The quest for increased performance at lower energy consumption rates, especially in embedded systems used in smart systems, has reached physical limits that can no longer be exploited using traditional optimization techniques. One popular way to achieve additional gains is to intentionally perform inaccurate computations. Our framework eases evaluation, analysis and comparison of approximation techniques in terms of energy consumption, run time, quality and user-defined criteria. Applied to a set of benchmarks, we obtain valuable insights into related side effects, including increased file sizes indicating that a careless utilization of approximate computing threatens its usefulness.