Symbolic techniques have been shown to be very effective in path-based test generation; however, they fail to scale to large programs due to the exponential number of paths to be explored. In this paper, we focus on tackling this path explosion problem and propose search strategies to achieve quick branch coverage under symbolic execution, while exploring only a fraction of paths in the program. We present a reachability-guided strategy that makes use of the reachability graph of the program to explore unvisited portions of the program and a conflictdriven backtracking strategy that utilizes conflict analysis to perform nonchronological backtracking. We present experimental evidence that these strategies can significantly reduce the search space and improve the speed of test generation for programs.

With the advent of advanced program analysis and constraint solving techniques, several test generation tools use variants of symbolic execution. Symbolic techniques have been shown to be very effective in path-based test generation; however, they fail to scale to large programs due to the exponential number of paths to be explored. In this paper, we focus on tackling this path explosion problem and propose search strategies to achieve quick branch coverage under symbolic execution, while exploring only a fraction of paths in the program. We present a reachability-guided strategy that makes use of the reachability graph of the program to explore unvisited portions of the program and a conflict-driven backtracking strategy that utilizes conflict analysis to perform nonchronological backtracking. We present experimental evidence that these strategies can significantly reduce the search space and improve the speed of test generation for programs.

An Efficient 2-Phase Strategy to Achieve High Branch Coverage Sarvesh Prabhu (ABSTRACT)Symbolic execution-based test generation is gaining popularity for software test generation.The increasing complexity of the software program is posing new challenges in software execution-based test generation because of the path explosion problem. We present a new 2-phase symbolic execution driven strategy that achieves high branch coverage in software quickly. Phase 1 follows a greedy approach that quickly covers as many branches as possible by exploring each branch through its corresponding shortest path prefix. Phase 2 covers the remaining branches that are left uncovered if the shortest path to the branch was infeasible.In Phase 1, a basic conflict driven learning is used to skip all the paths that may have any of the earlier encountered conflicting conditions, while in Phase 2, a more intelligent conflict driven learning is used to skip regions that do not have a feasible path to any unexplored branch. This results in considerable reduction in unnecessary SMT solver calls.Experimental results show that significant speedup can be achieved, effectively reducing the time to detect a bug and providing higher branch coverage for a fixed time out period than previous techniques.