Puzzle-based automatic testing: bringing humans into the loop by solving puzzles
Ning Chen, Sunghun Kim · 2012
Recently, many automatic test generation techniques have been proposed, such as Randoop, Pex and jCUTE. However, usually test coverage of these techniques has been around 50-60% only, due to several challenges, such as 1) the object mutation problem, where test generators cannot create and/or modify test inputs to desired object states; and 2) the constraint solving problem, where test generators fail to solve path conditions to cover certain branches. By analyzing branches not covered by state-of-the-art techniques, we noticed that these challenges might not be so difficult for humans.