SHF: MEDIUM: Collaborative Research: Transfer Learning in Software Engineering

Information

  • NSF Award
  • 1302169
Owner
  • Award Id
    1302169
  • Award Effective Date
    7/1/2013 - 11 years ago
  • Award Expiration Date
    6/30/2017 - 7 years ago
  • Award Amount
    $ 482,852.00
  • Award Instrument
    Continuing grant

SHF: MEDIUM: Collaborative Research: Transfer Learning in Software Engineering

The goal of the research is to enable software engineers to find software development best practices from past empirical data. The increasing availability of software development project data, plus new machine learning techniques, make it possible for researchers to study the generalizability of results across projects using the concept of transfer learning. Using data from real software projects, the project will determine and validate best practices in three areas: predicting software development effort; isolating software detects; effective code inspection practices. <br/><br/>This research will deliver new data mining technologies in the form of transfer learning techniques and tools that overcome current limitations in the state-of-the-art to provide accurate learning within and across projects. It will design new empirical studies, which apply transfer learning to empirical data collected from industrial software projects. It will build an on-line model analysis service, making the techniques and tools available to other researchers who are investigating validity of principles for best practice. <br/><br/>The broader impacts of the research will be to make empirical software engineering research results more transferable to practice, and to improve the research processes for the empirical software engineering community. By providing a means to test principles about software development, this work stands to transform empirical software engineering research and enable software managers to rely on scientifically obtained facts and conclusions rather than anecdotal evidence and one-off studies. Given the immense importance and cost of software in commercial and critical systems, the research has long-term economic impacts.

  • Program Officer
    Sol J. Greenspan
  • Min Amd Letter Date
    4/19/2013 - 11 years ago
  • Max Amd Letter Date
    6/1/2016 - 8 years ago
  • ARRA Amount

Institutions

  • Name
    Fraunhofer Center for Experimental Software Engineering
  • City
    College Park
  • State
    MD
  • Country
    United States
  • Address
    5825 University Research Court
  • Postal Code
    207403823
  • Phone Number
    2404872905

Investigators

  • First Name
    Lucas
  • Last Name
    Layman
  • Email Address
    llayman@fc-md.umd.edu
  • Start Date
    4/3/2014 12:00:00 AM
  • First Name
    Lucas
  • Last Name
    Layman
  • Email Address
    llayman@fc-md.umd.edu
  • Start Date
    4/19/2013 12:00:00 AM
  • End Date
    04/03/2014
  • First Name
    Forrest
  • Last Name
    Shull
  • Email Address
    fshull@fc-md.umd.edu
  • Start Date
    4/19/2013 12:00:00 AM
  • End Date
    04/03/2014

Program Element

  • Text
    SOFTWARE & HARDWARE FOUNDATION
  • Code
    7798
  • Text
    SOFTWARE ENG & FORMAL METHODS
  • Code
    7944

Program Reference

  • Text
    MEDIUM PROJECT
  • Code
    7924
  • Text
    SOFTWARE ENG & FORMAL METHODS
  • Code
    7944
  • Text
    EXP PROG TO STIM COMP RES
  • Code
    9150