Background. Industrial software increasingly relies on open source software. Its availability at no cost and its expected reliability make the use of open source software very appealing for industrial developers. However, even though the quality of open source software is generally believed to be high, given the variety of open source products and development projects, industrial practitioners need to evaluate the quality of a specific open source product they are considering for adoption. Automated tools greatly help assess open source software quality, by reducing the related cost. Automated tools do not provide perfectly reliable indications, but the results obtained can be used to restrict and focus manual code inspections, which are typically expensive and time-consuming, only on the code sections most likely to contain faults. Aim. We investigate the extent of the effectiveness of static analysis bug detectors by themselves and in combination with code smell detectors in guiding inspections. Method. We performed an empirical study, in which we used a bug detector (SpotBugs) and a code smell detector (JDeodorant). Results. Our results show that the selected bug detector is precise enough to justify inspecting the code it flags as possibly buggy. Applying the considered code smell detector makes predictions even more precise, but at the price of a rather low Recall. Conclusions. Though the limitations of our study do not allow us to draw universally valid conclusions, using the considered tools as inspection drivers appears to be quite useful.