### Program Information

Name: Tot_info
Domain: Algorithm
Functionality: Printing the Kullbacks information measure, the degree of freedom and the possibility density of distribution of one table.
Input:
T: N tables(Type: Table)
Output:
For each table tiT, $I_i$: The Kullbacks information measure(Type: ?) $D_i$: The degree of freedom(Type: Integer) $Q_i$: the possibility density of distribution of one table(Type: ?)

#### Reference

Metamorphic slice: An application in spectrum-based fault localization http://dx.doi.org/10.1016/j.infsof.2012.08.008

### MR Information

#### MR1

Source input: $T_s$ ; Source output: $I^s_i,D^s_i,Q^s_i$
Follow-up input: $T_f$ ; Follow-up output: $I^f_i,D^f_i,Q^f_i$
Input relation: $T_f = T_s \cup T_s$
Output relation: $(tot_I)_f$ = $2 \times (tot_I)_s$, where $tot_I$ is the summaries of all $I_i$. $(tot_D)_f$ = $2 \times (tot_D)_s$, where $tot_D$ is the summaries of all $D_i$. $Q_f = Q_s$

#### MR2

Source input: $T_s$ ; Source output: $I^s_i,D^s_i,Q^s_i$
Follow-up input: $T_f$ ; Follow-up output: $I^f_i,D^f_i,Q^f_i$
Input relation: $R^f_i = 2 \times R^s_i$ $C^f_i = C^s_i$ where $R_i$ is the number of rows of $t_i$, $C_i$ is the number of columns of $t_i$ ,and the content from the ($R^s_i+1$)th row to the ($2 \times R^s_i$)th row in $t^f_i$ is the duplicate of its first $r^s_i$ rows.
Output relation: $I^f_i = 2 \times I^s_i$ $D^f_i = D^s_i + R^s_i \times (C^s_i - 1)$ $Q_f = Q_s$

#### MR3

Source input: $T_s$ ; Source output: $I^s_i,D^s_i,Q^s_i$
Follow-up input: $T_f$ ; Follow-up output: $I^f_i,D^f_i,Q^f_i$
Input relation: $T_f$ = Each element of $T_s$ multiplied by k.
Output relation: $I^f_i = k \times I^s_i$ $D^f_i = D^s_i$ $Q_f = Q_s$

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