SHF: Small: Dynamic Analysis on Code Fragments
SHF:小:代码片段的动态分析
基本信息
- 批准号:1816352
- 负责人:
- 金额:$ 48.6万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2018
- 资助国家:美国
- 起止时间:2018-10-01 至 2023-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
In many software engineering environments, software developers would like to understand, test, debug and verify a relatively small fragment of code instead of the entire program. However, currently available program analysis and testing tools only work on programs that are whole, in the sense that they can be compiled and executed as a whole program. When the goal is to target only a small code fragment, it is excessively expensive and time-consuming to test and analyze the targeted code in the context of entire programs, which requires configuring a whole system, setting up the execution environment, and finding suites of test inputs that supply all the needed data values to execute the whole program. Software development processes would be much more efficient and effective if a program property for the code fragment of interest could be checked as a standalone unit of code. This research project addresses the technical challenges in converting code fragments into testable units. If software testing and analysis could be applied successfully to code fragments, rather than whole programs, the overall process of developing correct code would be streamlined. This project focuses on dynamic program analysis, which is the analysis of computer software that is performed by executing programs in a run-time environment (as opposed to static analysis, which is analysis of the source code). The project will generate algorithms, tools, and data that can advance the state of the art of program analysis tools and software engineering practice. The results will be disseminated through conferences, classrooms, open source projects, industrial collaborations and STEM volunteer opportunities.For dynamic program analysis to be effective, the target program must be executed with sufficient test inputs to produce interesting (e.g., incorrect or anomalous) behaviors. Dynamic analysis is made difficult by frequently huge numbers of program paths, and the large number of inputs that must be tested. Often, the tests are ineffective because they produce an overwhelming number of false positives and often fail on parts of the program that are not even relevant to the purpose of understanding, debugging or verifying the targeted code. The project will develop an approach to take code fragments, selected or constructed from the original program, and generate compilable and executable units, using new syntactic patching techniques to enable dynamic analysis on code fragments. It will also develop a techniques to search for and select meaningful code fragments on which to operate.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在许多软件工程环境中,软件开发人员希望理解,测试,调试和验证相对较小的代码片段,而不是整个程序。然而,当前可用的程序分析和测试工具仅对完整的程序起作用,在某种意义上,它们可以作为整个程序被编译和执行。当目标是仅针对小的代码片段时,在整个程序的上下文中测试和分析目标代码是非常昂贵和耗时的,这需要配置整个系统,设置执行环境,并找到提供执行整个程序所需的所有数据值的测试输入套件。 如果感兴趣的代码片段的程序属性可以作为独立的代码单元进行检查,则软件开发过程将更加高效和有效。这个研究项目解决了将代码片段转换为可测试单元的技术挑战。如果软件测试和分析可以成功地应用于代码片段,而不是整个程序,那么开发正确代码的整个过程将被简化。该项目侧重于动态程序分析,这是通过在运行时环境中执行程序来执行的计算机软件分析(相对于静态分析,这是对源代码的分析)。该项目将产生算法,工具和数据,可以推进程序分析工具和软件工程实践的艺术状态。结果将通过会议、课堂、开源项目、行业合作和STEM志愿者机会传播。为了使动态程序分析有效,目标程序必须在执行时有足够的测试输入,以产生有趣的(例如,不正确或异常)行为。由于经常有大量的程序路径以及必须测试的大量输入,动态分析变得困难。通常,测试是无效的,因为它们产生了大量的误报,并且经常在程序的某些部分失败,这些部分甚至与理解,调试或验证目标代码的目的无关。 该项目将开发一种方法,采用从原始程序中选择或构建的代码片段,并使用新的语法修补技术生成可编译和可执行的单元,以实现对代码片段的动态分析。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(1)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Validating static warnings via testing code fragments
- DOI:10.1145/3460319.3464832
- 发表时间:2021-06
- 期刊:
- 影响因子:0
- 作者:Ashwin Kallingal Joshy;Xueyuan Chen;Benjamin Steenhoek;Wei Le
- 通讯作者:Ashwin Kallingal Joshy;Xueyuan Chen;Benjamin Steenhoek;Wei Le
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Wei Le其他文献
Exploring service quality model from the perspective of sensory perception
从感官感知角度探索服务质量模型
- DOI:
10.1080/14783363.2020.1747425 - 发表时间:
2020 - 期刊:
- 影响因子:3.9
- 作者:
Jing Yang;Xiang Jin;Wei Le;Fei Sheng - 通讯作者:
Fei Sheng
Urethral reconstruction with RNA interference and polycaprolactone/silk fibroin/collagen electrospun fiber in rabbits
RNA干扰和聚己内酯/丝素蛋白/胶原电纺纤维重建兔尿道
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Chengdang Xu;Ying Liu;Chao Li;Weidong Zhou;Shengsong Huang;Wei Le;Zhe Hong;Denglong Wu - 通讯作者:
Denglong Wu
Ru-Embedded Highly Porous Carbon Nanocubes Derived from Metal-Organic Frameworks for Catalyzing Reversible Li2O2 Formation
源自金属有机框架的钌嵌入高多孔碳纳米立方体用于催化可逆 Li2O2 形成
- DOI:
10.1021/acsami.1c06572 - 发表时间:
2021 - 期刊:
- 影响因子:9.5
- 作者:
Wei Le;Ma Yong;Gu Yuting;Yuan Xuzhou;He Ying;Li Xinjian;Zhao Liang;Peng Yang;Deng Zhao - 通讯作者:
Deng Zhao
DeepDiagnosis: Automatically Diagnosing Faults and Recommending Actionable Fixes in Deep Learning Programs
DeepDiagnosis:自动诊断深度学习程序中的故障并推荐可行的修复方案
- DOI:
10.1145/3510003.3510071 - 发表时间:
2021 - 期刊:
- 影响因子:0
- 作者:
Mohammad Wardat;Breno Dantas Cruz;Wei Le;Hridesh Rajan - 通讯作者:
Hridesh Rajan
Marple: Detecting faults in path segments using automatically generated analyses
Marple:使用自动生成的分析检测路径段中的故障
- DOI:
10.1145/2491509.2491512 - 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Wei Le;M. Soffa - 通讯作者:
M. Soffa
Wei Le的其他文献
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{{ truncateString('Wei Le', 18)}}的其他基金
Collaborative Research: SHF: Medium: Learning Semantics of Code To Automate Software Assurance Tasks
协作研究:SHF:媒介:学习代码语义以自动化软件保障任务
- 批准号:
2313054 - 财政年份:2023
- 资助金额:
$ 48.6万 - 项目类别:
Standard Grant
CAREER: Analyzing Program Changes and Versions for Bug Detection and Diagnosis
职业:分析程序更改和版本以进行错误检测和诊断
- 批准号:
1350886 - 财政年份:2014
- 资助金额:
$ 48.6万 - 项目类别:
Continuing Grant
CAREER: Analyzing Program Changes and Versions for Bug Detection and Diagnosis
职业:分析程序更改和版本以进行错误检测和诊断
- 批准号:
1542117 - 财政年份:2014
- 资助金额:
$ 48.6万 - 项目类别:
Continuing Grant
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