Dynamic Symbolic Execution (DSE) is a state-of-the-art test-generation approach that systematically explores program paths to generate high-covering tests. In DSE, the presence of loops (especially unbound loops) can cause an enormous or even infinite number of paths to be explored. There exist techniques (such as bounded iteration, heuristics, and summarization) that assist DSE in addressing loop problems. However, there exists no literature-survey or empirical work that shows the pervasiveness of loop problems or identifies challenges faced by these techniques on real-world open-source applications. To fill this gap, we provide characteristic studies to guide future research on addressing loop problems for DSE. Our proposed study methodology starts with conducting a literature-survey study to investigate how technical problems such as loop problems compromise automated software-engineering tasks such as test generation, and which existing techniques are proposed to deal with such technical problems. Then the study methodology continues with conducting an empirical study of applying the existing techniques on real-world software applications sampled based on the literature-survey results and major open-source project hostings. This empirical study investigates the pervasiveness of the technical problems and how well existing techniques can address such problems among real-world software applications. Based on such study methodology, our two-phase characteristic studies identify that bounded iteration and heuristics are effective in addressing loop problems when used properly. Our studies further identify challenges faced by these techniques and provide guidelines for effectively addressing these challenges.