2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)最新文献

{"title":"Towards a Bayesian Network Model for Predicting Flaky Automated Tests","authors":"Tariq M. King, D. Santiago, Justin Phillips, Peter J. Clarke","doi":"10.1109/QRS-C.2018.00031","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00031","url":null,"abstract":"Artificial intelligence and machine learning are making it possible for computers to diagnose some medical diseases more accurately than doctors. Such systems analyze millions of patient records and make generalizations to diagnose new patients. A key challenge is determining whether a patient's symptoms are attributed to a known disease or other factors. Software testers face a similar problem when troubleshooting automation failures. They investigate questions like: Is a given failure due to a defect, environmental issue, or flaky test? Flaky tests exhibit both passing and failing results although neither the code nor test has changed. Maintaining flaky tests is costly, especially in large-scale software projects. In this paper, we present an approach that leverages Bayesian networks for classifying and predicting flaky tests. Our approach views the test flakiness problem as a disease by specifying its symptoms and possible causes. Preliminary results from a case study suggest the approach is feasible.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115433762","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}

{"title":"Information System Reliability Quantitative Assessment Method and Engineering Application","authors":"Jin-Gang Shang, Ping Chen, Qiang Wang, Liewen Lu","doi":"10.1109/QRS-C.2018.00044","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00044","url":null,"abstract":"In view of the current situation of the lack of theoretical and methodological guidance for the reliability test of information system, this paper puts forward a method of reliability quantitative assessment method of information system, and describes the feasibility of the method engineering application with a certain information system as the experimental object. It provides guidance for ordering and carrying out information system reliability for the research side, and provides the basis for quantitative evaluation of the reliability level of information system.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125557269","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}

{"title":"Collaborative Simulation Testing with State Behavior Tree","authors":"Yunqiang Yan, Siyou Ma","doi":"10.1109/QRS-C.2018.00084","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00084","url":null,"abstract":"Validation method based on simulation is generally used to ensure reliability of the embedded system. Combination of hardware in the loop simulation and full digital simulation to carry out collaborative simulation can use one's strengths to off-set the other's weaknesses, which is the most common means used. In order to resolve challengesfacedin collaborative simula-tion test along with hybrid real-time task scheduling, this paper proposed an optimized method of collaborative simulation test based on state behavior tree, which is composed of hierarchical design strategy of the test scripts, organization model of the states and behaviors in test execution as the state behavior tree struc-ture, test optimization by reusability of test execution results based on state behavior tree and hybrid real-time task scheduling mechanism. Experiments showed that this optimized method can improve test efficiency ofautomatic collaborativesimulation test combining hardware in the loop simulation and full digital simu-lation.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114191190","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}

{"title":"Safety-Based Software Reconfiguration Method for Integrated Modular Avionics Systems in AADL Model","authors":"Xiaomin Wei, Yunwei Dong, Mingrui Xiao","doi":"10.1109/QRS-C.2018.00083","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00083","url":null,"abstract":"Many Cyber-Physical Systems (CPSs) are safety-critical systems and reconfigurable, such as Integrated Modular Avionics (IMA) systems that are required to reconfigure at runtime when some components fail. However, designing a safe reconfigurable IMA system is challenging. This paper proposes a safety-based software reconfiguration method for IMA systems at the architecture level. The software reconfiguration method integrates error events and hazard triggers into the reconfiguration process. By extending AADL, Error Model Annex (EMV2) and Hazard Model Annex (HMA) can describe the method. The runtime architecture is described using Architecture Analysis and Design Language (AADL) and EMV2. The architecture and software reconfiguration method are combined as a complete AADL model. To simulate the IMA system with the proposed reconfiguration method, mapping rules from an AADL model to Deterministic Stochastic Petri nets (DSPNs) are formulated. Finally, an IMA system is applied to demonstrate the applicability and effectiveness of our safety-based reconfiguration method.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121599944","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}

{"title":"QRS 2018 Program Committee","authors":"Jun Ai, Doo-Hwan Bae, Xiaoying Bai, David Benavides, Arun Chakrapani, Junjie Chen, Frédéric Dadeau, Junhua Ding, T. Dohi, Mercedes G. Merayo, Osamu Mizuno, Tien Nguyen, Manuel Nuñez, H. Okamura, Hailong Sun, Linzhang Wang, Husnu Yenigun","doi":"10.1109/qrs-c.2018.00010","DOIUrl":"https://doi.org/10.1109/qrs-c.2018.00010","url":null,"abstract":"Jun Ai, Beihang University, China Domenico Amalfitano, University of Naples Federico II, France Doo-Hwan Bae, Korea Advanced Institute of Science and Technology, Korea Xiaoying Bai, Tsinghua University, China David Benavides, University of Seville, Spain Antonia Bertolino, Italian National Research Council, Italy Mario Bravetti, Università di Bologna, Italy Christof Budnik, Siemens, Germany Yan Cai, Chinese Academy of Sciences, China Emilia Cambronero, Universidad Castilla-La Mancha, Spain Ana Cavalli, IT SudParis, France Arun Chakrapani Rao, University of Warwick, UK W.K. Chan, City University of Hong Kong, Hong Kong Junjie Chen, Peking University, China Sunita Chulani, Cisco, USA Frederic Dadeau, University of Franche-Comté, France Junhua Ding, East Carolina University, USA Tadashi Dohi, Hiroshima University, Japan Wei Dong, National University of Defense Technology, China Yunwei Dong, Northwestern Polytechnical University, China Khaled El-Fakih, American University of Sharjah, UAE Sadik Esmelioglu, Middle East Technical University, Turkey Hugues Evrard, Imperial College London, UK Joao Pascoal Faria, University of Porto, Portugal Sudipto Ghosh, Colorado State University, USA Arnaud Gotlieb, Simula Research Laboratory, Norway Matthias Güdemann, diffBlue, UK Rajiv Gupta, University of California, Riverside, USA Song Huang, Army Engineering University, China Bo Jiang, Beihang University, China He Jiang, Dalian University of Technology, China Yu Jiang, Tsinghua University, China Xiaoyuan Jing, Wuhan University, China Roland Jochem, TU Berlin, Germany Yves Le Traon, University of Luxembourg, Luxembourg Jenny Li, Kean University, USA Huai Liu, Victoria University, Australia Lin Liu, Tsinghua University, China Shaoying Liu, Hosei University, Japan Liang Luo, University of Electronic Science and Technology of China, China Henrique Madeira, University of Coimbra, Portugal Dusica Marijan, Simula Research Laboratory, Norway Bruce McMillin, Missouri University of Science and Technology, USA","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132387442","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}

{"title":"Design and Application of a Sikuli Based Capture-Replay Tool","authors":"Jin-lei Sun, Shi-wen Zhang, Song Huang, Zhan-wei Hui","doi":"10.1109/QRS-C.2018.00021","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00021","url":null,"abstract":"Graphical user interface (GUI) testing is an important branch of software testing. Using capture-replay technology to automate GUI testing can effectively improve efficiency and save costs. However, most of the traditional capture-replay tools capture their GUI elements through the API of the SUT (System Under Test) and depend on the openness of the API; the generated scripts usually involve the internal code of the GUI elements, and the readability is not good. In this article, we proposed a capture-replay technology based on the open source tool-Sikuli, which can generate scripts with good readability based on the testers' operations and can record and playback any visual interface.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130207109","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}

{"title":"Defect Prediction Based on the Characteristics of Multilayer Structure of Software Network","authors":"Yiwen Yang, J. Ai, Fei Wang","doi":"10.1109/QRS-C.2018.00019","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00019","url":null,"abstract":"Software defect prediction can help us identify software defect modules and improve software quality. The existing defect prediction mainly analyzes the software code or the development process and uses the statistical feature data on the files or categories related to the software defects as the metrics. The method disregards the macroscopic integrity of software programs and the relevance of local defects to the surrounding program elements. For this reason, this study introduces a complex network technology into defect prediction, establishes a software network model, uses a complex network metric to design a set of metrics that can reflect the local and global features of defects, and proposes a dynamic prediction model optimization method based on the threshold filter algorithm. The effectiveness of the proposed metric and method is verified through comparison with the Predictive Model in Software Engineering dataset experiment and a practical engineering software data prediction experiment.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132951987","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}

{"title":"Research on the Information Quality Measurement of Judicial Documents","authors":"Hao Lian, Tieke He, Zemin Qin, Haoyu Li, Jia Liu","doi":"10.1109/QRS-C.2018.00043","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00043","url":null,"abstract":"This paper explores and defines data quality metrics of document data in judicial field. The objective information theory defines information as an objective reflection of the objects and the state of movement in the objective world and the subjective world. All kinds of information systems in physics can obtain, transmit, process and apply various objective information. Document is the carrier of case information, and the entity mapping of cases in the objective world. In order to describe the nature of the case infor-mation and its various dimensions accurately, this paper con-structs and quantifies the data quality evaluation standards of the documents with the help of six-tuple information theory and the related knowledge of rough sets.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131884063","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}

{"title":"MURE: Making Use of MUtations to REfine Spectrum-Based Fault Localization","authors":"Zijie Li, Lanfei Yan, Yuzhen Liu, Zhenyu Zhang, Bo Jiang","doi":"10.1109/QRS-C.2018.00024","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00024","url":null,"abstract":"Locating faults in programs is never an easy task. Spectrum-based fault localization (SBFL) techniques estimate suspicious statements by contrasting the coverage spectra collected from passed and failed program runs. Mutation-based such techniques locate faults by trying different mutates with the aim of finding one that involves less turbulence to program behavior. The latter is empirically known more accurate, but with massive increases in time complexity. In this paper, we propose a new approach, MURE, which uses methodology of the latter to refine results of the former. MURE first drives a stateor-the-art SBFL technique Naish2 to output a list of suspicious statements. It then picks out suspicious statement as candidates, generates mutates for them, and estimates their likelihood of relating to faults. Finally, it refines the resultant list by adjusting part of its ordering. An experiment validates its effectiveness by showing a 30% accuracy improvement over Naish2.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"132 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124432225","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}

{"title":"A New Software Reliability Evaluation Model Based on the Probability of the Failure Mode","authors":"Yunqiang Yan, Yanhong Peng, Chang Liu, Haifeng Li","doi":"10.1109/QRS-C.2018.00020","DOIUrl":"https://doi.org/10.1109/QRS-C.2018.00020","url":null,"abstract":"Most existing software reliability models are only suitable for the reliability testing based on the operation profile which has the low fault detection rate. The reliability testing based on the failure modes can improve the fault detection rate. However, it can't describe the reliability accurately for it doesn't have the related reliability models. To solve this problem, we propose a new reliability model for the reliability testing based on the failure modes. First, the probability of the failure mode is obtained according to the operation profile and the input value domain. Based on the probabilities of the failure modes, the failure rate of the function is calculated. Furthermore, the function transition matrix with the failure rate is constructed by Markov process. Then a new software reliability model is proposed based on the probabilities of the failure modes. We apply this new model on the engine control software. The experimental results showed this model can process the failure modes for calculating the reliability accurately. Meanwhile, the fault detection rate can be improved and the testing effort can be reduced significantly.","PeriodicalId":199384,"journal":{"name":"2018 IEEE International Conference on Software Quality, Reliability and Security Companion (QRS-C)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117333079","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}