 These calculations are straightforward, but in more realistic cases, there will be complications. The parties at trial will often put forward several piecemeal claims that need to be combined together to form a theory of what happened. For example, the prosecutor may present eyewitness testimony to argue that the defendant ran away from the crime scene, along with documentary evidence as proof of a motive. The different piecemeal claims, each supported by distinct pieces of evidence, must be combined to form structured hypotheses about what happened. Since different claims and different pieces of evidence may depend on one another, direct calculations would soon become unmanageable. Fortunately, a tool exists to make the task easier: Bayesian networks. This section identifies guidelines for deploying Bayesian networks in the presentation, aggregation and evaluation of complex bodies of evidence and hypotheses.