Detecting Functional Dependence Program Invariants Based on Data Mining

被引：0
|
作者：
Liu Shukun [1 ]
Yang Xiaohua [2 ]
机构：
[1] Hunan Int Econ Univ, Dept Comp Sci & Technol, Changsha, Hunan, Peoples R China
[2] Univ South China, Dept Comp Sci & Technol, Hengyang, Hunan, Peoples R China
来源：
2009 ASIA-PACIFIC CONFERENCE ON INFORMATION PROCESSING (APCIP 2009), VOL 1, PROCEEDINGS | 2009年
关键词：
program invariants; dynamically generating; quality of software;
D O I：
10.1109/APCIP.2009.91
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
With the development of computer science and technology, software has been widely applied in all kinds of business. It has been a very popular and important application system. So the quality of soft-ware causes more serious attention than before. Design by program invariant is a very important method which is used to improve quality of software. In this paper, a theory model of dynamically detecting technology of program invariant was built. And a new method of dynamically generating technology of program invariant of functional dependence based on the theory of database was showed. In this way, program invariant of functional dependence can be detected in a nimble way. Experiments have been done and the result demonstrates that the method is obviously reliable and efficient.
引用
收藏
页码：332 / +
页数：2
相关论文
共 50 条
  • [1] Detecting Silent Data Corruptions in Aerospace-Based Computing Using Program Invariants
    Ma, Junchi
    Yu, Dengyun
    Wang, Yun
    Cai, Zhenbo
    Zhang, Qingxiang
    Hu, Cheng
    INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING, 2016, 2016
  • [2] Dynamically detecting relevant program invariants
    Notkin, D
    SIXTH IEEE INTERNATIONAL CONFERENCE ON ENGINEERING OF COMPLEX COMPUTER SYSTEMS, PROCEEDINGS, 2000, : 162 - 162
  • [3] Apsect mining based on program dependence graph
    Min, Hongbo
    Xu, Baowen
    Qian, Ju
    Dongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Southeast University (Natural Science Edition), 2008, 38 (02): : 239 - 243
  • [4] Detecting Bugs of Concurrent Programs With Program Invariants
    Wang, Rong
    Ding, Zuohua
    Gui, Ning
    Liu, Yang
    IEEE TRANSACTIONS ON RELIABILITY, 2017, 66 (02) : 425 - 439
  • [5] Detecting Bugs of Concurrent Programs with Program Invariants
    Ding, Zuohua
    Wang, Rong
    Hu, Jueliang
    Liu, Yang
    2016 IEEE INTERNATIONAL CONFERENCE ON SOFTWARE QUALITY, RELIABILITY AND SECURITY COMPANION (QRS-C 2016), 2016, : 412 - 413
  • [6] Mining Temporal Properties of Data Invariants
    Lemieux, Caroline
    2015 IEEE/ACM 37TH IEEE INTERNATIONAL CONFERENCE ON SOFTWARE ENGINEERING, VOL 2, 2015, : 751 - 753
  • [7] Software Defects Detecting Method Based on Data Mining
    Yang, Peng
    ADVANCES IN COMPUTER SCIENCE, ENVIRONMENT, ECOINFORMATICS, AND EDUCATION, PT II, 2011, 215 : 272 - 278
  • [8] Applying Data Mining for Detecting Anomalies in Satellites Applying Data Mining for Detecting Anomalies in Satellites
    Azevedo, Denise Rotondi
    Ambrosio, Ana Maria
    Vieira, Marco
    2012 NINTH EUROPEAN DEPENDABLE COMPUTING CONFERENCE (EDCC 2012), 2012, : 212 - 217
  • [9] Data Mining Based Strategy for Detecting Malicious PDF Files
    Sayed, Samir G.
    Shawkey, Mohamed
    2018 17TH IEEE INTERNATIONAL CONFERENCE ON TRUST, SECURITY AND PRIVACY IN COMPUTING AND COMMUNICATIONS (IEEE TRUSTCOM) / 12TH IEEE INTERNATIONAL CONFERENCE ON BIG DATA SCIENCE AND ENGINEERING (IEEE BIGDATASE), 2018, : 661 - 667
  • [10] Data Mining Techniques for Detecting Household Characteristics Based on Smart Meter Data
    Gajowniczek, Krzysztof
    Zabkowski, Tomasz
    ENERGIES, 2015, 8 (07) : 7407 - 7427
12345