The first interprocedural modification side-effects analysis for C (MOD C ) that obtains better than worst-case precision on programs with general-purpose pointer usage is presented with empirical results. The analysis consists of an algorithm schema corresponding to a family of MOD C algorithms with two independent phases: one for determining pointer-induced aliases and a subsequent one for propagating interprocedural side effects. These MOD C algorithms are parameterized by the aliasing method used. The empirical results compare the performance of two dissimilar MOD C algorithms: MOD C ( FSAlias ) uses a flow-sensitive, calling-context-sensitive interprocedural alias analysis; MOD C ( FIAlias uses a flow-insensitive, calling-context-insensitive alias analysis which is much faster, but less accurate. These two algorithms were profiled on 45 programs ranging in size from 250 to 30,000 lines of C code, and the results demonstrate dramatically the possible cost-precision trade-offs. This first comparative implementation of MOD C analyses offers insight into the differences between flow-/context-sensitive and flow-/context-insensitive analyses. The analysis cost versus precision trade-offs in side-effect information obtained are reported. The results show surprisingly that the precision of flow-sensitive side-effect analysis is not always prohibitive in cost, and that the precision of flow-insensitive analysis is substantially better than worst-case estimates and seems sufficient for certain applications. On average MOD C ( FSAlias ) for procedures and calls is in the range of 20% more precise than MOD C ( FIAlias ); however, the performance was found to be at least an order of magnitude slower than MOD C ( FIAlias ).

Precision and scalability are two desirable, yet often conflicting, features of data-flow analyses. This paper reports on a case study of the modification---ide-effects problem for C in the presence of pointers from the perspective of contrasting the flow and context sensitivity of the solution procedure with respect to precision and scalability. The results show that the cost of precision of flow- and context-sensitive analysis is not always prohibitive, and that the precision of flow- and context-insensitive analysis is substantially better than worst-case estimates and can be sufficient for certain applications. Program characteristics that affect the performance of data-flow analysis are identified.

Incremental static analysis seeks to efficiently update semantic information about an evolving software system, without recomputing “from scratch.” Interprocedural modification side effect analysis (MOD) calculates the set of variables possibly modified by execution of a procedure or a statement. We introduce a partial incrementalization of MOD for C systems using the hybrid method and present results of a study of 27 C programs, that predicts that our incremental MOD analysis will be substantially cheaper than exhaustive analysis for many program changes.

Test templates and a test template framework are introduced as useful concepts in specification-based testing. The framework can be defined using any model-based specification notation and used to derive tests from model-based specifications-in this paper, it is demonstrated using the Z notation. The framework formally defines test data sets and their relation to the operations in a specification and to other test data sets, providing structure to the testing process. Flexibility is preserved, so that many testing strategies can be used. Important application areas of the framework are discussed, including refinement of test data, regression testing, and test oracles.

A framework for specification-based testing is demonstrated on a symbol table case study, specified using the Z notation. Test derivation and structuring is discussed, as well as applications of the framework in deriving test oracles and aiding regressing testing during maintenance. Areas for further research and discussion are comparison of heuristics with regard to generated test suites and usability, formalising testing heuristics, and the discrepancy between functional testing and robustness testing.