Learning Stateful Preconditions Modulo a Test Generator

被引:12
作者
Astorga, Angello [1 ]
Madhusudan, P. [1 ]
Saha, Shambwaditya [1 ]
Wang, Shiyu [1 ]
Xie, Tao [1 ]
机构
[1] Univ Illinois, Champaign, IL 61820 USA
来源
PROCEEDINGS OF THE 40TH ACM SIGPLAN CONFERENCE ON PROGRAMMING LANGUAGE DESIGN AND IMPLEMENTATION (PLDI '19) | 2019年
基金
美国国家科学基金会;
关键词
Specification Mining; Data-Driven Inference; Synthesis;
D O I
10.1145/3314221.3314641
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper, we present a novel learning framework for inferring stateful preconditions (i.e., preconditions constraining not only primitive-type inputs but also non-primitive-type object states) modulo a test generator, where the quality of the preconditions is based on their safety and maximality with respect to the test generator. We instantiate the learning framework with a specific learner and test generator to realize a precondition synthesis tool for C#. We use an extensive evaluation to show that the tool is highly effective in synthesizing preconditions for avoiding exceptions as well as synthesizing conditions under which methods commute.
引用
收藏
页码:775 / 787
页数:13
相关论文
共 42 条
  • [1] Albarghouthi Aws, 2016, POPL 2016
  • [2] Syntax-Guided Synthesis
    Alur, Rajeev
    Bodik, Rastislav
    Dallal, Eric
    Fisman, Dana
    Garg, Pranav
    Juniwal, Garvit
    Kress-Gazit, Hadas
    Madhusudan, P.
    Martin, Milo M. K.
    Raghothaman, Mukund
    Saha, Shamwaditya
    Seshia, Sanjit A.
    Singh, Rishabh
    Solar-Lezama, Armando
    Torlak, Emina
    Udupa, Abhishek
    [J]. DEPENDABLE SOFTWARE SYSTEMS ENGINEERING, 2015, 40 : 1 - 25
  • [3] Alur Rajeev, 2005, POPL 2005
  • [4] Alur Rajeev, 2017, TACAS 2017
  • [5] [Anonymous], 2017, FORMAL METHODS SYSTE
  • [6] Astorga Angello, 2018, DSN 2018
  • [7] Bodik Rastislav, 2002, POPL 2002
  • [8] Brumley David, 2007, CSF 2007
  • [9] Buse Raymond P. L., 2008, ISSTA 2008
  • [10] Chandra Satish, 2009, PLDI 2009