Pub Date : 2016-02-23DOI: 10.1109/FMCAD.2016.7886678
Rohit Singh, Armando Solar-Lezama
This paper addresses the problem of creating simplifiers for logic formulas based on conditional term rewriting. In particular, the paper focuses on a program synthesis application where formula simplifications have been shown to have a significant impact. We show that by combining machine learning techniques with constraint-based synthesis, it is possible to synthesize a formula simplifier fully automatically from a corpus of representative problems, making it possible to create formula simplifiers tailored to specific problem domains. We demonstrate the benefits of our approach for synthesis benchmarks from the SyGuS competition and automated grading.
{"title":"SWAPPER: A framework for automatic generation of formula simplifiers based on conditional rewrite rules","authors":"Rohit Singh, Armando Solar-Lezama","doi":"10.1109/FMCAD.2016.7886678","DOIUrl":"https://doi.org/10.1109/FMCAD.2016.7886678","url":null,"abstract":"This paper addresses the problem of creating simplifiers for logic formulas based on conditional term rewriting. In particular, the paper focuses on a program synthesis application where formula simplifications have been shown to have a significant impact. We show that by combining machine learning techniques with constraint-based synthesis, it is possible to synthesize a formula simplifier fully automatically from a corpus of representative problems, making it possible to create formula simplifiers tailored to specific problem domains. We demonstrate the benefits of our approach for synthesis benchmarks from the SyGuS competition and automated grading.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"24 1","pages":"185-192"},"PeriodicalIF":0.0,"publicationDate":"2016-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84112189","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 : 2015-11-04DOI: 10.1109/FMCAD.2016.7886660
E. Goldberg
We introduce a new framework for Equivalence Checking (EC) of Boolean circuits based on a general technique called Logic Relaxation (LoR). LoR is meant for checking if a propositional formula G has only “good” satisfying assignments specified by a design property. The essence of LoR is to relax G into a formula Grlx and compute a set S that contains all assignments that satisfy Grlx but do not satisfy G. If all bad satisfying assignments are in S, formula G can have only good ones and the design property in question holds. Set S is built by a procedure called partial quantifier elimination. The appeal of EC by LoR is twofold. First, it facilitates generation of powerful inductive proofs. Second, proving inequiv-alence comes down to checking the existence of some assignments satisfying Grlx i.e. a simpler version of the original formula. We give experimental evidence that supports our approach.
{"title":"Equivalence checking by logic relaxation","authors":"E. Goldberg","doi":"10.1109/FMCAD.2016.7886660","DOIUrl":"https://doi.org/10.1109/FMCAD.2016.7886660","url":null,"abstract":"We introduce a new framework for Equivalence Checking (EC) of Boolean circuits based on a general technique called Logic Relaxation (LoR). LoR is meant for checking if a propositional formula G has only “good” satisfying assignments specified by a design property. The essence of LoR is to relax G into a formula Grlx and compute a set S that contains all assignments that satisfy Grlx but do not satisfy G. If all bad satisfying assignments are in S, formula G can have only good ones and the design property in question holds. Set S is built by a procedure called partial quantifier elimination. The appeal of EC by LoR is twofold. First, it facilitates generation of powerful inductive proofs. Second, proving inequiv-alence comes down to checking the existence of some assignments satisfying Grlx i.e. a simpler version of the original formula. We give experimental evidence that supports our approach.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"65 1","pages":"49-56"},"PeriodicalIF":0.0,"publicationDate":"2015-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78799830","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 : 2014-10-21DOI: 10.1109/FMCAD.2014.6987587
X. Leroy
Formal verification of software or hardware systems --- be it by model checking, deductive verification, abstract interpretation, type checking, or any other kind of static analysis --- is generally conducted over high-level programming or description languages, quite remote from the actual machine code and circuits that execute in the system. To bridge this particular gap, we all rely on compilers and other code generators to automatically produce the executable artifact. Compilers are, however, vulnerable to miscompilation: bugs in the compiler that cause incorrect code to be generated from a correct source code, possibly invalidating the guarantees so painfully obtained by source-level formal verification. Recent experimental studies [1] show that many widely-used production-quality compilers suffer from miscompilation. The formal verification of compilers and related code generators is a radical, mathematically-grounded answer to the miscompilation issue. By applying formal verification (typically, interactive theorem proving) to the compiler itself, it is possible to guarantee that the compiler preserves the semantics of the source programs it transforms, or at least preserves the properties of interest that were formally verified over the source programs. Proving the correctness of compilers is an old idea [2], [3] that took a long time to scale all the way to realistic compilers. In the talk, I give an overview of CompCert C [4], a moderately-optimizing compiler for almost all of the ISO C 99 language that has been formally verified using the Coq proof assistant [5]. The CompCert project is one point in a space of code generators whose verification deserves attention. For example, functional languages and object-oriented languages raise the issue of jointly verifying the compiler and the run-time system (memory management, exception handling, etc) that the generated code depends on. At the other end of the expressiveness spectrum, synchronous languages and hardware description languages also raise interesting verified generation issues, as exemplified by Pnueli's seminal work on translation validation for Signal [6] and Braibant and Chlipala's recent work on verified hardware synthesis [7]. Orthogonally, the integration of verification tools and compilers that are both verified against a shared formal semantics opens fascinating opportunities for "super-optimizations" that generate better code by exploiting the properties of the source code that were formally verified.
{"title":"Compiler verification for fun and profit","authors":"X. Leroy","doi":"10.1109/FMCAD.2014.6987587","DOIUrl":"https://doi.org/10.1109/FMCAD.2014.6987587","url":null,"abstract":"Formal verification of software or hardware systems --- be it by model checking, deductive verification, abstract interpretation, type checking, or any other kind of static analysis --- is generally conducted over high-level programming or description languages, quite remote from the actual machine code and circuits that execute in the system. To bridge this particular gap, we all rely on compilers and other code generators to automatically produce the executable artifact. Compilers are, however, vulnerable to miscompilation: bugs in the compiler that cause incorrect code to be generated from a correct source code, possibly invalidating the guarantees so painfully obtained by source-level formal verification. Recent experimental studies [1] show that many widely-used production-quality compilers suffer from miscompilation. \u0000 \u0000The formal verification of compilers and related code generators is a radical, mathematically-grounded answer to the miscompilation issue. By applying formal verification (typically, interactive theorem proving) to the compiler itself, it is possible to guarantee that the compiler preserves the semantics of the source programs it transforms, or at least preserves the properties of interest that were formally verified over the source programs. Proving the correctness of compilers is an old idea [2], [3] that took a long time to scale all the way to realistic compilers. In the talk, I give an overview of CompCert C [4], a moderately-optimizing compiler for almost all of the ISO C 99 language that has been formally verified using the Coq proof assistant [5]. \u0000 \u0000The CompCert project is one point in a space of code generators whose verification deserves attention. For example, functional languages and object-oriented languages raise the issue of jointly verifying the compiler and the run-time system (memory management, exception handling, etc) that the generated code depends on. At the other end of the expressiveness spectrum, synchronous languages and hardware description languages also raise interesting verified generation issues, as exemplified by Pnueli's seminal work on translation validation for Signal [6] and Braibant and Chlipala's recent work on verified hardware synthesis [7]. \u0000 \u0000Orthogonally, the integration of verification tools and compilers that are both verified against a shared formal semantics opens fascinating opportunities for \"super-optimizations\" that generate better code by exploiting the properties of the source code that were formally verified.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"10 1","pages":"9"},"PeriodicalIF":0.0,"publicationDate":"2014-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79554710","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 : 2014-10-21DOI: 10.1109/FMCAD.2014.6987588
T. Henzinger
We summarize some recent results on using computed-aided verification technology for understanding biological systems. This includes the use of reactive models for specifying cellular mechanisms, the use of symbolic state space exploration for analyzing molecular reaction networks, and the use of SMT solvers for studying the evolution of gene regulatory circuits.
{"title":"Computer-aided verification technology for biology","authors":"T. Henzinger","doi":"10.1109/FMCAD.2014.6987588","DOIUrl":"https://doi.org/10.1109/FMCAD.2014.6987588","url":null,"abstract":"We summarize some recent results on using computed-aided verification technology for understanding biological systems. This includes the use of reactive models for specifying cellular mechanisms, the use of symbolic state space exploration for analyzing molecular reaction networks, and the use of SMT solvers for studying the evolution of gene regulatory circuits.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"59 2 1","pages":"11"},"PeriodicalIF":0.0,"publicationDate":"2014-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79836646","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}
This paper addresses the problem of placing memory fences in a concurrent program running on a relaxed memory model. Modern architectures implement relaxed memory models which may reorder memory operations or execute them non-atomically. Special instructions called memory fences are provided to the programmer, allowing control of this behavior. To ensure correctness of many algorithms, in particular of non-blocking ones, a programmer is often required to explicitly insert memory fences into her program. However, she must use as few fences as possible, or the benefits of the relaxed architecture may be lost. Placing memory fences is challenging and very error prone, as it requires subtle reasoning about the underlying memory model. We present a framework for automatic inference of memory fences in concurrent programs, assisting the programmer in this complex task. Given a finite-state program, a safety specification and a description of the memory model, our framework computes a set of ordering constraints that guarantee the correctness of the program under the memory model. The computed constraints are maximally permissive: removing any constraint from the solution would permit an execution violating the specification. Our framework then realizes the computed constraints as additional fences in the input program. We implemented our approach in a tool called FENDER and used it to infer correct and efficient placements of fences for several non-trivial algorithms, including practical concurrent data structures.
{"title":"Automatic inference of memory fences","authors":"M. Kuperstein, Martin T. Vechev, Eran Yahav","doi":"10.1145/2261417.2261438","DOIUrl":"https://doi.org/10.1145/2261417.2261438","url":null,"abstract":"This paper addresses the problem of placing memory fences in a concurrent program running on a relaxed memory model. Modern architectures implement relaxed memory models which may reorder memory operations or execute them non-atomically. Special instructions called memory fences are provided to the programmer, allowing control of this behavior. To ensure correctness of many algorithms, in particular of non-blocking ones, a programmer is often required to explicitly insert memory fences into her program. However, she must use as few fences as possible, or the benefits of the relaxed architecture may be lost. Placing memory fences is challenging and very error prone, as it requires subtle reasoning about the underlying memory model. We present a framework for automatic inference of memory fences in concurrent programs, assisting the programmer in this complex task. Given a finite-state program, a safety specification and a description of the memory model, our framework computes a set of ordering constraints that guarantee the correctness of the program under the memory model. The computed constraints are maximally permissive: removing any constraint from the solution would permit an execution violating the specification. Our framework then realizes the computed constraints as additional fences in the input program. We implemented our approach in a tool called FENDER and used it to infer correct and efficient placements of fences for several non-trivial algorithms, including practical concurrent data structures.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"76 1","pages":"111-119"},"PeriodicalIF":0.0,"publicationDate":"2010-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75284758","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}
Eyad Alkassar, Ernie Cohen, Mark A. Hillebrand, Mikhail Kovalev, W. Paul
Efficient virtualization of translation lookaside buffers (TLBs), a core component of modern hypervisors, is complicated by the concurrent, speculative walking of page tables in hardware. We give a formal model of an x64-like TLB, criteria for its correct virtualization, and outline the verification of a virtualization algorithm using shadow page tables. The verification is being carried out in VCC, a verifier for concurrent C code.
{"title":"Verifying shadow page table algorithms","authors":"Eyad Alkassar, Ernie Cohen, Mark A. Hillebrand, Mikhail Kovalev, W. Paul","doi":"10.5555/1998496.1998543","DOIUrl":"https://doi.org/10.5555/1998496.1998543","url":null,"abstract":"Efficient virtualization of translation lookaside buffers (TLBs), a core component of modern hypervisors, is complicated by the concurrent, speculative walking of page tables in hardware. We give a formal model of an x64-like TLB, criteria for its correct virtualization, and outline the verification of a virtualization algorithm using shadow page tables. The verification is being carried out in VCC, a verifier for concurrent C code.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"1 1","pages":"267-270"},"PeriodicalIF":0.0,"publicationDate":"2010-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82959043","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}
Arbiters are commonly used components in electronic systems to control access to shared resources. In this paper, we describe a novel method to check starvation in random priority-based arbiters. Typical implementations of random priority-based arbiters use pseudo-random number generators such as linear feedback shift registers (LFSRs) which makes them sequentially deep precluding a direct analysis of the design. The proposed technique checks a stronger bounded-starvation property; if the stronger property fails, we use the counterexample to construct an underapproximation abstraction. We next check the original property on the abstraction to check for its validity. We have found the approach to be a very effective bug hunting technique to reveal starvation issues in LFSR-based arbiters. We describe its successful application on formal verification of arbiters on a commercial processor design.
{"title":"Formal verification of arbiters using property strengthening and underapproximations","authors":"Gadiel Auerbach, Fady Copty, Viresh Paruthi","doi":"10.5555/1998496.1998504","DOIUrl":"https://doi.org/10.5555/1998496.1998504","url":null,"abstract":"Arbiters are commonly used components in electronic systems to control access to shared resources. In this paper, we describe a novel method to check starvation in random priority-based arbiters. Typical implementations of random priority-based arbiters use pseudo-random number generators such as linear feedback shift registers (LFSRs) which makes them sequentially deep precluding a direct analysis of the design. The proposed technique checks a stronger bounded-starvation property; if the stronger property fails, we use the counterexample to construct an underapproximation abstraction. We next check the original property on the abstraction to check for its validity. We have found the approach to be a very effective bug hunting technique to reveal starvation issues in LFSR-based arbiters. We describe its successful application on formal verification of arbiters on a commercial processor design.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"59 1","pages":"21-24"},"PeriodicalIF":0.0,"publicationDate":"2010-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89188743","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}
S. Bensalem, M. Bozga, Axel Legay, Thanh-Hung Nguyen, J. Sifakis, Rongjie Yan
We propose invariant-based techniques for the efficient verification of safety and deadlock properties of concurrent systems. We assume that components and component interactions are described within the BIP framework, a tool for component-based design. We build on a compositional methodology in which the invariant is obtained by combining the invariants of the individual components with an interaction invariant that takes concurrency and interaction between components into account. In this paper, we propose new efficient techniques for computing interaction invariants. This is achieved in several steps. First, we propose a formalization of incremental component-based design. Then we suggest sufficient conditions that ensure the preservation of invariants through the introduction of new interactions. For cases in which these conditions are not satisfied, we propose methods for generation of new invariants in an incremental manner. The reuse of existing invariants reduces considerably the verification effort. Our techniques have been implemented in the D-Finder toolset. Among the experiments conducted, we have been capable of verifying properties and deadlock-freedom of DALA, an autonomous robot whose behaviors in the functional level are described with 500000 lines of C Code. This experiment, which is conducted with industrial partners, is far beyond the scope of existing academic tools such as NuSMV or SPIN.
{"title":"Incremental component-based construction and verification using invariants","authors":"S. Bensalem, M. Bozga, Axel Legay, Thanh-Hung Nguyen, J. Sifakis, Rongjie Yan","doi":"10.5555/1998496.1998542","DOIUrl":"https://doi.org/10.5555/1998496.1998542","url":null,"abstract":"We propose invariant-based techniques for the efficient verification of safety and deadlock properties of concurrent systems. We assume that components and component interactions are described within the BIP framework, a tool for component-based design. We build on a compositional methodology in which the invariant is obtained by combining the invariants of the individual components with an interaction invariant that takes concurrency and interaction between components into account. In this paper, we propose new efficient techniques for computing interaction invariants. This is achieved in several steps. First, we propose a formalization of incremental component-based design. Then we suggest sufficient conditions that ensure the preservation of invariants through the introduction of new interactions. For cases in which these conditions are not satisfied, we propose methods for generation of new invariants in an incremental manner. The reuse of existing invariants reduces considerably the verification effort. Our techniques have been implemented in the D-Finder toolset. Among the experiments conducted, we have been capable of verifying properties and deadlock-freedom of DALA, an autonomous robot whose behaviors in the functional level are described with 500000 lines of C Code. This experiment, which is conducted with industrial partners, is far beyond the scope of existing academic tools such as NuSMV or SPIN.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"20 1","pages":"257-256"},"PeriodicalIF":0.0,"publicationDate":"2010-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82556919","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}
M. Gyssens, J. Paredaens, D. V. Gucht, G. Fletcher
Program Synthesis, which is the task of discovering programs that realize user intent, can be useful in several scenarios: discovery of new algorithms, helping regular programmers automatically discover tricky/mundane programming details, enabling people with no programming background to develop scripts for performing repetitive tasks (end-user programming), and even problem solving in the context of automating teaching. In this tutorial, I will describe the three key dimensions that should be taken into account in designing any program synthesis system: expression of user intent, space of programs over which to search, and the search technique [1]. (i) The user intent can be expressed in the form of logical relations between inputs and outputs, input-output examples, demonstrations, natural language, and inefficient or related programs. (ii) The search space can be over imperative or functional programs (with possible restrictions on the control structure or the operator set), or over restricted models of computations such as regular/context-free grammars/transducers, or succinct logical representations. (iii) The search technique can be based on exhaustive search, version space algebras, machine learning techniques (such as belief propagation or genetic programming), or logical reasoning techniques based on SAT/SMT solvers. I will illustrate these concepts by brief description of various program synthesis projects that target synthesis of a wide variety of programs such as standard undergraduate textbook algorithms (e.g., sorting, dynamic programming), program inverses (e.g., decoders, deserializers), bitvector manipulation routines, deobfuscated programs, graph algorithms, text-manipulating routines, geometry algorithms etc.
{"title":"Dimensions in program synthesis","authors":"M. Gyssens, J. Paredaens, D. V. Gucht, G. Fletcher","doi":"10.1145/1836089.1836091","DOIUrl":"https://doi.org/10.1145/1836089.1836091","url":null,"abstract":"Program Synthesis, which is the task of discovering programs that realize user intent, can be useful in several scenarios: discovery of new algorithms, helping regular programmers automatically discover tricky/mundane programming details, enabling people with no programming background to develop scripts for performing repetitive tasks (end-user programming), and even problem solving in the context of automating teaching. In this tutorial, I will describe the three key dimensions that should be taken into account in designing any program synthesis system: expression of user intent, space of programs over which to search, and the search technique [1]. (i) The user intent can be expressed in the form of logical relations between inputs and outputs, input-output examples, demonstrations, natural language, and inefficient or related programs. (ii) The search space can be over imperative or functional programs (with possible restrictions on the control structure or the operator set), or over restricted models of computations such as regular/context-free grammars/transducers, or succinct logical representations. (iii) The search technique can be based on exhaustive search, version space algebras, machine learning techniques (such as belief propagation or genetic programming), or logical reasoning techniques based on SAT/SMT solvers. I will illustrate these concepts by brief description of various program synthesis projects that target synthesis of a wide variety of programs such as standard undergraduate textbook algorithms (e.g., sorting, dynamic programming), program inverses (e.g., decoders, deserializers), bitvector manipulation routines, deobfuscated programs, graph algorithms, text-manipulating routines, geometry algorithms etc.","PeriodicalId":6479,"journal":{"name":"2016 Formal Methods in Computer-Aided Design (FMCAD)","volume":"25 1","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2010-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81712855","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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