2021 28th Asia-Pacific Software Engineering Conference (APSEC)最新文献_第2页

AWaRE2-MM: A Meta-Model for Goal-Driven, Contract-Mediated, Team-Centric Autonomous Middleware Frameworks for Antifragility AWaRE2-MM:目标驱动、契约中介、以团队为中心的反脆弱性自治中间件框架的元模型

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00066

Anton V. Uzunov, Matthew Brennan, Mohan Baruwal Chhetri, Quoc Bao Vo, R. Kowalczyk, John Wondoh

引用次数: 4

Probabilistic testing of asynchronously communicating systems 异步通信系统的概率测试

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00058

Puneet Bhateja

{"title":"Probabilistic testing of asynchronously communicating systems","authors":"Puneet Bhateja","doi":"10.1109/APSEC53868.2021.00058","DOIUrl":"https://doi.org/10.1109/APSEC53868.2021.00058","url":null,"abstract":"Input-output labelled transition system (IOLTS) is a state-based model that is widely used to describe the functional behaviour of a reactive system. However when the same system is observed asynchronously through a pair of unbounded FIFO queues (or channels), its apparent behaviour is different from its actual behaviour. This is because an execution trace of the system could appear distorted in a multitude of ways. The apparent behaviour is called the asynchronous behaviour of the system. It is well known that the asynchronous behaviour can also be described by an infinite-state IOLTS. This description however proves to be appropriate only as long as the channels are assumed to be reliable. The moment we throw in unreliability assumptions, the asynchronous behaviour becomes probabilistic in nature. The plain IOLTS model is simply not expressive enough to capture this probabilistic behaviour. To this end, we in this paper show how the asynchronous behaviour of a reactive system can be captured by Segala's probabilistic automata (SPA). We further show how the SPA expressing the asynchronous behaviour can serve as a reference model for probabilistic testing of asynchronously communicating systems.","PeriodicalId":143800,"journal":{"name":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133506420","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: 0

PGraph: A Graph-based Structure for Interactive Event Exploration on Social Media PGraph:基于图的社交媒体互动事件探索结构

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00015

Yang Yu, Minglai Shao, Hongyan Xu, Ying Sun, Wenjun Wang, Bofei Ma

{"title":"PGraph: A Graph-based Structure for Interactive Event Exploration on Social Media","authors":"Yang Yu, Minglai Shao, Hongyan Xu, Ying Sun, Wenjun Wang, Bofei Ma","doi":"10.1109/APSEC53868.2021.00015","DOIUrl":"https://doi.org/10.1109/APSEC53868.2021.00015","url":null,"abstract":"Event detection is a common research topic in visualization. Existing methods always follow an exploration mode, where machine learning algorithms identify events and then analyze them via a visualization system. The detection process does not integrate the expert's experience. In this paper, we propose a novel framework that organizes the original dataset as an integrated graph that allows for Interactive Event Detection (IED) on the graph. Specifically, we formulate the problem Interactive Event Detection as subgraph detection on the graph under expert's interactions. Further, we define a flexible structure called PGraph to model the dataset and then propose an efficient algorithm that returns a subgraph as an event. Our proposed method supports performing various IED tasks under the expert's interactions. We evaluate the utility of our approach by applying it in two scenarios. One uses a social media dataset to study hot events; the other urban burglary dataset is used to detect consecutive burglary cases. Case studies show that our algorithm could detect more global events considering the expert's experience. By quantitative performance experiments, our method outperforms traditional machine detection approaches, especially in the social media dataset; our method's accuracy is higher than baselines at least 10%.","PeriodicalId":143800,"journal":{"name":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134052669","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

An Exploration Study On the Dependency Among Vulnerabilities and Bugs 漏洞与bug依赖关系的探索性研究

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00074

Shaikh Mostafa, Xiaoyin Wang

引用次数: 0

Verification Assisted Gas Reduction for Smart Contracts 智能合约的验证辅助减气

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00034

Bo Gao, Siyuan Shen, Ling Shi, Jiaying Li, Jun Sun, Lei Bu

{"title":"Verification Assisted Gas Reduction for Smart Contracts","authors":"Bo Gao, Siyuan Shen, Ling Shi, Jiaying Li, Jun Sun, Lei Bu","doi":"10.1109/APSEC53868.2021.00034","DOIUrl":"https://doi.org/10.1109/APSEC53868.2021.00034","url":null,"abstract":"Smart contracts are computerized transaction protocols built on top of blockchain networks. Users are charged with fees, a.k.a. gas in Ethereum, when they create, deploy or execute smart contracts. Since smart contracts may contain vulnerabilities which may result in huge financial loss, developers and smart contract compilers often insert codes for security checks. The trouble is that those codes consume gas every time they are executed. Many of the inserted codes are however redundant. In this work, we present sOptimize, a tool that optimizes smart contract gas consumption automatically without compromising functionality or security. sOptimize works on smart contract bytecode, statically identifies 3 kinds of code patterns, and further removes them through verification-assisted techniques. The resulting code is guaranteed to be equivalent to the original one and can be directly deployed on blockchain. We evaluate sOptimize on a collection of 1,152 real-world smart contracts and show that it optimizes 43% of them, and the reduction on gas consumption is about 2.0% while in deployment and 1.2% in transactions, the amount can be as high as 954,201 gas units per contract.","PeriodicalId":143800,"journal":{"name":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","volume":"10 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114171386","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

Effective Bug Triage Based on a Hybrid Neural Network 基于混合神经网络的有效Bug分类

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00016

Hongbing Wang, Qi Li

{"title":"Effective Bug Triage Based on a Hybrid Neural Network","authors":"Hongbing Wang, Qi Li","doi":"10.1109/APSEC53868.2021.00016","DOIUrl":"https://doi.org/10.1109/APSEC53868.2021.00016","url":null,"abstract":"With the increasing scale and complexity of open source software, the quality of software has become a focus to which repairers pay close attention. Due to the inevitable existence of some known or unknown bugs in software,under certain conditions, software bugs may directly cause program running errors, and then produce abnormal running results and wrong program behavior, which will cause huge economic losses. Therefore, software defect repair is an important part of software evolution and quality assurance. Quickly and efficiently assigning defect reports to the right repairer for repair,to ensure efficiency and reduce the cost of open-source software development is an important problem that must be solved in software quality improvement. In this study, we propose a new defect report repair recommendation algorithm, RCNN, which can effectively learn the features of the defect report and recommend the appropriate repairer according to the feature. The proposed algorithm uses a CNN convolution kernel to capture the local information of the text and RNN is used to capture the sequence information of the text. The attention mechanism is introduced to learn the contribution ratio of each part of the text to the overall semantic information of the text. Thus, to a certain extent, it makes up for the defect that RNN cannot effectively learn and monitor remote information. Through experiments on the Eclipse and Mozilla datasets, compared with NB (naive Bayes), SVM (support vector machines), LeeCNN and DBRNNA, the RCNN model can effectively find the appropriate bug repairer among many repairers, and achieve higher classification accuracy.","PeriodicalId":143800,"journal":{"name":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114341946","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

[Copyright notice] (版权)

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/apsec53868.2021.00003

引用次数: 0

Improving Semantic Consistency of Variable Names with Use-Flow Graph Analysis 用用流图分析改进变量名的语义一致性

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00030

Yusuke Shinyama, Yoshitaka Arahori, K. Gondow

引用次数: 0

Message from the APSEC 2021 Chairs APSEC 2021届主席致辞

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/apsec53868.2021.00005

引用次数: 0

Thread-Sensitive Data Race Detection for Java 线程敏感的Java数据竞争检测

2021 28th Asia-Pacific Software Engineering Conference (APSEC) Pub Date : 2021-12-01 DOI: 10.1109/APSEC53868.2021.00011

S. Schulz, Emanuel Herrendorf, Christoph Bockisch

{"title":"Thread-Sensitive Data Race Detection for Java","authors":"S. Schulz, Emanuel Herrendorf, Christoph Bockisch","doi":"10.1109/APSEC53868.2021.00011","DOIUrl":"https://doi.org/10.1109/APSEC53868.2021.00011","url":null,"abstract":"In this paper we present StaTS, a precise static data-race detection mechanism for Java. It analyzes applications in four phases. The first one is a novel points-to analysis that includes approximations of threads and execution contexts. The second phase uses the results of the points-to analysis to compute which fields are accessed by which threads, while considering the locks held by the threads. The third phase carries out a context-sensitive static happens-before analysis to rule out accesses in execution contexts that can never be executed in parallel. The final phase builds upon the results of the first three to determine conflicting accesses and report them to the user. Our proof-of-concept implementation does not scale for large programs, which is why it can optionally limit the number of points-to relations it considers, based on sampling. Nevertheless, our evaluation shows that, even with sampling enabled for large programs, StaTS detects more data races than existing approaches. In terms of execution time, the analysis without sampling takes in the order of seconds for smaller programs. For larger ones and with sampling enabled, analysis takes minutes, thus being practically usable in nightly build environments in all cases.","PeriodicalId":143800,"journal":{"name":"2021 28th Asia-Pacific Software Engineering Conference (APSEC)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130257391","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