2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)最新文献_第8页

“This Is Damn Slick!” Estimating the Impact of Tweets on Open Source Project Popularity and New Contributors “这真是他妈的滑溜!”估计推文对开源项目受欢迎程度和新贡献者的影响

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510121

Hongbo Fang, Hemank Lamba, J. Herbsleb, Bogdan Vasilescu

{"title":"“This Is Damn Slick!” Estimating the Impact of Tweets on Open Source Project Popularity and New Contributors","authors":"Hongbo Fang, Hemank Lamba, J. Herbsleb, Bogdan Vasilescu","doi":"10.1145/3510003.3510121","DOIUrl":"https://doi.org/10.1145/3510003.3510121","url":null,"abstract":"Twitter is widely used by software developers. But how effective are tweets at promoting open source projects? How could one use Twitter to increase a project's popularity or attract new contributors? In this paper we report on a mixed-methods empirical study of 44,544 tweets containing links to 2,370 open-source GitHub repositories, looking for evidence of causal effects of these tweets on the projects attracting new GitHub stars and contributors, as well as characterizing the high-impact tweets, the people likely being attracted by them, and how they differ from contributors attracted otherwise. Among others, we find that tweets have a statistically significant and practically sizable effect on obtaining new stars and a small average effect on attracting new contributors. The popularity, content of the tweet, as well as the identity of tweet authors all affect the scale of the attraction effect. In addition, our qualitative analysis suggests that forming an active Twitter community for an open source project plays an important role in attracting new committers via tweets. We also report that developers who are new to GitHub or have a long history of Twitter usage but few tweets posted are most likely to be attracted as contributors to the repositories mentioned by tweets. Our work contributes to the literature on open source sustainability.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123268604","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}

引用次数: 6

Retrieving Data Constraint Implementations Using Fine-Grained Code Patterns 使用细粒度代码模式检索数据约束实现

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510167

Juan Manuel Florez, Jonathan Perry, Shiyi Wei, Andrian Marcus

{"title":"Retrieving Data Constraint Implementations Using Fine-Grained Code Patterns","authors":"Juan Manuel Florez, Jonathan Perry, Shiyi Wei, Andrian Marcus","doi":"10.1145/3510003.3510167","DOIUrl":"https://doi.org/10.1145/3510003.3510167","url":null,"abstract":"Business rules are an important part of the requirements of software systems that are meant to support an organization. These rules describe the operations, definitions, and constraints that apply to the organization. Within the software system, business rules are often translated into constraints on the values that are required or allowed for data, called data constraints. Business rules are subject to frequent changes, which in turn require changes to the corre-sponding data constraints in the software. The ability to efficiently and precisely identify where data constraints are implemented in the source code is essential for performing such necessary changes. In this paper, we introduce Lasso, the first technique that automatically retrieves the method and line of code where a given data constraint is enforced. Lasso is based on traceability link recovery approaches and leverages results from recent research that identified line-of-code level implementation patterns for data constraints. We implement three versions of Lasso that can retrieve data constraint implementations when they are implemented with any one of 13 frequently occurring patterns. We evaluate the three versions on a set of 299 data constraints from 15 real-world Java systems, and find that they improve method-level link recovery by 30%,70%, and 163%, in terms of true positives within the first 10 results, compared to their text-retrieval-based baseline. More importantly, the Lasso variants correctly identify the line of code implementing the constraint inside the methods for 68% of the 299 constraints.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115792412","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}

引用次数: 3

Improving Machine Translation Systems via Isotopic Replacement 通过同位素替换改进机器翻译系统

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510206

Zeyu Sun, J Zhang, Yingfei Xiong, M. Harman, Mike Papadakis, Lu Zhang

{"title":"Improving Machine Translation Systems via Isotopic Replacement","authors":"Zeyu Sun, J Zhang, Yingfei Xiong, M. Harman, Mike Papadakis, Lu Zhang","doi":"10.1145/3510003.3510206","DOIUrl":"https://doi.org/10.1145/3510003.3510206","url":null,"abstract":"Machine translation plays an essential role in people's daily international communication. However, machine translation systems are far from perfect. To tackle this problem, researchers have proposed several approaches to testing machine translation. A promising trend among these approaches is to use word replacement, where only one word in the original sentence is replaced with another word to form a sentence pair. However, precise control of the impact of word replacement remains an outstanding issue in these approaches. To address this issue, we propose CAT, a novel word-replacement-based approach, whose basic idea is to identify word replacement with controlled impact (referred to as isotopic replacement). To achieve this purpose, we use a neural-based language model to encode the sentence context, and design a neural-network-based algorithm to evaluate context-aware semantic similarity between two words. Furthermore, similar to TransRepair, a state-of-the-art word-replacement-based approach, CAT also provides automatic fixing of revealed bugs without model retraining. Our evaluation on Google Translate and Transformer indicates that CAT achieves significant improvements over TransRepair. In particular, 1) CAT detects seven more types of bugs than TransRe-pair; 2) CAT detects 129% more translation bugs than TransRepair; 3) CAT repairs twice more bugs than TransRepair, many of which may bring serious consequences if left unfixed; and 4) CAT has better efficiency than TransRepair in input generation (0.01s v.s. 0.41s) and comparable efficiency with TransRepair in bug repair (1.92s v.s. 1.34s).","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129773223","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}

引用次数: 27

Automated Testing of Software that Uses Machine Learning APIs 使用机器学习api的软件自动化测试

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510068

Chengcheng Wan, Shicheng Liu, Sophie Xie, Yifan Liu, H. Hoffmann, M. Maire, Shan Lu

{"title":"Automated Testing of Software that Uses Machine Learning APIs","authors":"Chengcheng Wan, Shicheng Liu, Sophie Xie, Yifan Liu, H. Hoffmann, M. Maire, Shan Lu","doi":"10.1145/3510003.3510068","DOIUrl":"https://doi.org/10.1145/3510003.3510068","url":null,"abstract":"An increasing number of software applications incorporate machine learning (ML) solutions for cognitive tasks that statistically mimic human behaviors. To test such software, tremendous human effort is needed to design image/text/audio inputs that are relevant to the software, and to judge whether the software is processing these inputs as most human beings do. Even when misbehavior is exposed, it is often unclear whether the culprit is inside the cognitive ML API or the code using the API. This paper presents Keeper, a new testing tool for software that uses cognitive ML APIs. Keeper designs a pseudo-inverse function for each ML API that reverses the corresponding cognitive task in an empirical way (e.g., an image search engine pseudo-reverses the image-classification API), and incorporates these pseudo-inverse functions into a symbolic execution engine to automatically gener-ate relevant image/text/audio inputs and judge output correctness. Once misbehavior is exposed, Keeper attempts to change how ML APIs are used in software to alleviate the misbehavior. Our evalu-ation on a variety of open-source applications shows that Keeper greatly improves the branch coverage, while identifying many pre-viously unknown bugs.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125878275","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}

引用次数: 13

SnR: Constraint-Based Type Inference for Incomplete Java Code Snippets SnR:不完整Java代码片段的基于约束的类型推断

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510061

Yiwen Dong, Tianxiao Gu, Yongqiang Tian, Chengnian Sun

{"title":"SnR: Constraint-Based Type Inference for Incomplete Java Code Snippets","authors":"Yiwen Dong, Tianxiao Gu, Yongqiang Tian, Chengnian Sun","doi":"10.1145/3510003.3510061","DOIUrl":"https://doi.org/10.1145/3510003.3510061","url":null,"abstract":"Code snippets are prevalent on websites such as Stack Overflow and are effective in demonstrating API usages concisely. However they are usually difficult to be used directly because most code snippets not only are syntactically incomplete but also lack dependency information, and thus do not compile. For example, Java snippets usually do not have import statements or required library names; only 6.88% of Java snippets on Stack Overflow include import statements necessary for compilation. This paper proposes SnR, a precise, efficient, constraint-based technique to automatically infer the exact types used in code snippets and the libraries containing the inferred types, to compile and therefore reuse the code snippets. Initially, SnR builds a knowledge base of APIs, i.e., various facts about the available APIs, from a corpus of Java libraries. Given a code snippet with missing import statements, SnR automatically extracts typing constraints from the snippet, solves the constraints against the knowledge base, and returns a set of APIs that satisfies the constraints to be imported into the snippet. We have evaluated SnR on a benchmark of 267 code snippets from Stack Overflow. SnR significantly outperforms the state-of-the-art tool Coster. SnR correctly infers 91.0% of the import statements, which makes 73.8% of the snippets compile, compared to 36.0% of the import statements and 9.0% of the snippets by Coster.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"110-111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122553403","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}

引用次数: 8

Precise Divide-By-Zero Detection with Affirmative Evidence 精确的除零检测与肯定的证据

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510066

Yiyuan Guo, Jinguo Zhou, Peisen Yao, Qingkai Shi, Charles Zhang

{"title":"Precise Divide-By-Zero Detection with Affirmative Evidence","authors":"Yiyuan Guo, Jinguo Zhou, Peisen Yao, Qingkai Shi, Charles Zhang","doi":"10.1145/3510003.3510066","DOIUrl":"https://doi.org/10.1145/3510003.3510066","url":null,"abstract":"The static detection of divide-by-zero, a common programming error, is particularly prone to false positives because conventional static analysis reports a divide-by-zero bug whenever it cannot prove the safety property – the divisor variable is not zero in all executions. When reasoning the program semantics over a large number of under-constrained variables, conventional static analyses significantly loose the bounds of divisor variables, which easily fails the safety proof and leads to a massive number of false positives. We propose a static analysis to detect divide-by-zero bugs taking additional evidence for under-constrained variables into consideration. Based on an extensive empirical study of known divide-by-zero bugs, we no longer arbitrarily report a bug once the safety verification fails. Instead, we actively look for affirmative evidences, namely source evidence and bound evidence, that imply a high possibility of the bug to be triggerable at runtime. When applying our tool Wit to the real-world software such as the Linux kernel, we have found 72 new divide-by-zero bugs with a low false positive rate of 22%.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122610856","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}

引用次数: 1

Demystifying Android Non-SDK APls: Measurement and Understanding 揭秘Android非sdk api:测量和理解

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510045

S. Yang, Rui Li, Jiongyi Chen, Wenrui Diao, Shanqing Guo

{"title":"Demystifying Android Non-SDK APls: Measurement and Understanding","authors":"S. Yang, Rui Li, Jiongyi Chen, Wenrui Diao, Shanqing Guo","doi":"10.1145/3510003.3510045","DOIUrl":"https://doi.org/10.1145/3510003.3510045","url":null,"abstract":"During the Android app development, the SDK is essential, which provides rich APIs to facilitate the implementations of functional-ities. However, in the Android framework, there still exist plenty of non-SDK APIs that are not well documented. These non-SDK APIs can be invoked through unconventional ways, such as Java reflection. On the other hand, these APIs are not stable and may be changed or even removed in future Android versions, providing no guarantee for compatibility. From Android 9 (API level 28), Google began to strictly restrict the use of non-SDK APIs, and the corresponding checking mechanism has been integrated into the Android OS. In this work, we systematically study the use and design of Android non-SDK APIs. Notably, we propose four research questions covering the restriction mechanism, the present usage status, malicious usage, and the API list evolution. To answer these questions, we conducted a large-scale measurement based on over 200K apps and the source code of three recent Android versions. As a result, a series of exciting and valuable findings are obtained. For example, Google's restriction is not strong enough and can still be bypassed. Besides, app developers use only a tiny part of non-SDK APIs. Our work provides new knowledge to the research community and can help researchers improve the Android API designs.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"69 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120889725","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}

引用次数: 2

Towards Boosting Patch Execution On-the-Fly 朝着提高补丁执行的方向发展

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510117

Samuel Benton, Yu Xie, Lan Lu, Mengshi Zhang, Xia Li, Ling Zhang

{"title":"Towards Boosting Patch Execution On-the-Fly","authors":"Samuel Benton, Yu Xie, Lan Lu, Mengshi Zhang, Xia Li, Ling Zhang","doi":"10.1145/3510003.3510117","DOIUrl":"https://doi.org/10.1145/3510003.3510117","url":null,"abstract":"Program repair is an integral part of every software system's life-cycle but can be extremely challenging. To date, various automated program repair (APR) techniques have been proposed to reduce manual debugging efforts. However, given a real-world buggy program, a typical APR technique can generate a large number of patches, each of which needs to be validated against the original test suite, incurring extremely high computation costs. Although existing APR techniques have already leveraged various static and/or dynamic information to find the desired patches faster, they are still rather costly. In this work, we propose SeAPR (Self-Boosted Automated Program Repair), the first general-purpose technique to leverage the earlier patch execution information during APR to directly boost existing APR techniques themselves on-the-fly. Our basic intuition is that patches similar to earlier high-quality/low-quality patches should be promoted/degraded to speed up the detection of the desired patches. The experimental study on 13 state-of-the-art APR tools demonstrates that, overall, SeAPR can sub-stantially reduce the number of patch executions with negligible overhead. Our study also investigates the impact of various configurations on SeAPR. Lastly, our study demonstrates that SeAPR can even leverage the historical patch execution information from other APR tools for the same buggy program to further boost the current APR tool.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133219883","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}

引用次数: 4

FlakiMe: Laboratory-Controlled Test Flakiness Impact Assessment FlakiMe:实验室控制测试薄片影响评估

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510194

Maxime Cordy, Renaud Rwemalika, Adriano Franci, Mike Papadakis, M. Harman

{"title":"FlakiMe: Laboratory-Controlled Test Flakiness Impact Assessment","authors":"Maxime Cordy, Renaud Rwemalika, Adriano Franci, Mike Papadakis, M. Harman","doi":"10.1145/3510003.3510194","DOIUrl":"https://doi.org/10.1145/3510003.3510194","url":null,"abstract":"Much research on software testing makes an implicit assumption that test failures are deterministic such that they always witness the presence of the same defects. However, this assumption is not always true because some test failures are due to so-called flaky tests, i.e., tests with non-deterministic outcomes. To help testing researchers better investigate flakiness, we introduce a test flakiness assessment and experimentation platform, called FlakiMe. FlakiMe supports the seeding of a (controllable) degree of flakiness into the behaviour of a given test suite. Thereby, FlakiMe equips researchers with ways to investigate the impact of test flakiness on their techniques under laboratory-controlled conditions. To demonstrate the application of FlakiMe, we use it to assess the impact of flakiness on mutation testing and program repair (the PRAPR and ARJA methods). These results indicate that a 10% flakiness is sufficient to affect the mutation score, but the effect size is modest (2% – 5%), while it reduces the number of patches produced for repair by 20% up to 100% of repair problems; a devastating impact on this application of testing. Our experiments with FlakiMe demonstrate that flakiness affects different testing applications in very different ways, thereby motivating the need for a laboratory-controllable flakiness impact assessment platform and approach such as FlakiMe.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130496783","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}

引用次数: 7

What the Fork? Finding Hidden Code Clones in npm 什么叉子?在npm中寻找隐藏的代码克隆

2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE) Pub Date : 2022-05-01 DOI: 10.1145/3510003.3510168

Elizabeth Wyss, Lorenzo De Carli, Drew Davidson

{"title":"What the Fork? Finding Hidden Code Clones in npm","authors":"Elizabeth Wyss, Lorenzo De Carli, Drew Davidson","doi":"10.1145/3510003.3510168","DOIUrl":"https://doi.org/10.1145/3510003.3510168","url":null,"abstract":"This work presents findings and mitigations on an under-studied issue, which we term shrinkwrapped clones, that is endemic to the npm software package ecosystem. A shrink-wrapped clone is a package which duplicates, or near-duplicates, the code of another package without any indication or refer-ence to the original package. This phenomenon represents a challenge to the hygiene of package ecosystems, as a clone package may siphon interest from the package being cloned, or create hidden duplicates of vulnerable, insecure code which can fly under the radar of audit processes. Motivated by these considerations, we propose UNWRAP-PER, a mechanism to programmatically detect shrinkwrapped clones and match them to their source package. UNWRAP-PER uses a package difference metric based on directory tree similarity, augmented with a prefilter which quickly weeds out packages unlikely to be clones of a target. Overall, our prototype can compare a given package within the entire npm ecosystem (1,716,061 packages with 20,190,452 differ-ent versions) in 72.85 seconds, and it is thus practical for live deployment. Using our tool, we performed an analysis of a subset of npm packages, which resulted in finding up to 6,292 previously unknown shrinkwrapped clones, of which up to 207 carried vulnerabilities from the original package that had already been fixed in the original package. None of such vulnerabilities were discoverable via the standard npm audit process.","PeriodicalId":202896,"journal":{"name":"2022 IEEE/ACM 44th International Conference on Software Engineering (ICSE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131638240","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}

引用次数: 10