By running the life tests at higher stress levels than normal operating conditions, accelerated life testing (ALT) quickly yields information on the lifetime distribution of a test unit. The lifetime at the design
stress is then estimated through extrapolation using a regression model. In the first part of this talk, a step-stress ALT is considered for progressively Type-I censored exponential failure data with equal step duration. For small to moderate sample sizes, a practical modification is suggested to the censoring scheme in order to guarantee a feasible test, and the optimal step duration is determined under C-optimality, D-optimality, and A-optimality criteria. In the second part of the talk, the optimal constant-stress and step-stress ALTs are compared under complete sampling and Type-I censoring. The efficiency of step-stress ALT relative to constant-stress ALT is discussed in terms of the ratio of optimal objective functions based on the Fisher information matrix.