Wei Le  Assistant Professor

Computer Science, Iowa State University

weile(At)iastate.edu, CV, Research Log, Teaching Log

Papers, Code and Data


I am always looking forward to working with ambitious, highly motivated and talented students. Please contact me if you are interested in a research position in our lab.

  Recent Work and News

      9/18-9/19 trip: Teaching Software Carpentary @ Stanford Neurosciences Institute

      [MobileSoft17][ICSE17-Poster] [data] : Generating Predicate Callback Summaries for the Android Framework

  Research Interests


I work with Program Analysis Laboratory to develop fundamentals and applications of program analysis and software testing. We seek automatic, practical solutions in the areas of software engineering, systems, programming languages and machine learning for improving software reliability, security and performance.

   Selected Papers  

    [FSE16] Proteus: Computing Disjunctive Loop Summary via Path Dependency Analysis (Distinguished Paper)
    [ICSE16] Generating Performance Distributions via Probabilistic Symbolic Execution
    [ICSE14] Patch Verification via Multiversion Interprocedural Control Flow Graphs
    [ICSE13] Segmented Symbolic Analysis
    [TOSEM13] Marple: Detecting Faults in Path Segments Using Automatically Generated Analyses
    [FSE10] Path-Based Fault Correlations
    [FSE08] Marple, A Demand-Driven Path-Sensitive Buffer Overflow Detector


    2016, 2017 Fall: COM S 342 Principles of Programming Languages

    2016 Spring: COM S/CPRE 513x Foundations and Applications of Program Analysis

    2015 Fall: COM S 440/540 Principles and Practice of Compiling

  Professional Activities

    Co-chair: ICST'16 Testing Tool Demo, ICST'17 Workshop, ESEC/FSE'17 Doctoral Symposium

    PC/Journal Review: MOBS'13, TOSEM 2014/2015/2016, ICPC'14 ERA, ICSE'15 Demonstration, TSE 2015/2016, ISSTA'15, ICSE'16, ICST'16, ASE'16, FSE'18

    Panelist: NSF 2013/2014/2016, DOE 2015/2016

    SIGSOFT CAPS coordinator: 2014-2015

    Instructor: Software Carpentry, Data Carpentry