Java program analysis by symbolic execution

Program analysis has a long history in computer science. Even when only considering the important aspect of termination analysis, in the past decades an overwhelming number of different techniques has been developed. While the programming languages considered by these approaches initially were more of theoretical importance than of practical use, recently also automated analyses for imperative programming languages like C or Java have been developed. Here, a major challenge is to deal with language constructs and concepts which do not exist in simpler languages. For example, in Java one often uses dynamic dispatch, complex object hierarchies, or side-effects with far-reaching consequences involving the global heap. In this thesis, we present a preprocessing step for Java Bytecode programs in which all such complicated language constructs are handled. This way, subsequent analyses do not need to be concerned with these, and making use of existing techniques is easy. In particular, we show how Symbolic Execution Graphs can be constructed which contain an over-approximation of all possible program runs. This way, and by taking care of having a precise approximation, the information contained in the constructed graphs can, for example, be used to reason about the termination behavior of the original program. Additionally to the construction of such graphs, in this thesis we present a new analysis technique which helps end users identify parts of the analyzed code which are irrelevant for the desired outcome. This way, programming errors causing code to be not executed can be identified and, consequently, fixed by the user. For this technique to be useful, the information contained in the previously constructed graph needs to be precise. We will demonstrate that this is the case. For the techniques presented in this thesis, a rigorous formalization is shown. To comply with the overall goal of, for example, automated termination analysis, we also need to implement the techniques and theoretical results. In this thesis we show how certain hard to automate aspects can be approached, leading to a competitive implementation. The techniques presented in this thesis are implemented in the AProVE tool. As also related techniques working on Symbolic Execution Graphs are implemented in AProVE, with the click of a button users can analyze Java Bytecode programs for (non)termination and find irrelevant code. In the annual International Termination Competition, it is demonstrated that currently AProVE is the most powerful termination analyzer for Java Bytecode programs.