IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security最新文献

High-Reliability Compilation Optimization Sequence Generation Framework Based ANN 基于人工神经网络的高可靠性编译优化序列生成框架

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2020-01-01 DOI: 10.1109/QRS51102.2020.00053

Jiang Wu, Jianjun Xu, Xiankai Meng, Zhuo Zhang, Nan Zhang, Haoyu Zhang

引用次数: 0

From Natural Language Requirements to Passive Test Cases Using Guarded Assertions 从自然语言需求到使用保护断言的被动测试用例

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2018-01-01 DOI: 10.1109/QRS.2018.00060

Daniel Flemström, Eduard Paul Enoiu, W. Afzal, Daniel Sundmark, T. Gustafsson, A. Kobetski

引用次数: 0

Hunting Killer Tasks for Cloud System through Machine Learning: A Google Cluster Case Study 通过机器学习为云系统寻找杀手级任务:一个Google集群案例研究

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2016-08-01 DOI: 10.1109/QRS.2016.11

Hongyan Tang, Ying Li, Tong Jia, Zhonghai Wu

{"title":"Hunting Killer Tasks for Cloud System through Machine Learning: A Google Cluster Case Study","authors":"Hongyan Tang, Ying Li, Tong Jia, Zhonghai Wu","doi":"10.1109/QRS.2016.11","DOIUrl":"https://doi.org/10.1109/QRS.2016.11","url":null,"abstract":"Motivated by frequent failures in cloud computing systems, we analyze failure frequency and failure continuity of tasks from the Google cloud cluster, and find what we call killer tasks that suffer from frequent failures and repeated rescheduling. Killer tasks cause unnecessary resource wasting and significant increase of scheduling workloads, which can be a big concern in cloud systems. We aim to recognize killer tasks at the very early stage of their occurrence so that they can be addressed proactively instead of being rescheduled repeatedly, so as to promote reliability and save resources. To recognize killer tasks from a large amount of tasks in real time is really challenging. In this paper, we first investigate characteristics and behavior patterns of killer tasks and then develop two machine learning based methods, K-HUNTER and C-HUNTER, for online recognition of killer tasks. The empirical results show that our approach performs at 97% of precision in recognizing killer tasks with an 89% timing advance and 88% of resource saving for the cloud system on average.","PeriodicalId":92210,"journal":{"name":"IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security","volume":"20 1","pages":"1-12"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81922765","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

Software Reliability Analysis of NASA Space Flight Software: A Practical Experience. NASA航天飞行软件可靠性分析:一种实践经验。

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2016-01-01 Epub Date: 2016-10-13 DOI: 10.1109/QRS.2016.50

Harish Sukhwani, Javier Alonso, Kishor S Trivedi, Issac Mcginnis

{"title":"Software Reliability Analysis of NASA Space Flight Software: A Practical Experience.","authors":"Harish Sukhwani, Javier Alonso, Kishor S Trivedi, Issac Mcginnis","doi":"10.1109/QRS.2016.50","DOIUrl":"https://doi.org/10.1109/QRS.2016.50","url":null,"abstract":"<p><p>In this paper, we present the software reliability analysis of the flight software of a recently launched space mission. For our analysis, we use the defect reports collected during the flight software development. We find that this software was developed in multiple releases, each release spanning across all software life-cycle phases. We also find that the software releases were developed and tested for four different hardware platforms, spanning from off-the-shelf or emulation hardware to actual flight hardware. For releases that exhibit reliability growth or decay, we fit Software Reliability Growth Models (SRGM); otherwise we fit a distribution function. We find that most releases exhibit reliability growth, with Log-Logistic (NHPP) and S-Shaped (NHPP) as the best-fit SRGMs. For the releases that experience reliability decay, we investigate the causes for the same. We find that such releases were the first software releases to be tested on a new hardware platform, and hence they encountered major hardware integration issues. Also such releases seem to have been developed under time pressure in order to start testing on the new hardware platform sooner. Such releases exhibit poor reliability growth, and hence exhibit high predicted failure rate. Other problems include hardware specification changes and delivery delays from vendors. Thus, our analysis provides critical insights and inputs to the management to improve the software development process. As NASA has moved towards a product line engineering for its flight software development, software for future space missions will be developed in a similar manner and hence the analysis results for this mission can be considered as a baseline for future flight software missions.</p>","PeriodicalId":92210,"journal":{"name":"IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security","volume":"3 ","pages":"386-397"},"PeriodicalIF":0.0,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1109/QRS.2016.50","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"35688247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Modeling Embedded Software Test Requirement Based on MARTE 基于MARTE的嵌入式软件测试需求建模

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2013-01-01 DOI: 10.1109/SERE-C.2013.43

Yichen Wang, Xinsheng Lan, Yikun Wang

引用次数: 1

A Study on Airborne Software Safety Requirements Patterns 机载软件安全需求模式研究

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2013-01-01 DOI: 10.1109/SERE-C.2013.44

Wei Chang, Xiaohong Bao, Xuefei Li

引用次数: 0

Application of Software Safety Analysis Using Event-B Event-B在软件安全分析中的应用

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2013-01-01 DOI: 10.1109/SERE-C.2013.45

Hong Zhang, Lili Xu

引用次数: 0

A Novel Method for Modeling Complex Network of Software System Security 一种新的软件系统安全复杂网络建模方法

IEEE International Conference on Software Quality, Reliability and Security : proceedings. IEEE International Conference on Software Quality, Reliability and Security Pub Date : 2012-01-01 DOI: 10.1109/SERE-C.2012.33

Hailin Li, Yadi Wang, Jihong Han

引用次数: 0