Visible to the public Predicting the Difficulty of Compromise through How Attackers Discover VulnerabilitiesConflict Detection Enabled

Submitted by gargvaibhav on Thu, 12/15/2022 - 6:38am

PI(s), Co-PI(s), Researchers:

PI: Andrew Meneely; Co-PI: Laurie Williams; Researchers: Ben Meyers and Nasif Imtiaz

HARD PROBLEM(S) ADDRESSED
This refers to Hard Problems, released November 2012.

  • Metrics

PUBLICATIONS
Papers were written as a result of your research from the current quarter only.

KEY HIGHLIGHTS

  • We continued working on a user study of the Taxonomy For Human Errors in Software Engineering (T.H.E.S.E.). In this study, participants track their software engineering activity and write down their human errors. Each week, they classify those errors according to T.H.E.S.E. and do a semi-structured interview with Ben Meyers. The project has lasted for twelve weeks in total and has yielded some great feedback for improving the taxonomy as a whole. The data for the user study has been collected and is now being analyzed.

Each effort should submit one or two specific highlights. Each item should include a paragraph or two along with a citation if available. Write as if for the general reader of IEEE S&P.
The purpose of the highlights is to give our immediate sponsors a body of evidence that the funding they are providing (in the framework of the SoS lablet model) is delivering results that "more than justify" the investment they are making.

COMMUNITY ENGAGEMENT

EDUCATIONAL ADVANCES:

  • None.
Groups: