Update user_guide.rst

doc/user_guide.rst

@@ -37,8 +37,7 @@ Memory management
     *C++* libraries expose in their interfaces either raw pointers, shared pointers or references, while *Python* handles memory allocation and garbage collection automatically.
     The concepts of pointer or references are thus not meaningful in *Python*.
     These language differences entail several problems in the memory management of *C++* components into *Python*.
-    Moreover the :code:`const` correctness which is a *C++* idiom doesn't exists in *Python*.
-    A special attention is therefore required for dealing with :code:`const` correctness, references (:code:`\&`) and pointers (:code:`*`) that are highly used in *C++*.
+    A special attention is therefore required for dealing with references (:code:`&`) and pointers (:code:`*`) that are highly used in *C++*.
 
 Error management
     *C++* exceptions need to be consistently managed in *Python*.
@@ -50,7 +49,7 @@ Error management
 Dependency management between components
     The management of multiple dependencies between *C++* libraries with *Python* bindings is required at run-time from *Python*.
     *C++* libraries tends to have dependencies.
-    For instance the *C++* **Standard Template Library** containers \citep{PLMS00} are used in many *C++* libraries (e.g :code:`std::vector`, :code:`std::set`).
+    For instance the *C++* **Standard Template Library** containers :cite:`PLMS00` are used in many *C++* libraries (e.g :code:`std::vector`, :code:`std::set`).
     For such cases, it doesn't seem relevant that every wrapped *C++* library contains wrappers for usual **STL** containers (e.g. :code:`std::vector< double >`, :code:`std::set< int >`).
     Moreover, loading in the *Python* interpreter multiple compiled libraries sharing different wrappers from same *C++* components could lead to serious side effects.
     It is therefore required that dependencies across different library bindings can be handled automatically.