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Delta debugging

From Wikipedia, the free encyclopedia

Delta Debugging is a methodology to automate the debugging of programs using a scientific approach of hypothesis-trial-result loop. This methodology was first developed by Andreas Zeller of the Saarland University in 1999.[1]

In practice, the Delta Debugging algorithm builds on unit testing to isolate failure causes automatically - by systematically narrowing down failure-inducing circumstances until a minimal set remains. For example, if you can supply a test case that will produce the bug you are looking for, then you can feed that to the Delta Debugging algorithm, which will then simply try to trim useless functions and lines of code that are not needed to reproduce the bug, until a 1-minimal program is found.

Delta Debugging has been applied to isolate failure-inducing program input (e.g. an HTML page that makes a Web browser fail), failure-inducing user interaction (e.g. the keystrokes that make a program crash), or failure-inducing changes to the program code (e.g. after a failing regression test).

Later, some software development tools have been inspired by Delta Debugging, such as the bisect commands of revision control systems (e.g., git-bisect, svn-bisect, hg-bisect, etc.), which, instead of working on the program's code, apply the delta debugging methodology on the code history by comparing various versions until the faulty change is found.

Recently, Network Dialog Minimization a technique based on delta debugging is proposed to find the smallest subset of network traffic from the original dialog, that when replayed still achieves the same goal as the original dialog [2]



See also



  • Andreas Zeller: Why Programs Fail: A Guide to Systematic Debugging, Morgan Kaufmann, ISBN 1-55860-866-4
  • Learning from Code History A presentation at Google Tech Talk from the original inventor of the Delta Debugging
  1. ^ Zeller, Andreas (1999). "Yesterday, my program worked. Today, it does not. Why?". Software Engineering — ESEC/FSE '99. Lecture Notes in Computer Science. Vol. 1687. Springer. pp. 253–267. doi:10.1007/3-540-48166-4_16. ISBN 978-3-540-66538-0.
  2. ^ M. Zubair Rafique; et al. "Network Dialog Minimization and Network Dialog Diffing: Two Novel Primitives for Network Security Applications" (PDF). In Proceedings of 30th Annual Computer Security Applications Conference (ACSAC 2014). ACM.
  3. ^ danielwilkerson.com
  4. ^ DustMite, the general purpose data reduction tool
  5. ^ "Detecting Software Errors via Genetic Algorithms". 2014-03-05. Retrieved 22 July 2015.