Let's take as example the following system:
$ \begin{cases} 2x + 1 = 0 \\ -x + 1 = 0 \end{cases} $
I could take x from the first and check on the second which will give me no solution. Taking from one and replacing in other guarantees safety
But if I add them together I will get x + 2 = 0 => x = -2. Checking -2 will fail in both of them. More solutions than needed are shown, and for advanced problems is not easy if possible at all to check the solutions
a = 2, b = 3 => a + b = 5, but a + b = 5 does not mean a = 2, b = 3. Even if there are the same number of equations as the number of variables, since they are on the same domain, I guess some dirty tricks can be applied so the system does not result only true solutions
What rules shall be applied to the system in order to guarantee valid solutions?
Example (please mention the mistake):
We have 2 quadratric equations f(x) and g(x). By using f(x) = g(x) we get all x coordinates of the intersection points. Let's say we want to get all point with y = 2:
$ \begin{cases} f(x) = 2 \\ g(x) = 2 \end{cases} $
The system results f(x) = g(x) or f(x) - g(x) = 0, and we said earlier that this means we get all intersection points, contrary to our rule of y = 2. In a real example we may have $f(x) = x^2 + mx + 1$ (m parameter) and some conditions that our f shall accomplish (so we can determine m). Since the system will not result only true solutions, then the method is quite useless and other ways shall be taken
For linear equations (such as in the first example) you need to look at how many conditions you apply over how many parameters are in question: in your example you impose 2 different conditions on x (has to equal both 1 and -1/2), therefore there is no solution. Generally speaking you can have one of three outcomes: 1. if the number of parameters exceed the number of conditions you will have infinite solutions. 2. if the number of parameters is exactly the same as the number of conditions you have a single solution. 3. otherwise there is no solution (as in your example). If you studied linear algebra - that has to do with the rank of the matrix involved.