2016 IEEE 16th International Working Conference on Source Code Analysis and Manipulation (SCAM)最新文献

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BinCFP: Efficient Multi-threaded Binary Code Control Flow Profiling 高效多线程二进制代码控制流分析

2016 IEEE 16th International Working Conference on Source Code Analysis and Manipulation (SCAM) Pub Date : 2016-10-01 DOI: 10.1109/SCAM.2016.21

Jiang Ming, Dinghao Wu

{"title":"BinCFP: Efficient Multi-threaded Binary Code Control Flow Profiling","authors":"Jiang Ming, Dinghao Wu","doi":"10.1109/SCAM.2016.21","DOIUrl":"https://doi.org/10.1109/SCAM.2016.21","url":null,"abstract":"In many tasks of reverse engineering and binary code analysis (e.g., hybrid disassembly, resolving indirect jump, and decoupled taint analysis), the knowledge of detailed dynamic control flow can be of great value. However, the high runtime overhead beset the complete collection of dynamic control flow. The previous efforts on efficient path profiling cannot be directly applied to the obfuscated binary code in which an accurate control flow graph is typically absent. To address these challenges, we present BinCFP, an efficient multi-threaded binary code control flow profiling tool by taking advantage of pervasive multi-core platforms. BinCFP relies on dynamic binary instrumentation to work with the unmodified binary code. The key of BinCFP is a multi-threaded fast buffering scheme that supports processing trace buffers asynchronously. To achieve better performance gains, we also apply a set of optimizations to reduce control flow profile size and instrumentation overhead. Our design enables the complete dynamic control flow collection for an obfuscated binary execution. We have implemented BinCFP on top of Pin. The comparative experiments on SPEC2006 and obfuscated common utility programs show BinCFP outperforms the previous work in several ways. In addition, BinCFP's control flow profile sizes are only about 49.2% that of the conventional design.","PeriodicalId":407579,"journal":{"name":"2016 IEEE 16th International Working Conference on Source Code Analysis and Manipulation (SCAM)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115297920","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

Collective Intelligence for Smarter API Recommendations in Python Python中更智能的API推荐的集体智能

2016 IEEE 16th International Working Conference on Source Code Analysis and Manipulation (SCAM) Pub Date : 2016-08-31 DOI: 10.1109/SCAM.2016.22

A. D'Souza, Di Yang, C. Lopes

{"title":"Collective Intelligence for Smarter API Recommendations in Python","authors":"A. D'Souza, Di Yang, C. Lopes","doi":"10.1109/SCAM.2016.22","DOIUrl":"https://doi.org/10.1109/SCAM.2016.22","url":null,"abstract":"Software developers use Application Programming Interfaces (APIs) of libraries and frameworks extensively while writing programs. In this context, the recommendations provided in code completion pop-ups help developers choose the desired methods. The candidate lists recommended by these tools, however, tend to be large, ordered alphabetically and sometimes even incomplete. A fair amount of work has been done recently to improve the relevance of these code completion results, especially for statically typed languages like Java. However, these proposed techniques rely on the static type of the object and are therefore inapplicable for a dynamically typed language like Python. In this paper, we present PyReco, an intelligent code completion system for Python which uses the mined API usages from open source repositories to order the results based on relevance rather than the conventional alphabetic order. To recommend suggestions that are relevant for a working context, a nearest neighbor classifier is used to identify the best matching usage among all the extracted usage patterns. To evaluate the effectiveness of our system, the code completion queries are automatically extracted from projects and tested quantitatively using a ten-fold cross validation technique. The evaluation shows that our approach outperforms the alphabetically ordered API recommendation systems in recommending APIs for standard, as well as, third-party libraries.","PeriodicalId":407579,"journal":{"name":"2016 IEEE 16th International Working Conference on Source Code Analysis and Manipulation (SCAM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129868175","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: 16

A Source-Level Energy Optimization Framework for Mobile Applications 移动应用的源级能量优化框架

2016 IEEE 16th International Working Conference on Source Code Analysis and Manipulation (SCAM) Pub Date : 2016-08-18 DOI: 10.1109/SCAM.2016.12

Xueliang Li, J. Gallagher

引用次数: 18

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