Understanding large software systems is difficult. Traditionally, automated tools are used to assist program understanding. However, the representations constructed by these tools often require prohibitive time and space. Demand-driven techniques can be used to reduce these requirements. However, the use of pointers in modern languages introduces additional problems that do not integrate well with these techniques. We present new techniques for effectively coping with pointers in large software

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... systems written in the C programming language and use our techniques to implement a program slicing tool. First, we use a fast, flow-insensitive, points-to analysis before traditional data-flow analysis. Second, we allow the user to parameterize the points-to analysis so that the resulting program slices more closely match the actual program behavior. Such information cannot easily be obtained by the tool or might otherwise be deemed unsafe. Finally, we present data-flow equations for dealing with pointers to local variables in recursive programs. These equations allow the user to select an arbitrary amount of calling context in order to better trade performance for precision. To validate our techniques, we present empirical results using our program slicer on large programs. The results indicate that cost-effective analysis of large programs with pointers is feasible using our techniques.