Fault- and attack injection are techniques usedto measure dependability attributes of  omputer systems. Animportant property of such techniques is their efficiency inexploring the target system’s fault- or attack space. As this spaceis generally very large, pre-injection analysis techniques may beused to effectively explore the space. In this paper, we studytwo such techniques proposed in the past, namely inject-on-readand inject-on-write. Furthermore, we propose two new techniquescalled error space pruning of signals and error space pruning ofsignals and ports and evaluate their efficiency in reducing thespace needed to be explored by injection experiments. Thesetechniques were integrated into MODIFI, a fault- and attackinjector targeting Simulink models. To the best of our knowledge,we are the first to evaluate these pre-injection techniques for thiskind of injector.The results of our evaluation of 11 Simulink models from theautomotive domain and one from the avionics domain, show thatthe new proposed techniques reduce the fault- and attack spaceneeded to be explored by about 27–49%. Using MODIFI, we thenperformed injection experiments on two automotive models,  swell as an aero engine control model, while elaborating on theresults obtained.