Test Generation for High Coverage with Abstraction Refinement and Coarsening (ARC)

Decanato - Facoltà di scienze informatiche

Data d'inizio: 30 Aprile 2014

Data di fine: 1 Maggio 2014

You are cordially invited to attend the PhD Dissertation Defense of Mauro BALUDA on Wednesday, April 30th 2014 at 13h30 in room A32 (Red building)
 
Abstract:
Testing is the main approach used in the software industry to expose failures. Several empirical studies shows that test suites achieving high structural coverage rates present high failure detection ability.
However, producing highly covering test suites automatically is hard as certain code elements are executed only under complex conditions while other might be not reachable at all.

We propose ARC, a goal-oriented technique that combines static and dynamic software analysis to automatically generate test suites with high code coverage. At the core of our approach there is an abstract program model that enables the synergistic application of the different analysis components.
In ARC we integrate dynamic symbolic execution and abstraction refinement to precisely direct test generation towards the coverage goals and detect infeasible elements.
Our evaluation shows that the approach effectively exploits the synergy between symbolic testing and reachability analysis outperforming state of the art test generation approaches.

Dissertation Committee:

  • Prof. Mauro Pezzè, Università della Svizzera italiana, Switzerland (Research Advisor)
  • Prof. Giovanni Denaro, Università di Milano Bicocca, Italy (Research Co-Advisor)
  • Prof. Antonio Carzaniga, Università della Svizzera italiana, Switzerland (Internal Member)
  • Prof. Nate Nystrom, Università della Svizzera italiana, Switzerland (Internal Member)
  • Prof. Paolo Tonella, ITC-irst, Povo (Trento), Italy (External Member)
  • Prof. Andreas Zeller, Saarland University, Saarbrücken, Germany (External Member)