2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)最新文献_第5页

EtherSolve: Computing an Accurate Control-Flow Graph from Ethereum Bytecode EtherSolve:从以太坊字节码计算精确的控制流图

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-16 DOI: 10.1109/ICPC52881.2021.00021

Filippo Contro, Marco Crosara, M. Ceccato, M. Preda

{"title":"EtherSolve: Computing an Accurate Control-Flow Graph from Ethereum Bytecode","authors":"Filippo Contro, Marco Crosara, M. Ceccato, M. Preda","doi":"10.1109/ICPC52881.2021.00021","DOIUrl":"https://doi.org/10.1109/ICPC52881.2021.00021","url":null,"abstract":"Motivated by the immutable nature of Ethereum smart contracts and of their transactions, quite many approaches have been proposed to detect defects and security problems before smart contracts become persistent in the blockchain and they are granted control on substantial financial value.Because smart contracts source code might not be available, static analysis approaches mostly face the challenge of analysing compiled Ethereum bytecode, that is available directly from the official blockchain. However, due to the intrinsic complexity of Ethereum bytecode (especially in jump resolution), static analysis encounters significant obstacles that reduce the accuracy of exiting automated tools.This paper presents a novel static analysis algorithm based on the symbolic execution of the Ethereum operand stack that allows us to resolve jumps in Ethereum bytecode and to construct an accurate control-flow graph (CFG) of the compiled smart contracts. EtherSolve is a prototype implementation of our approach. Experimental results on a significant set of real world Ethereum smart contracts show that EtherSolve improves the accuracy of the execrated CFGs with respect to the state of the art available approaches.Many static analysis techniques are based on the CFG representation of the code and would therefore benefit from the accurate extraction of the CFG. For example, we implemented a simple extension of EtherSolve that allows to detect instances of the re-entrancy vulnerability.","PeriodicalId":288873,"journal":{"name":"2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131081661","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

Using Grammar Patterns to Interpret Test Method Name Evolution 使用语法模式解释测试方法名称演变

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-16 DOI: 10.1109/ICPC52881.2021.00039

Anthony S Peruma, Emily Hu, Jiajun Chen, E. Alomar, Mohamed Wiem Mkaouer, Christian D. Newman

引用次数: 11

Using Non-Verbal Expressions as a Tool in Naming Research 非语言表达在命名研究中的应用

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-15 DOI: 10.1109/ICPC52881.2021.00040

Omer Regev, Michael Soloveitchik, D. Feitelson

引用次数: 2

Considerations and Pitfalls in Controlled Experiments on Code Comprehension 代码理解控制实验中的注意事项和缺陷

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-15 DOI: 10.1109/ICPC52881.2021.00019

D. Feitelson

引用次数: 11

Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting 用块抽象语法树分割改进代码摘要

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-14 DOI: 10.1109/ICPC52881.2021.00026

Chen Lin, Z. Ouyang, Junqing Zhuang, Jian-qiang Chen, Hui Li, Rongxin Wu

{"title":"Improving Code Summarization with Block-wise Abstract Syntax Tree Splitting","authors":"Chen Lin, Z. Ouyang, Junqing Zhuang, Jian-qiang Chen, Hui Li, Rongxin Wu","doi":"10.1109/ICPC52881.2021.00026","DOIUrl":"https://doi.org/10.1109/ICPC52881.2021.00026","url":null,"abstract":"Automatic code summarization frees software developers from the heavy burden of manual commenting and benefits software development and maintenance. Abstract Syntax Tree (AST), which depicts the source code’s syntactic structure, has been incorporated to guide the generation of code summaries. However, existing AST based methods suffer from the difficulty of training and generate inadequate code summaries. In this paper, we present the Block-wise Abstract Syntax Tree Splitting method (BASTS for short), which fully utilizes the rich tree-form syntax structure in ASTs, for improving code summarization. BASTS splits the code of a method based on the blocks in the dominator tree of the Control Flow Graph, and generates a split AST for each code split. Each split AST is then modeled by a Tree-LSTM using a pre-training strategy to capture local non-linear syntax encoding. The learned syntax encoding is combined with code encoding, and fed into Transformer to generate high-quality code summaries. Comprehensive experiments on benchmarks have demonstrated that BASTS significantly outperforms state-of-the-art approaches in terms of various evaluation metrics. To facilitate reproducibility, our implementation is available at https://github.com/XMUDM/BASTS.","PeriodicalId":288873,"journal":{"name":"2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129397190","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: 37

Predicting Community Smells’ Occurrence on Individual Developers by Sentiments 通过情绪预测社区气味对个体开发者的影响

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-12 DOI: 10.1109/ICPC52881.2021.00030

Zijie Huang, Zhiqing Shao, Guisheng Fan, Jianhua Gao, Ziyi Zhou, Kang Yang, Xingguang Yang

{"title":"Predicting Community Smells’ Occurrence on Individual Developers by Sentiments","authors":"Zijie Huang, Zhiqing Shao, Guisheng Fan, Jianhua Gao, Ziyi Zhou, Kang Yang, Xingguang Yang","doi":"10.1109/ICPC52881.2021.00030","DOIUrl":"https://doi.org/10.1109/ICPC52881.2021.00030","url":null,"abstract":"Community smells appear in sub-optimal software development community structures, causing unforeseen additional project costs, e.g., lower productivity and more technical debt. Previous studies analyzed and predicted community smells in the granularity of community sub-groups using socio-technical factors. However, refactoring such smells requires the effort of developers individually. To eliminate them, supportive measures for every developer should be constructed according to their motifs and working states. Recent work revealed developers’ personalities could influence community smells’ variation, and their sentiments could impact productivity. Thus, sentiments could be evaluated to predict community smells’ occurrence on them. To this aim, this paper builds a developer-oriented and sentiment-aware community smell prediction model considering 3 smells such as Organizational Silo, Lone Wolf, and Bottleneck. Furthermore, it also predicts if a developer quitted the community after being affected by any smell. The proposed model achieves cross- and within-project prediction F-Measure ranging from 76% to 93%. Research also reveals 6 sentimental features having stronger predictive power compared with activeness metrics. Imperative and indicative expressions, politeness, and several emotions are the most powerful predictors. Finally, we test statistically the mean and distribution of sentimental features. Based on our findings, we suggest developers should communicate in a straightforward and polite way.","PeriodicalId":288873,"journal":{"name":"2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132498086","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

A Multi-Modal Transformer-based Code Summarization Approach for Smart Contracts 基于多模态变压器的智能合约代码汇总方法

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-12 DOI: 10.1109/ICPC52881.2021.00010

Zhen Yang, J. Keung, Xiao Yu, Xiaodong Gu, Zhengyuan Wei, Xiaoxue Ma, Miao Zhang

{"title":"A Multi-Modal Transformer-based Code Summarization Approach for Smart Contracts","authors":"Zhen Yang, J. Keung, Xiao Yu, Xiaodong Gu, Zhengyuan Wei, Xiaoxue Ma, Miao Zhang","doi":"10.1109/ICPC52881.2021.00010","DOIUrl":"https://doi.org/10.1109/ICPC52881.2021.00010","url":null,"abstract":"Code comment has been an important part of computer programs, greatly facilitating the understanding and maintenance of source code. However, high-quality code comments are often unavailable in smart contracts, the increasingly popular programs that run on the blockchain. In this paper, we propose a Multi-Modal Transformer-based (MMTrans) code summarization approach for smart contracts. Specifically, the MMTrans learns the representation of source code from the two heterogeneous modalities of the Abstract Syntax Tree (AST), i.e., Structure-based Traversal (SBT) sequences and graphs. The SBT sequence provides the global semantic information of AST, while the graph convolution focuses on the local details. The MMTrans uses two encoders to extract both global and local semantic information from the two modalities respectively, and then uses a joint decoder to generate code comments. Both the encoders and the decoder employ the multi-head attention structure of the Transformer to enhance the ability to capture the long-range dependencies between code tokens. We build a dataset with over 300K pairs of smart contracts, and evaluate the MMTrans on it. The experimental results demonstrate that the MMTrans outperforms the state-of-the-art baselines in terms of four evaluation metrics by a substantial margin, and can generate higher quality comments.","PeriodicalId":288873,"journal":{"name":"2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133378892","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: 34

ArCode: A Tool for Supporting Comprehension and Implementation of Architectural Concerns ArCode:一个支持理解和实现架构关注点的工具

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-11 DOI: 10.1109/ICPC52881.2021.00056

A. Shokri, Mehdi Mirakhorli

{"title":"ArCode: A Tool for Supporting Comprehension and Implementation of Architectural Concerns","authors":"A. Shokri, Mehdi Mirakhorli","doi":"10.1109/ICPC52881.2021.00056","DOIUrl":"https://doi.org/10.1109/ICPC52881.2021.00056","url":null,"abstract":"Integrated development environments (IDE) play an important role in supporting developers during program comprehension and completion. Many of these supportive features focus on low-level programming and debugging activities. Unfortunately, there is less support in understanding and implementing architectural concerns in the form of patterns, tactics and/or other concerns. In this paper we present ArCode, a tool designed as a plugin for a popular IDE, IntelliJ IDEA. ArCode is able to learn correct ways of using frameworks’ API to implement architectural concerns such as Authentication and Authorization from two sources, sample programs that practice the framework, and the byte code of that framework. Analyzing a program under development, this tool is able to find deviations from correct implementation and provide fix recommendations alongside with graphical demonstrations to better communicate the recommendations with the developers. We showcase how programmers can benefit from ArCode by providing an example of API misuse detection and API recommendation for a popular Java framework, Java Authentication and Authorization (JAAS) security framework.","PeriodicalId":288873,"journal":{"name":"2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116217512","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

Atoms of Confusion in Java Java中的混淆原子

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2021-03-08 DOI: 10.1109/ICPC52881.2021.00012

C. Langhout, M. Aniche

引用次数: 7

Title Page iii 第三页标题

2021 IEEE/ACM 29th International Conference on Program Comprehension (ICPC) Pub Date : 2018-11-01 DOI: 10.1109/IPSN.2008.1

B. St, Louis, Missouri., Washington bullet Tokyo

引用次数: 0