains a subtle race condition, and (2) an MPI-based 1d-wave simulator that fails to conform to a simple sequential implementation.
{"title":"CIVL: Formal Verification of Parallel Programs","authors":"Manchun Zheng, Michael S. Rogers, Ziqing Luo, Matthew B. Dwyer, Stephen F. Siegel","doi":"10.1109/ASE.2015.99","DOIUrl":"https://doi.org/10.1109/ASE.2015.99","url":null,"abstract":"CIVL is a framework for static analysis and verification of concurrent programs. One of the main challenges to practical application of these techniques is the large number of ways to express concurrency: MPI, OpenMP, CUDA, and Pthreads, for example, are just a few of many \"concurrency dialects\" in wide use today. These dialects are constantly evolving and it is increasingly common to use several of them in a single \"hybrid\" program. CIVL addresses these problems by providing a concurrency intermediate verification language, CIVL-C, as well as translators that consume C programs using these dialects and produce CIVL-C. Analysis and verification tools which operate on CIVL-C can then be applied easily to a wide variety of concurrent C programs. We demonstrate CIVL's error detection and verification capabilities on (1) an MPI+OpenMP program that estimates π and contains a subtle race condition, and (2) an MPI-based 1d-wave simulator that fails to conform to a simple sequential implementation.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"107 1","pages":"830-835"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81318707","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}
Temporal properties are useful for describing and reasoning about software behavior, but developers rarely write down temporal specifications of their systems. Prior work on inferring specifications developed tools to extract likely program specifications that fit particular kinds of tool-specific templates. This paper introduces Texada, a new temporal specification mining tool for extracting specifications in linear temporal logic (LTL) of arbitrary length and complexity. Texada takes a user-defined LTL property type template and a log of traces as input and outputs a set of instantiations of the property type (i.e., LTL formulas) that are true on the traces in the log. Texada also supports mining of almost invariants: properties with imperfect confidence. We formally describe Texada's algorithms and evaluate the tool's performance and utility.
{"title":"General LTL Specification Mining (T)","authors":"Caroline Lemieux, Dennis Park, Ivan Beschastnikh","doi":"10.1109/ASE.2015.71","DOIUrl":"https://doi.org/10.1109/ASE.2015.71","url":null,"abstract":"Temporal properties are useful for describing and reasoning about software behavior, but developers rarely write down temporal specifications of their systems. Prior work on inferring specifications developed tools to extract likely program specifications that fit particular kinds of tool-specific templates. This paper introduces Texada, a new temporal specification mining tool for extracting specifications in linear temporal logic (LTL) of arbitrary length and complexity. Texada takes a user-defined LTL property type template and a log of traces as input and outputs a set of instantiations of the property type (i.e., LTL formulas) that are true on the traces in the log. Texada also supports mining of almost invariants: properties with imperfect confidence. We formally describe Texada's algorithms and evaluate the tool's performance and utility.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"41 1","pages":"81-92"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79839554","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}
Michael Vierhauser, Rick Rabiser, P. Grünbacher, Alexander Egyed
Complex software-intensive systems are often described as systems of systems (SoS) comprising heterogeneous architectural elements. As SoS behavior fully emerges during operation only, runtime monitoring is needed to detect deviations from requirements. Today, diverse approaches exist to define and check runtime behavior and performance characteristics. However, existing approaches often focus on specific types of systems and address certain kinds of checks, thus impeding their use in industrial SoS. Furthermore, as many SoS need to run continuously for long periods, the dynamic definition and deployment of constraints needs to be supported. In this paper we describe experiences of developing and applying a DSL-based approach for monitoring an SoS in the domain of industrial automation software. We evaluate both the expressiveness of our DSL as well as the scalability of the constraint checker. We also describe lessons learned.
{"title":"Developing a DSL-Based Approach for Event-Based Monitoring of Systems of Systems: Experiences and Lessons Learned (E)","authors":"Michael Vierhauser, Rick Rabiser, P. Grünbacher, Alexander Egyed","doi":"10.1109/ASE.2015.25","DOIUrl":"https://doi.org/10.1109/ASE.2015.25","url":null,"abstract":"Complex software-intensive systems are often described as systems of systems (SoS) comprising heterogeneous architectural elements. As SoS behavior fully emerges during operation only, runtime monitoring is needed to detect deviations from requirements. Today, diverse approaches exist to define and check runtime behavior and performance characteristics. However, existing approaches often focus on specific types of systems and address certain kinds of checks, thus impeding their use in industrial SoS. Furthermore, as many SoS need to run continuously for long periods, the dynamic definition and deployment of constraints needs to be supported. In this paper we describe experiences of developing and applying a DSL-based approach for monitoring an SoS in the domain of industrial automation software. We evaluate both the expressiveness of our DSL as well as the scalability of the constraint checker. We also describe lessons learned.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"5 1","pages":"715-725"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85599009","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}
J. Rubin, Michael I. Gordon, Nguyen Nguyen, M. Rinard
This paper studies communication patterns in mobile applications. Our analysis shows that 63% of the external communication made by top-popular free Android applications from Google Play has no effect on the user-observable application functionality. To detect such covert communication in an efficient manner, we propose a highly precise and scalable static analysis technique: it achieves 93% precision and 61% recall compared to the empirically determined "ground truth", and runs in a matter of a few minutes. Furthermore, according to human evaluators, in 42 out of 47 cases, disabling connections deemed covert by our analysis leaves the delivered application experience either completely intact or with only insignificant interference. We conclude that our technique is effective for identifying and disabling covert communication. We then use it to investigate communication patterns in the 500 top-popular applications from Google Play.
{"title":"Covert Communication in Mobile Applications (T)","authors":"J. Rubin, Michael I. Gordon, Nguyen Nguyen, M. Rinard","doi":"10.1109/ASE.2015.66","DOIUrl":"https://doi.org/10.1109/ASE.2015.66","url":null,"abstract":"This paper studies communication patterns in mobile applications. Our analysis shows that 63% of the external communication made by top-popular free Android applications from Google Play has no effect on the user-observable application functionality. To detect such covert communication in an efficient manner, we propose a highly precise and scalable static analysis technique: it achieves 93% precision and 61% recall compared to the empirically determined \"ground truth\", and runs in a matter of a few minutes. Furthermore, according to human evaluators, in 42 out of 47 cases, disabling connections deemed covert by our analysis leaves the delivered application experience either completely intact or with only insignificant interference. We conclude that our technique is effective for identifying and disabling covert communication. We then use it to investigate communication patterns in the 500 top-popular applications from Google Play.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"154 1","pages":"647-657"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83431784","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}
Paulo Barros, René Just, Suzanne Millstein, Paul Vines, Werner Dietl, Marcelo d’Amorim, Michael D. Ernst
Implicit or indirect control flow is a transfer of control between procedures using some mechanism other than an explicit procedure call. Implicit control flow is a staple design pattern that adds flexibility to system design. However, it is challenging for a static analysis to compute or verify properties about a system that uses implicit control flow. This paper presents static analyses for two types of implicit control flow that frequently appear in Android apps: Java reflection and Android intents. Our analyses help to resolve where control flows and what data is passed. This information improves the precision of downstream analyses, which no longer need to make conservative assumptions about implicit control flow. We have implemented our techniques for Java. We enhanced an existing security analysis with a more precise treatment of reflection and intents. In a case study involving ten real-world Android apps that use both intents and reflection, the precision of the security analysis was increased on average by two orders of magnitude. The precision of two other downstream analyses was also improved.
{"title":"Static Analysis of Implicit Control Flow: Resolving Java Reflection and Android Intents (T)","authors":"Paulo Barros, René Just, Suzanne Millstein, Paul Vines, Werner Dietl, Marcelo d’Amorim, Michael D. Ernst","doi":"10.1109/ASE.2015.69","DOIUrl":"https://doi.org/10.1109/ASE.2015.69","url":null,"abstract":"Implicit or indirect control flow is a transfer of control between procedures using some mechanism other than an explicit procedure call. Implicit control flow is a staple design pattern that adds flexibility to system design. However, it is challenging for a static analysis to compute or verify properties about a system that uses implicit control flow. This paper presents static analyses for two types of implicit control flow that frequently appear in Android apps: Java reflection and Android intents. Our analyses help to resolve where control flows and what data is passed. This information improves the precision of downstream analyses, which no longer need to make conservative assumptions about implicit control flow. We have implemented our techniques for Java. We enhanced an existing security analysis with a more precise treatment of reflection and intents. In a case study involving ten real-world Android apps that use both intents and reflection, the precision of the security analysis was increased on average by two orders of magnitude. The precision of two other downstream analyses was also improved.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"17 1","pages":"669-679"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74471914","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}
Recently, Begel et al. found that one of the most important questions software developers ask is "what parts of software are used/loved by users." User reviews provide an effective channel to address this question. However, most existing review summarization tools treat reviews as bags-of-words (i.e., mixed review categories) and are limited to extract software aspects and user preferences. We present a novel review summarization framework, SUR-Miner. Instead of a bags-of-words assumption, it classifies reviews into five categories and extracts aspects for sentences which include aspect evaluation using a pattern-based parser. Then, SUR-Miner visualizes the summaries using two interactive diagrams. Our evaluation on seventeen popular apps shows that SUR-Miner summarizes more accurate and clearer aspects than state-of-the-art techniques, with an F1-score of 0.81, significantly greater than that of ReviewSpotlight (0.56) and Guzmans' method (0.55). Feedback from developers shows that 88% developers agreed with the usefulness of the summaries from SUR-Miner.
{"title":"\"What Parts of Your Apps are Loved by Users?\" (T)","authors":"Xiaodong Gu, Sunghun Kim","doi":"10.1109/ASE.2015.57","DOIUrl":"https://doi.org/10.1109/ASE.2015.57","url":null,"abstract":"Recently, Begel et al. found that one of the most important questions software developers ask is \"what parts of software are used/loved by users.\" User reviews provide an effective channel to address this question. However, most existing review summarization tools treat reviews as bags-of-words (i.e., mixed review categories) and are limited to extract software aspects and user preferences. We present a novel review summarization framework, SUR-Miner. Instead of a bags-of-words assumption, it classifies reviews into five categories and extracts aspects for sentences which include aspect evaluation using a pattern-based parser. Then, SUR-Miner visualizes the summaries using two interactive diagrams. Our evaluation on seventeen popular apps shows that SUR-Miner summarizes more accurate and clearer aspects than state-of-the-art techniques, with an F1-score of 0.81, significantly greater than that of ReviewSpotlight (0.56) and Guzmans' method (0.55). Feedback from developers shows that 88% developers agreed with the usefulness of the summaries from SUR-Miner.","PeriodicalId":6586,"journal":{"name":"2015 30th IEEE/ACM International Conference on Automated Software Engineering (ASE)","volume":"51 1","pages":"760-770"},"PeriodicalIF":0.0,"publicationDate":"2015-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75995659","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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