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Unit Test Data Generation for C Using Rule-Directed Symbolic execution

Journal of Computer Science & Technology 2019年第3期34卷 670-689页

作者： Ming-Zhe Zhang Yun-Zhan Gong Ya-Wen Wang Da-Hai Jin State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing 100876China

Unit testing is widely used in software development. One important activity in unit testing is automatic test data generation. Constraint-based test data generation is a technique for automatic generation of test data, which uses symbolic execution to generate constraints. Unit testing only tests functions instead of the whole program, where individual functions typically have preconditions imposed on their inputs. Conventional symbolic execution cannot detect these preconditions, let alone converting these preconditions into constraints. To overcome these limitations, we propose a novel unit test data generation approach using rule-directed symbolic execution for dealing with functions with missing input preconditions. Rule-directed symbolic execution uses predefined rules to detect preconditions in the individual function, and generates constraints for inputs based on preconditions. We introduce implicit constraints to represent preconditions, and unify implicit constraints and program constraints into integrated constraints. Test data generated based on integrated constraints can explore previously unreachable code and help developers find more functional faults and logical faults. We have implemented our approach in a tool called CTS-IC, and applied it to real-world projects. The experimental results show that rule-directed symbolic execution can find preconditions (implicit constraints) automatically from an individual function. Moreover, the unit test data generated by our approach achieves higher coverage than similar tools and efficiently mitigates missing input preconditions problems in unit testing for individual functions.

关键词： automated unit testing program constraint symbolic execution static analysis

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Toward parallel intelligence: An interdisciplinary solution for complex systems

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The Innovation 2023年第6期4卷 152-164页

作者： Yong Zhao Zhengqiu Zhu Bin Chen Sihang Qiu Jincai Huang Xin Lu Weiyi Yang Chuan Ai Kuihua Huang Cheng He Yucheng Jin Zhong Liu Fei-Yue Wang College of Systems Engineering National University of Defense TechnologyChangsha 410073China Hunan Institute of Advanced Technology Changsha 410073China Shanghai Institute of Infectious Disease and Biosecurity Shanghai 200032China Institute of Epidemiology Helmholtz Zentrum Minchen-German Research Center for Environmental Health(GmbH)NeuherbergGermany Department of Computer Science Hong Kong Baptist UniversityHong KongChina State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

The growing complexity of real-world systems necessitates interdisciplinary solutions to confront myriad challenges in modeling,analysis,management,and control.To meet these demands,the parallel systems method rooted in the artificial systems,computational experiments,and parallel execution(ACP)approach has been developed.The method cultivates a cycle termed parallel intelligence,which iteratively creates data,acquires knowledge,and refines the actual system.Over the past two decades,the parallel systems method has continuously woven advanced knowledge and technologies from various disciplines,offering vers atile interdisciplinary solutions for complex systems across diverse fields.This review explores the origins and fundamental concepts of the parallel systems method,showcasing its accomplishments as a diverse array of parallel technologies and applica-tions while also prognosticating potential challenges.We posit that this method will considerably augment sustainable development while enhancing interdisciplinary communication and cooperation.

关键词： execution artificial offering

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Multiregional neural pathway: from movement planning to initiation

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Signal Transduction and Targeted Therapy 2022年第7期7卷 2121-2122页

作者： Xing-feng Mao Shuai-shuai Wang Feng Han Key Laboratory of Cardiovascular&Cerebrovascular Medicine Drug Target and Drug Discovery CenterSchool of PharmacyNanjing Medical UniversityNanjingChina Gusu School Nanjing Medical UniversitySuzhou Municipal HospitalThe Affiliated Suzhou Hospital of Nanjing Medical UniversitySuzhouChina Institute of Brain Science The Affiliated Brain Hospital of Nanjing Medical UniversityNanjingChina

A recent study by Inagaki et al.provides new evidence that the input from the pedunculopontine nucleus/midbrain reticular nucleus(PPN/MRN)to the thalamus can trigger a rapid switch of ALM activity from a motor planning mode to a motor execution mode.1 Planning and execution are vital components of motor behavior that are produced by distinct patterns of neuronal activity.Neuroscience researchers have devoted substantial effort to exploring how the precise neural pathway mediates cuetriggered population activity pattern switching for the execution of planned movements.The different patterns of neuronal population activity in the motor cortex,thalamus,brainstem,and spinal cord are related to motor planning and execution.2,3 However,to understand how neuronal dynamics in the cortex trigger motor execution,it is essential to explore the mechanism underlying the transition between those different modes in response to contextual Go cues(Fig.1).

关键词： cortex al. execution

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Detecting Bank Conflict of GPU Programs Using Symbolic execution—Case Study

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Journal of Software Engineering and Applications 2017年第2期10卷 159-167页

作者： Koki Hamaya Satoshi Yamane Graduate School of Natural Science and Technology Kanazawa University Kanazawa Japan

GPU (Graphics Processing Unit) is used in various areas. Therefore, the demand for the verification of GPU programs is increasing. In this paper, we suggest the method to detect bank conflict by using symbolic execution. Bank conflict is one of the bugs happening in GPU and it leads the performance of programs lower. Bank conflict happens when some processing units in GPU access the same shared memory. Symbolic execution is the method to analysis programs with symbolic values. By using it, we can detect bank conflict on GPU programs which use many threads. We implement a prototype of the detector for bank conflict and evaluate it with some GPU programs. The result states that we can detect bank conflict on the programs with no loop regardless of the number of threads.

关键词： Graphics Processing Units GPU Bank Conflict Symbolic execution Model Checking

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A Trading execution Model Based on Mean Field Games and Optimal Control

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Applied Mathematics 2014年第19期5卷 3091-3116页

作者： Lorella Fatone Francesca Mariani Maria Cristina Recchioni Francesco Zirilli Dipartimento di Matematica e Informatica Università di Camerino Camerino Italy Dipartimento di Scienze Economiche Università degli Studi di Verona Verona Italy Dipartimento di Management Università Politecnica delle Marche Ancona Italy Dipartimento di Matematica “G. Castelnuovo” Università di Roma “La Sapienza” Roma Italy

We present a trading execution model that describes the behaviour of a big trader and of a multitude of retail traders operating on the shares of a risky asset. The retail traders are modeled as a population of “conservative” investors that: 1) behave in a similar way, 2) try to avoid abrupt changes in their trading strategies, 3) want to limit the risk due to the fact of having open positions on the asset shares, 4) in the long run want to have a given position on the asset shares. The big trader wants to maximize the revenue resulting from the action of buying or selling a (large) block of asset shares in a given time interval. The behaviour of the retail traders and of the big trader is modeled using respectively a mean field game model and an optimal control problem. These models are coupled by the asset share price dynamic equation. The trading execution strategy adopted by the retail traders is obtained solving the mean field game model. This strategy is used to formulate the optimal control problem that determines the behaviour of the big trader. The previous mathematical models are solved using the dynamic programming principle. In some special cases explicit solutions of the previous models are found. An extensive numerical study of the trading execution model proposed is presented. The interested reader is referred to the website: http://www.***.univpm.it/recchioni/finance/w19 to find material including animations, an interactive application and an app that helps the understanding of the paper. A general reference to the work of the authors and of their coauthors in mathematical finance is the website:?http://www.***.univpm.it/recchioni/finance.

关键词： Trading execution Mean Field Game Optimal Control

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Specifying the Global execution Context of Computer-Mediated Tasks: A Visual Notation and a Supporting Tool

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Journal of Software Engineering and Applications 2010年第4期3卷 312-330页

作者： Demosthenes Akoumianakis Department of Applied Informatics & Multimedia School of Applied Technologies Advanced Technological Education Institution of Crete Crete Greece.

This paper presents the notion of the global execution context of a task as a representational construct for analysing complexity in software evolution. Based on this notion a visual notation and a supporting tool are presented to support specification of a system’s global execution context. A system’s global execution context is conceived as an evolving network of use scenarios depicted by nodes and links designating semantic relationships between scenarios. A node represents either a base or a growth scenario. Directed links characterize the transition from one node to another by means of semantic scenario relationships. Each growth scenario is generated following a critique (or screening) of one or more base or reference scenarios. Subsequently, representative growth scenarios are compiled and consolidated in the global execution context graph. The paper describes the stages of this process, presents the tool designed to facilitate the construction of the global execution context graph and elaborates on recent practice and experience.

关键词： Non-Functional Requirements Software Evolution Artifacts Global execution Context Tools

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融合执行力与适应性：基层治理的制度优势分析

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中国政治 2024年第5期

作者：李晴刘海军

基层是国家制度传导的神经末梢，其治理效能的有效发挥是制度优势最直接的体现。新时代十年来，我国各领域基础性制度框架基本建立，但发展不平衡不充分问题仍然突出，信息公开、垃圾分类等基层治理中的制度优势彰显不足。制度优势向治... 详细信息

基层是国家制度传导的神经末梢，其治理效能的有效发挥是制度优势最直接的体现。新时代十年来，我国各领域基础性制度框架基本建立，但发展不平衡不充分问题仍然突出，信息公开、垃圾分类等基层治理中的制度优势彰显不足。制度优势向治理效能转化是国家治理的应然逻辑，转化过程中的动态机制、信任关系都会影响到制度执行的效果。单纯以制度执行力评判制度优势和治理效能略显偏颇，制度之所以具备优势，在于其能体现公平正义、呼应人之需求。而不同人的利益追求、目标取向、认知结构均不相同，这导致基层治理中制度出现适应性问题。经由理论层面的合理补充与实然层面的动态修复，融合执行力与适应性，有望打通制度优势、运行机制、信任支撑、治理效能的闭合回路，从而加快制度优势向基层传导，并反向以基层治理效能倒逼各类制度优化完善。

关键词：基层治理制度优势治理效能执行力适应性　　grassroots governance institutional advantages governance effectiveness execution adaptability

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A New Speculative execution Algorithm Based on C4.5 Decision Tree for Hadoop

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国际计算机前沿大会会议论文集 2015年第1期 83-84页

作者： Yuanzhen Li Qun Yang Shangqi Lai Bohan Li Nanjing University of Aeronautics and Astronautics NanJingChina The University of Hong Kong HongKongChina

As a distributed computing platform, Hadoop provides an effective way to handle big data. In Hadoop, the completion time of job will be delayed by a straggler. Although the definitive cause of the straggler is hard to detect, speculative execution is usually used for dealing with this problem, by simply backing up those stragglers on alternative nodes. In this paper, we design a new Speculative execution algorithm based on C4.5 Decision Tree, SECDT, for Hadoop. In SECDT, we speculate completion time of stragglers and also of backup tasks, based on a kind of decision tree method: C4.5 decision tree. After we speculate the completion time, we compare the completion time of stragglers and of the backup tasks, calculating their differential value, and selecting the straggler with the maximum differential value to start the backup task.Experiment result shows that the SECDT can predict execution time more accurately than other speculative execution methods, hence reduce the job completion time.

关键词： speculative execution C4.5 decision tree Hadoop

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Machine learning for automated experimentation in scanning transmission electron microscopy

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npj Computational Materials 2023年第1期9卷 25-40页

作者： Sergei V.Kalinin Debangshu Mukherjee Kevin Roccapriore Benjamin J.Blaiszik Ayana Ghosh Maxim A.Ziatdinov Anees Al-Najjar Christina Doty Sarah Akers Nageswara S.Rao Joshua C.Agar Steven R.Spurgeon Department of Materials Science and Engineering University of TennesseeKnoxvilleTN 37996USA Computational Sciences and Engineering Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Center for Nanophase Materials Sciences Oak Ridge National LaboratoryOak RidgeTN 37831USA Argonne National Laboratory Data Science and Learning DivisionChicagoIL 60439USA University of Chicago GlobusChicagoIL 60637USA National Security Directorate Pacific Northwest National LaboratoryRichlandWA 99352USA Department of Materials Science and Engineering Drexel UniversityPhiladelphiaPA 19104USA Department of Physics University of WashingtonSeattleWA 98195USA

Machine learning(ML)has become critical for post-acquisition data analysis in(scanning)transmission electron microscopy,(S)TEM,imaging and spectroscopy.An emerging trend is the transition to real-time analysis and closed-loop microscope operation.The effective use of ML in electron microscopy now requires the development of strategies for microscopy-centric experiment workflow design and optimization.Here,we discuss the associated challenges with the transition to active ML,including sequential data analysis and out-of-distribution drift effects,the requirements for edge operation,local and cloud data storage,and theory in the loop operations.Specifically,we discuss the relative contributions of human scientists and ML agents in the ideation,orchestration,and execution of experimental workflows,as well as the need to develop universal hyper languages that can apply across multiple platforms.These considerations will collectively inform the operationalization of ML in next-generation experimentation.

关键词： optimization automated execution

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On strong-scaling and open-source tools for analyzing atom probe tomography data

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npj Computational Materials 2021年第1期7卷 148-157页

作者： Markus Kühbach Priyanshu Bajaj Huan Zhao Murat HÇelik Eric AJägle Baptiste Gault Max-Planck-Institut für Eisenforschung GmbH(MPIE) DüsseldorfGermany m4p material solutions GmbH MagdeburgGermany Institute for Advanced Simulation(IAS) Jülich Supercomputing Centre(JSC)JülichGermany Universität der Bundeswehr München NeubibergGermany Department of Materials Imperial College LondonRoyal School of MinesLondonUK

The development of strong-scaling computational tools for high-throughput methods with an open-source code and transparent metadata standards has successfully transformed many computational materials science communities.While such tools are mature already in the condensed-matter physics community,the situation is still very different for many experimentalists.Atom probe tomography(APT)is one example.This microscopy and microanalysis technique has matured into a versatile nano-analytical characterization tool with applications that range from materials science to geology and possibly beyond.Here,data science tools are required for extracting chemo-structural spatial correlations from the reconstructed point cloud.For APT and other high-end analysis techniques,post-processing is mostly executed with proprietary software tools,which are opaque in their execution and have often limited performance.Software development by members of the scientific community has improved the situation but compared to the sophistication in the field of computational materials science several gaps remain.This is particularly the case for open-source tools that support scientific computing hardware,tools which enable high-throughput workflows,and open welldocumented metadata standards to align experimental research better with the fair data stewardship principles.To this end,we introduce paraprobe,an open-source tool for scientific computing and high-throughput studying of point cloud data,here exemplified with APT.We show how to quantify uncertainties while applying several computational geometry,spatial statistics,and clustering tasks for post-processing APT datasets as large as two billion ions.These tools work well in concert with Python and HDF5 to enable several orders of magnitude performance gain,automation,and reproducibility.

关键词： hardware Python execution

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