2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS)最新文献_第5页

Quality of Reusable Game Software: Empowering Developers with Automated Quality Checks 可重用游戏软件的质量:授权开发者进行自动质量检查

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00061

W. V. D. Vegt, W. Westera

引用次数: 0

TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs TFCheck:用于检测神经网络程序中训练问题的TensorFlow库

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00059

Houssem Ben Braiek, Foutse Khomh

{"title":"TFCheck : A TensorFlow Library for Detecting Training Issues in Neural Network Programs","authors":"Houssem Ben Braiek, Foutse Khomh","doi":"10.1109/QRS.2019.00059","DOIUrl":"https://doi.org/10.1109/QRS.2019.00059","url":null,"abstract":"The increasing inclusion of Machine Learning (ML) models in safety-critical systems like autonomous cars have led to the development of multiple model-based ML testing techniques. One common denominator of these testing techniques is their assumption that training programs are adequate and bug-free. These techniques only focus on assessing the performance of the constructed model using manually labeled data or automatically generated data. However, their assumptions about the training program are not always true as training programs can contain inconsistencies and bugs. In this paper, we examine training issues in ML programs and propose a catalog of verification routines that can be used to detect the identified issues, automatically. We implemented the routines in a Tensorflow-based library named TFCheck. Using TFCheck, practitioners can detect the aforementioned issues automatically. To assess the effectiveness of TFCheck, we conducted a case study with real-world, mutants, and synthetic training programs. Results show that TFCheck can successfully detect training issues in ML code implementations.","PeriodicalId":122665,"journal":{"name":"2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115105082","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

Fault Detection in Timed FSM with Timeouts by SAT-Solving 基于sat求解的定时FSM超时故障检测

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00049

Omer Nguena Timo, Dimitri Prestat, Florent Avellaneda

引用次数: 2

Improving the Accuracy of Vulnerability Report Classification Using Term Frequency-Inverse Gravity Moment 利用项频率-反重力矩提高漏洞报告分类的准确性

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00041

P. Kudjo, Jinfu Chen, Minmin Zhou, Solomon Mensah, Rubing Huang

{"title":"Improving the Accuracy of Vulnerability Report Classification Using Term Frequency-Inverse Gravity Moment","authors":"P. Kudjo, Jinfu Chen, Minmin Zhou, Solomon Mensah, Rubing Huang","doi":"10.1109/QRS.2019.00041","DOIUrl":"https://doi.org/10.1109/QRS.2019.00041","url":null,"abstract":"Software vulnerability analysis is one of the critical issues in the software industry, and vulnerability classification plays a major role in this analysis. A typical vulnerability classification model usually involves a stage of term selection, in which the relevant terms are identified via feature selection. It also involves a stage of term weighting, in which document weights for the selected terms are computed, and a stage for classifier learning. Generally, the term frequency-inverse document frequency (TF-IDF) is the most widely used term-weighting method. However, empirical evidence shows that the TF-IDF is plagued with issues pertaining to its effectiveness. This paper introduces a new approach for vulnerability classification, which is based on term frequency and inverse gravity moment (TF-IGM). The proposed method is validated by empirical experiments using three machine learning algorithms on ten publicly available vulnerability datasets. The result shows that TF-IGM outperforms the benchmark method across the applications studied.","PeriodicalId":122665,"journal":{"name":"2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126718555","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: 15

[Copyright notice] (版权)

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/qrs.2019.00003

引用次数: 0

Publisher's Information 出版商的信息

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/qrs.2019.00062

引用次数: 0

Efficient Evolutionary Fuzzing for Android Application Installation Process Android应用程序安装过程的高效演化模糊分析

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00021

Veysel Hataş, Sevil Şen, J. A. Clark

引用次数: 0

On the Investigation of Essential Diversities for Deep Learning Testing Criteria 深度学习测试标准的本质差异性研究

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00056

Zhiyi Zhang, Xiaoyuan Xie

引用次数: 5

A Mechanism for Automatically Summarizing Software Functionality from Source Code 一种从源代码自动总结软件功能的机制

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-07-01 DOI: 10.1109/QRS.2019.00028

C. Psarras, Themistoklis G. Diamantopoulos, A. Symeonidis

引用次数: 3

Repeatable Decentralized Simulations for Cyber-Physical Systems 网络物理系统的可重复分散仿真

2019 IEEE 19th International Conference on Software Quality, Reliability and Security (QRS) Pub Date : 2019-06-22 DOI: 10.1109/QRS.2019.00040

Christophe Reymann, M. Foughali, S. Lacroix

引用次数: 2