  Simultaneously transmitting and reflecting \textcolor{black}{reconfigurable
intelligent surface} (STAR-RIS) is a promising implementation of RIS-assisted
systems that enables full-space coverage. However, STAR-RIS as well as
conventional RIS suffer from the double-fading effect. Thus, in this paper, we
propose the marriage of active RIS and STAR-RIS, denoted as ASTARS for massive
multiple-input multiple-output (mMIMO) systems, and we focus on the energy
splitting (ES) and mode switching (MS) protocols. Compared to prior literature,
we consider the impact of correlated fading, and we rely our analysis on the
two timescale protocol, being dependent on statistical channel state
information (CSI). On this ground, we propose a channel estimation method for
ASTARS with reduced overhead that accounts for its architecture. Next, we
derive a \textcolor{black}{closed-form expression} for the achievable sum-rate
for both types of users in the transmission and reflection regions in a unified
approach with significant practical advantages such as reduced complexity and
overhead, which result in a lower number of required iterations for convergence
compared to an alternating optimization (AO) approach. Notably, we maximize
simultaneously the amplitudes, the phase shifts, and the active amplifying
coefficients of the ASTARS by applying the projected gradient ascent method
(PGAM). Remarkably, the proposed optimization can be executed at every several
coherence intervals that reduces the processing burden considerably.
Simulations corroborate the analytical results, provide insight into the
effects of fundamental variables on the sum achievable SE, and present the
superiority of 16 ASTARS compared to passive STAR-RIS for a practical number of
surface elements.
