2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)最新文献

Securing Smart Contracts in Blockchain 保护区块链中的智能合约

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00032

Jaturong Kongmanee, Phongphun Kijsanayothin, R. Hewett

{"title":"Securing Smart Contracts in Blockchain","authors":"Jaturong Kongmanee, Phongphun Kijsanayothin, R. Hewett","doi":"10.1109/ASEW.2019.00032","DOIUrl":"https://doi.org/10.1109/ASEW.2019.00032","url":null,"abstract":"Blockchain is an emerging technology that underlies creation and exchange of the digital assets, including cryptocurrency such as Bitcoin and Ether, without the need for a central authority. It provides a public ledger for recording sequence of transactions in blocks that are linked as a chain. Smart contracts are computer programs governing participant agreements that are automatically enforced by consensus protocols in the blockchain. Together, blockchain and smart contracts revolutionize efficient transaction stores, services and workflows that work even among distrusting participants and without a trusted authority. Unfortunately, like most software, smart contracts are vulnerable as evidenced by a recent Decentralized Autonomous Organization (DAO) attack that lost cryptocurrency then-valued about $60 million. Correctness of executions alone is not sufficient to guarantee security of smart contracts. This paper addresses how we can apply model checking, a well-established formal verification technique, to help alleviate security issues in smart contract development. Most existing studies have focused on verification of smart contracts on a specific language and specific platform. Smart contracts may have hidden operational side effects that impact software behaviors. Thus, applying model checking to smart contracts is not necessarily straightforward. This paper presents a general technique for building the core functional models applicable for model checking to identify all possible executions that lead to security breaches. It also shows how resulting executions can be systematically analyzed to help identify security issues. The models are language and system independent in that they can represent any smart contract in any language or any platform. We illustrate and evaluate the technique with a widely used example of a smart contract in a financial system along with experimental results using a well-known model checker, NuSMV in various scenarios.","PeriodicalId":277020,"journal":{"name":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116752800","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

Predicting Defects with Latent and Semantic Features from Commit Logs in an Industrial Setting 利用工业环境中提交日志的潜在特征和语义特征预测缺陷

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00038

Beyza Eken, RiFat Atar, Sahra Sertalp, Ayse Tosun Misirli

引用次数: 5

The Effect of Weighted Moving Windows on Security Vulnerability Prediction 加权移动窗口对安全漏洞预测的影响

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00031

P. Kudjo, Jinfu Chen, Selasie Brown Aformaley, Solomon Mensah

{"title":"The Effect of Weighted Moving Windows on Security Vulnerability Prediction","authors":"P. Kudjo, Jinfu Chen, Selasie Brown Aformaley, Solomon Mensah","doi":"10.1109/ASEW.2019.00031","DOIUrl":"https://doi.org/10.1109/ASEW.2019.00031","url":null,"abstract":"Vulnerability prediction models strive to identify vulnerable modules in large software systems. Consequently, several vulnerability prediction approaches have been proposed to identify such susceptible units by using software metrics, historical data, and machine learning techniques. However, in spite of the key role seasonal trends of vulnerabilities play in estimating the resources needed for developing corrective measures, most of the proffered models fail to examine the trend, level, and seasonality of security vulnerability. To address this lacuna, this paper examines the statistical significance of the annual seasonal patterns and trends in vulnerability discovery using the weighted moving window. Our approach takes into account the chronological order within vulnerability data and assigns different weights of importance to projects in a window to effectively portray current security practices. Specifically, we used three regression-based models as vulnerability predictors for historical vulnerability data mined from five open-source applications offered by the Common Vulnerability Exposures and the National Vulnerability Database (CVE-NVD). In addition, we evaluate the performance and reliability of the models with symmetric mean absolute percent error (SMAPE). The preliminary results suggest that weighting the moving window based on Gaussian function yields improved accuracy and the recommended forecasting model is the robust regression.","PeriodicalId":277020,"journal":{"name":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133211260","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

Synthesizing Mutable Configurations: Setting up Systems for Success 综合可变配置:为成功建立系统

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00034

Tim Nelson, Natasha Danas, Theophilos Giannakopoulos, S. Krishnamurthi

引用次数: 5

On the Engineering of AI-Powered Systems 关于人工智能驱动系统的工程

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00042

Evgeny Kusmenko, Svetlana Pavlitskaya, Bernhard Rumpe, Sebastian Stüber

{"title":"On the Engineering of AI-Powered Systems","authors":"Evgeny Kusmenko, Svetlana Pavlitskaya, Bernhard Rumpe, Sebastian Stüber","doi":"10.1109/ASEW.2019.00042","DOIUrl":"https://doi.org/10.1109/ASEW.2019.00042","url":null,"abstract":"More and more tasks become solvable using deep learning technology nowadays. Consequently, the amount of neural network code in software rises continuously. To make the new paradigm more accessible, frameworks, languages, and tools keep emerging. Although, the maturity of these tools is steadily increasing, we still lack appropriate domain specific languages and a high degree of automation when it comes to deep learning for productive systems. In this paper we present a multi-paradigm language family allowing the AI engineer to model and train deep neural networks as well as to integrate them into software architectures containing classical code. Using input and output layers as strictly typed interfaces enables a seamless embedding of neural networks into component-based models. The lifecycle of deep learning components can then be governed by a compiler accordingly, e.g. detecting when (re-)training is necessary or when network weights can be shared between different network instances. We provide a compelling case study, where we train an autonomous vehicle for the TORCS simulator. Furthermore, we discuss how the methodology automates the AI development process if neural networks are changed or added to the system.","PeriodicalId":277020,"journal":{"name":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116179647","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

On Secret Management and Handling in Mobile Application Development Life Cycle: A Position Paper 移动应用开发生命周期中的秘密管理与处理:立场文件

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00033

P. Bunyakiati, Usa Sammapun

引用次数: 2

Service Application Knowledge Graph and Dependency System 服务应用知识图谱与依赖系统

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00043

Hanzhang Wang, C. Shah, Praseeda Sathaye, Amit Nahata, Sanjeev Katariya

引用次数: 4

Challenges in Secure Engineering of Critical Infrastructure Systems 关键基础设施系统安全工程的挑战

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00030

Sridhar Adepu, Eunsuk Kang, A. Mathur

引用次数: 5

Explaining Business Process Software with Fulib-Scenarios 用全场景解释业务流程软件

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00024

Albert Zündorf, Sebastian Copei, I. Diethelm, Claude Draude, A. Kunz, U. Norbisrath

引用次数: 1

Android App Merging for Benchmark Speed-Up and Analysis Lift-Up Android应用合并的基准加速和分析提升

2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW) Pub Date : 2019-11-01 DOI: 10.1109/ASEW.2019.00019

Felix Pauck, Shikun Zhang

{"title":"Android App Merging for Benchmark Speed-Up and Analysis Lift-Up","authors":"Felix Pauck, Shikun Zhang","doi":"10.1109/ASEW.2019.00019","DOIUrl":"https://doi.org/10.1109/ASEW.2019.00019","url":null,"abstract":"In the field of software analysis a trade-off between scalability and accuracy always exists. In this respect, Android app analysis is no exception, in particular, analyzing large or many apps can be challenging. Dealing with many small apps is a typical challenge when facing micro-benchmarks such as DROIDBENCH or ICC-BENCH. These particular benchmarks are not only used for the evaluation of novel tools but also in continuous integration pipelines of existing mature tools to maintain and guarantee a certain quality-level. Considering this latter usage it becomes very important to be able to achieve benchmark results as fast as possible. Hence, benchmarks have to be optimized for this purpose. One approach to do so is app merging. We implemented the Android Merge Tool (AMT) following this approach and show that its novel aspects can be used to produce scaled up and accurate benchmarks. For such benchmarks Android app analysis tools do not suffer from the scalability-accuracy trade-off anymore. We show this throughout detailed experiments on DROIDBENCH employing three different analysis tools (AMANDROID, ICCTA, FLOWDROID). Benchmark execution times are largely reduced without losing benchmark accuracy. Moreover, we argue why AMT is an advantageous successor of the state-of-the-art app merging tool (APKCOMBINER) in analysis lift-up scenarios.","PeriodicalId":277020,"journal":{"name":"2019 34th IEEE/ACM International Conference on Automated Software Engineering Workshop (ASEW)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127830753","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