Raúl A. Santelices, Yiji Zhang, Haipeng Cai, Siyuan Jiang
We describe DUA-Forensics, our open-source Java-bytecode program analysis and instrumentation system built on top of Soot. DUA-Forensics has been in development for more than six years and has supported multiple research projects on efficient monitoring, test-suite augmentation, fault localization, symbolic execution, and change-impact analysis. Three core features of Soot have proven essential: the Java bytecode processor, the Jimple intermediate representation, and the API to access and manipulate Jimple programs. On top of these foundations, DUA-Forensics offers a number of features of potential interest to the Java-analysis community, including (1) a layer that facilitates the instrumentation of Jimple code, (2) a library modeling system for efficient points-to, data-flow, and symbolic analysis, and (3) a fine-grained dependence analysis component. These features have made our own research more productive, reliable, and effective.
{"title":"DUA-forensics: a fine-grained dependence analysis and instrumentation framework based on Soot","authors":"Raúl A. Santelices, Yiji Zhang, Haipeng Cai, Siyuan Jiang","doi":"10.1145/2487568.2487574","DOIUrl":"https://doi.org/10.1145/2487568.2487574","url":null,"abstract":"We describe DUA-Forensics, our open-source Java-bytecode program analysis and instrumentation system built on top of Soot. DUA-Forensics has been in development for more than six years and has supported multiple research projects on efficient monitoring, test-suite augmentation, fault localization, symbolic execution, and change-impact analysis. Three core features of Soot have proven essential: the Java bytecode processor, the Jimple intermediate representation, and the API to access and manipulate Jimple programs. On top of these foundations, DUA-Forensics offers a number of features of potential interest to the Java-analysis community, including (1) a layer that facilitates the instrumentation of Jimple code, (2) a library modeling system for efficient points-to, data-flow, and symbolic analysis, and (3) a fine-grained dependence analysis component. These features have made our own research more productive, reliable, and effective.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125884412","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}
Philip C. Pratt-Szeliga, Marc-André Laverdière, E. Merlo, James W. Fawcett, Roy D. Welch
One of the first activities of the Soot program analysis framework is to load the classes for analysis. With the current class loader, more classes are loaded than necessary. The overhead in memory of these classes can make whole-program analysis of large binaries infeasible on systems with limited memory. This paper describes new algorithms and data structures to efficiently load Java Bytecode classes for whole program analysis in Soot. Our method uses a modified version of Rapid Type Analysis (RTA) to determine what classes, methods and fields would be reachable during program execution. This enables us to load significantly less information in memory to enable program analyses. We implemented our approach for loading Java bytecode in the Soot-based Rootbeer compiler. The new class loader loaded a Scene that had 58% to 64% less classes, representing memory savings of 44% to 82%.
{"title":"Soot class loading in the rootbeer GPU compiler","authors":"Philip C. Pratt-Szeliga, Marc-André Laverdière, E. Merlo, James W. Fawcett, Roy D. Welch","doi":"10.1145/2487568.2487573","DOIUrl":"https://doi.org/10.1145/2487568.2487573","url":null,"abstract":"One of the first activities of the Soot program analysis framework is to load the classes for analysis. With the current class loader, more classes are loaded than necessary. The overhead in memory of these classes can make whole-program analysis of large binaries infeasible on systems with limited memory. This paper describes new algorithms and data structures to efficiently load Java Bytecode classes for whole program analysis in Soot. Our method uses a modified version of Rapid Type Analysis (RTA) to determine what classes, methods and fields would be reachable during program execution. This enables us to load significantly less information in memory to enable program analyses. We implemented our approach for loading Java bytecode in the Soot-based Rootbeer compiler. The new class loader loaded a Scene that had 58% to 64% less classes, representing memory savings of 44% to 82%.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130471472","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}
An interprocedural analysis is precise if it is flow sensitive and fully context-sensitive even in the presence of recursion. Many methods of interprocedural analysis sacrifice precision for scalability while some are precise but limited to only a certain class of problems. Soot currently supports interprocedural analysis of Java programs using graph reachability. However, this approach is restricted to IFDS/IDE problems, and is not suitable for general data flow frameworks such as heap reference analysis and points-to analysis which have non-distributive flow functions. We describe a general-purpose interprocedural analysis framework for Soot using data flow values for context-sensitivity. This framework is not restricted to problems with distributive flow functions, although the lattice must be finite. It combines the key ideas of the tabulation method of the functional approach and the technique of value-based termination of call string construction. The efficiency and precision of interprocedural analyses is heavily affected by the precision of the underlying call graph. This is especially important for object-oriented languages like Java where virtual method invocations cause an explosion of spurious call edges if the call graph is constructed naively. We have instantiated our framework with a flow and context-sensitive points-to analysis in Soot, which enables the construction of call graphs that are far more precise than those constructed by Soot's spark engine.
{"title":"Interprocedural data flow analysis in Soot using value contexts","authors":"Rohan Padhye, Uday P. Khedker","doi":"10.1145/2487568.2487569","DOIUrl":"https://doi.org/10.1145/2487568.2487569","url":null,"abstract":"An interprocedural analysis is precise if it is flow sensitive and fully context-sensitive even in the presence of recursion. Many methods of interprocedural analysis sacrifice precision for scalability while some are precise but limited to only a certain class of problems.\u0000 Soot currently supports interprocedural analysis of Java programs using graph reachability. However, this approach is restricted to IFDS/IDE problems, and is not suitable for general data flow frameworks such as heap reference analysis and points-to analysis which have non-distributive flow functions.\u0000 We describe a general-purpose interprocedural analysis framework for Soot using data flow values for context-sensitivity. This framework is not restricted to problems with distributive flow functions, although the lattice must be finite. It combines the key ideas of the tabulation method of the functional approach and the technique of value-based termination of call string construction.\u0000 The efficiency and precision of interprocedural analyses is heavily affected by the precision of the underlying call graph. This is especially important for object-oriented languages like Java where virtual method invocations cause an explosion of spurious call edges if the call graph is constructed naively. We have instantiated our framework with a flow and context-sensitive points-to analysis in Soot, which enables the construction of call graphs that are far more precise than those constructed by Soot's spark engine.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2013-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123272569","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}
Java Specification Request (JSR) 292, which was realized with Java 7, defines a new java bytecode called invokedynamic, which can be used to call methods by name, without determining statically where the implementation of the called method is to be found. This mechanism eases the implementation of highly dynamic languages for the Java Virtual Machine. In this work we explain how we extended the Soot framework for static analysis and transformation of Java programs to properly handle invokedynamic bytecodes. Our implementation required changes on all levels of Soot, as all intermediate representations needed to be adapted appropriately. We comment on the design decisions taken and how users can use our implementation to statically process or generate invokedynamic instructions. Our support has been integrated into Soot release 2.5.0 and is thus already available for everyone to use.
{"title":"InvokeDynamic support in Soot","authors":"E. Bodden","doi":"10.1145/2259051.2259059","DOIUrl":"https://doi.org/10.1145/2259051.2259059","url":null,"abstract":"Java Specification Request (JSR) 292, which was realized with Java 7, defines a new java bytecode called invokedynamic, which can be used to call methods by name, without determining statically where the implementation of the called method is to be found. This mechanism eases the implementation of highly dynamic languages for the Java Virtual Machine.\u0000 In this work we explain how we extended the Soot framework for static analysis and transformation of Java programs to properly handle invokedynamic bytecodes. Our implementation required changes on all levels of Soot, as all intermediate representations needed to be adapted appropriately. We comment on the design decisions taken and how users can use our implementation to statically process or generate invokedynamic instructions.\u0000 Our support has been integrated into Soot release 2.5.0 and is thus already available for everyone to use.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114736737","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}
Side-effect analysis is a fundamental static analysis used to determine the memory locations modified or used by each program entity. For the programs with pointers, the analysis can be very imprecise. To improve the precision of side-effect analysis, many approaches design more elaborate background pointer analyses in order to obtain smaller side-effect sets, but very few approaches consider to achieve better precisions by refining the side-effect analysis algorithms themselves. To address the problem, this paper presents a new side-effect analysis approach that uses Gay and Steensgaard's fast escape analysis to filter superfluous side-effects. The approach does not need to modify the background pointer analysis and can filter side-effects in the intraprocedural level and the interprocedural level. The experimental results show that it can effectively improve the analysis precision within a short extra time.
{"title":"Side-effect analysis with fast escape filter","authors":"Binxian Tao, Ju Qian, Xiaoyu Zhou","doi":"10.1145/2259051.2259054","DOIUrl":"https://doi.org/10.1145/2259051.2259054","url":null,"abstract":"Side-effect analysis is a fundamental static analysis used to determine the memory locations modified or used by each program entity. For the programs with pointers, the analysis can be very imprecise. To improve the precision of side-effect analysis, many approaches design more elaborate background pointer analyses in order to obtain smaller side-effect sets, but very few approaches consider to achieve better precisions by refining the side-effect analysis algorithms themselves. To address the problem, this paper presents a new side-effect analysis approach that uses Gay and Steensgaard's fast escape analysis to filter superfluous side-effects. The approach does not need to modify the background pointer analysis and can filter side-effects in the intraprocedural level and the interprocedural level. The experimental results show that it can effectively improve the analysis precision within a short extra time.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129183214","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}
Karthik Ramachandra, Ravindra Guravannavar, S. Sudarshan
We describe DBridge, a novel program analysis and transformation tool to optimize database and web service access. Traditionally, rewrite of queries and programs are done independently, by the database query optimizer and the language compiler respectively, leaving out many optimization opportunities. Our tool aims to bridge this gap by performing holistic transformations, which include both program and query rewrite. There has been earlier research in this area involving program analysis and transformation for automatically rewriting database applications to perform optimizations; for example, our earlier work has addressed batching or asynchronous submission of iterative queries, and prefetching query results. DBridge implements these techniques for Java programs and internally uses Soot, a Java optimization framework, for static analysis and transformation. DBridge can perform such optimizations on Java programs that use the JDBC API to access the database. It is currently being extended to handle the Hibernate API, and Web Services. In this paper, we describe the program transformations that DBridge can perform. We then discuss the design and implementation of DBridge with a focus on how the Soot framework has been used to achieve these goals. Finally, we conclude by discussing some of the future directions for our tool.
{"title":"Program analysis and transformation for holistic optimization of database applications","authors":"Karthik Ramachandra, Ravindra Guravannavar, S. Sudarshan","doi":"10.1145/2259051.2259057","DOIUrl":"https://doi.org/10.1145/2259051.2259057","url":null,"abstract":"We describe DBridge, a novel program analysis and transformation tool to optimize database and web service access. Traditionally, rewrite of queries and programs are done independently, by the database query optimizer and the language compiler respectively, leaving out many optimization opportunities. Our tool aims to bridge this gap by performing holistic transformations, which include both program and query rewrite.\u0000 There has been earlier research in this area involving program analysis and transformation for automatically rewriting database applications to perform optimizations; for example, our earlier work has addressed batching or asynchronous submission of iterative queries, and prefetching query results. DBridge implements these techniques for Java programs and internally uses Soot, a Java optimization framework, for static analysis and transformation. DBridge can perform such optimizations on Java programs that use the JDBC API to access the database. It is currently being extended to handle the Hibernate API, and Web Services.\u0000 In this paper, we describe the program transformations that DBridge can perform. We then discuss the design and implementation of DBridge with a focus on how the Soot framework has been used to achieve these goals. Finally, we conclude by discussing some of the future directions for our tool.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132334395","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}
We present a static analysis which identifies disjointness relations between collections in Java. We have implemented our analysis as a primarily intraprocedural dataflow analysis framework using Soot. We handle method calls using developer-provided annotations, with some inference support. We include experimental results of the from our disjointness analysis on a pair of benchmarks.
{"title":"Collection disjointness analysis","authors":"Hang Chu, Patrick Lam","doi":"10.1145/2259051.2259058","DOIUrl":"https://doi.org/10.1145/2259051.2259058","url":null,"abstract":"We present a static analysis which identifies disjointness relations between collections in Java. We have implemented our analysis as a primarily intraprocedural dataflow analysis framework using Soot. We handle method calls using developer-provided annotations, with some inference support. We include experimental results of the from our disjointness analysis on a pair of benchmarks.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123776447","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}
As a classical data-flow analysis, reaching definitions analysis is the corner stone of various techniques, such as code optimization and program slicing. The built-in data-flow analysis framework in Soot has been implemented in the traditional iterative style. While being able to meet general requirements for implementation of data flow analyses, the framework may be less efficient for a certain type of analyses in which the complete data-flow solution is unnecessary. In this paper, we introduce our Soot-based implementation of an inter-procedural demand-driven reaching definitions analysis. For a demand for reaching definitions facts, the analysis only explores relevant program points and variables, saving a considerable amount of computation. Preliminary results show that the implementation can be much more efficient than its traditional counterpart in several scenarios. The Soot framework has greatly facilitated the implementation by providing abundant basic analysis results via well designed APIs.
{"title":"Soot-based implementation of a demand-driven reaching definitions analysis","authors":"Longwen Lu, Cheng Zhang, Jianjun Zhao","doi":"10.1145/2259051.2259055","DOIUrl":"https://doi.org/10.1145/2259051.2259055","url":null,"abstract":"As a classical data-flow analysis, reaching definitions analysis is the corner stone of various techniques, such as code optimization and program slicing. The built-in data-flow analysis framework in Soot has been implemented in the traditional iterative style. While being able to meet general requirements for implementation of data flow analyses, the framework may be less efficient for a certain type of analyses in which the complete data-flow solution is unnecessary.\u0000 In this paper, we introduce our Soot-based implementation of an inter-procedural demand-driven reaching definitions analysis. For a demand for reaching definitions facts, the analysis only explores relevant program points and variables, saving a considerable amount of computation. Preliminary results show that the implementation can be much more efficient than its traditional counterpart in several scenarios. The Soot framework has greatly facilitated the implementation by providing abundant basic analysis results via well designed APIs.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125609562","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}
The IFDS and IDE frameworks by Reps, Horwitz and Sagiv are two general frameworks for the inter-procedural analysis of data-flow problems with distributive flow functions over finite domains. Many data-flow problems do have distributive flow functions and are thus expressible as IFDS or IDE problems, reaching from basic analyses like truly-live variables to complex analyses for problems from the current literature such as typestate and secure information-flow. In this work we describe our implementation of a generic IFDS/IDE solver on top of Soot and contrast it with an IFDS implementation in the Watson Libraries for Analysis (WALA), both from a user's perspective and in terms of the implementation. While WALA's implementation is geared much towards memory efficiency, ours is currently geared more towards extensibility and ease of use and we focus on efficiency as a secondary goal. We further discuss possible extensions to our IFDS/IDE implementation that may be useful to support a wider range of analyses.
{"title":"Inter-procedural data-flow analysis with IFDS/IDE and Soot","authors":"E. Bodden","doi":"10.1145/2259051.2259052","DOIUrl":"https://doi.org/10.1145/2259051.2259052","url":null,"abstract":"The IFDS and IDE frameworks by Reps, Horwitz and Sagiv are two general frameworks for the inter-procedural analysis of data-flow problems with distributive flow functions over finite domains. Many data-flow problems do have distributive flow functions and are thus expressible as IFDS or IDE problems, reaching from basic analyses like truly-live variables to complex analyses for problems from the current literature such as typestate and secure information-flow.\u0000 In this work we describe our implementation of a generic IFDS/IDE solver on top of Soot and contrast it with an IFDS implementation in the Watson Libraries for Analysis (WALA), both from a user's perspective and in terms of the implementation. While WALA's implementation is geared much towards memory efficiency, ours is currently geared more towards extensibility and ease of use and we focus on efficiency as a secondary goal.\u0000 We further discuss possible extensions to our IFDS/IDE implementation that may be useful to support a wider range of analyses.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116642312","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}
Whole-program static analysis has been extensively studied and widely used in the past few decades. For modern object-oriented programs, scalability has become an important issue for using whole-program analysis in real-world tools. In addition, the ever-increasing size of libraries (e.g., the JDK library) and frameworks exacerbates the scalability problems. To achieve the desired level of analysis performance, an effective approach could be to generate and apply analysis summary information for library methods. In this paper, such an approach is referred to as a summary-based whole-program analysis. The challenges for this technique are twofold: (1) carefully designed abstractions and algorithms are needed to create and use client-independent and analysis-specific library summary information; and (2) support for summary generation and application should be effectively incorporated into existing analysis infrastructures. This paper focuses on the second challenge. It uses Soot, a widely-used program analysis framework for Java, as a vehicle to explore some of the important issues in providing analysis infrastructures with capabilities for summary-based analysis. Experimental studies are presented to show that significant savings can potentially be achieved by making a whole-program alias analysis summary-based. To actually achieve these savings, the paper proposes to extend Soot to add support for summary-based analysis. Finally, a brief discussion of the required framework extensions is presented.
{"title":"Rethinking Soot for summary-based whole-program analysis","authors":"Dacong Yan, G. Xu, A. Rountev","doi":"10.1145/2259051.2259053","DOIUrl":"https://doi.org/10.1145/2259051.2259053","url":null,"abstract":"Whole-program static analysis has been extensively studied and widely used in the past few decades. For modern object-oriented programs, scalability has become an important issue for using whole-program analysis in real-world tools. In addition, the ever-increasing size of libraries (e.g., the JDK library) and frameworks exacerbates the scalability problems. To achieve the desired level of analysis performance, an effective approach could be to generate and apply analysis summary information for library methods. In this paper, such an approach is referred to as a summary-based whole-program analysis. The challenges for this technique are twofold: (1) carefully designed abstractions and algorithms are needed to create and use client-independent and analysis-specific library summary information; and (2) support for summary generation and application should be effectively incorporated into existing analysis infrastructures.\u0000 This paper focuses on the second challenge. It uses Soot, a widely-used program analysis framework for Java, as a vehicle to explore some of the important issues in providing analysis infrastructures with capabilities for summary-based analysis. Experimental studies are presented to show that significant savings can potentially be achieved by making a whole-program alias analysis summary-based. To actually achieve these savings, the paper proposes to extend Soot to add support for summary-based analysis. Finally, a brief discussion of the required framework extensions is presented.","PeriodicalId":198433,"journal":{"name":"State Of the Art in Java Program Analysis","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116234443","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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