Using the Ito's formula I have shown that $X_t$ is a local martingale, because $dX_t=\dots dB_t$, where
$$X_t = (B_t+t)\exp\left(-B_t-\frac{t}{2}\right),$$ $B_t$ - is a standard Brownian motion
I would like to show it is a true martingale, so I am looking at these sets:
$$\mathcal{S}_1:=\{ X^{T_n}_t : n\geq 1\} \text{ or }\mathcal{S}_2:=\{X_T : \text{ T is a bounded stopping time} \}$$ And trying to show that either of them is UI. ($T_n$ are the stopping times reducing $X_t$)
I need some help with this step.
Edit
This is a homework exercise, which stipulates the usage of Ito's formula
let $f(x,t):= \exp{(-(x+t))}(x+t)$, then we are allowed to apply Itô's formula. We just need to calculate the following derivatives: $\frac{\partial f}{\partial x},\frac{\partial f}{\partial t},\frac{\partial^2 f}{\partial t^2}$ since the second component of $f$ is continuous and increasing, thus has finite variation and any continuous function of finite variation has zero quadratic variation (and you have to use Cauchy-Schwarz.)
Here's what I get:
$\frac{\partial f}{\partial x} = \exp{(-(x+t))}-\exp{(-(x+t))}(t+x)$
$\frac{\partial f}{\partial t} = \exp{(-(x+t))}-\frac{1}{2}\exp{(-(x+t))}(t+x)$
$\frac{\partial^2 f}{\partial t^2} = -2\exp{(-(x+t))}+\exp{(-(x+t))}(t+x)$
Therefore:
$f(B_s,t)=\int_0^t{[\exp{(-(B_s+s))}-\exp{(-(B_s+s))}(s+B_s)]dB_s}\\ + \int_0^t{[\exp{(-(B_s+s))}-\frac{1}{2}\exp{(-(B_s+s))}(s+B_s)]}ds +\int_0^t{[-\exp{(-(B_s+s))}+\frac{1}{2}\exp{(-(B_s+s))}(s+B_s)]d\langle B_s,B_s\rangle}= \int_0^t{[\exp{(-(B_s+s))}-\exp{(-(B_s+s))}(s+B_s)]dB_s}\\ + \int_0^t{[\exp{(-(B_s+s))}-\frac{1}{2}\exp{(-(B_s+s))}(s+B_s)]}ds +\int_0^t{[-\exp{(-(B_s+s))}+\frac{1}{2}\exp{(-(B_s+s))}(s+B_s)]ds}$
Comparing the $ds$ integral, this leads to:
$$f(B_s,t)=\int_0^t{[\exp{(-(B_s+s))}-\exp{(-(B_s+s))}(s+B_s)]dB_s}$$
Now I use the following Theorem, which can be found on this exercise sheet, Exercise 1a): http://www.math.ethz.ch/%7Egruppe3/HS11/MFF/MFF_2011_exercise08.pdf
And apply it to $M_t = B_t$ and $H_s=\exp{(-(B_s+s))}-\exp{(-(B_s+s))}(s+B_s)$
cheers
math