`Name:`

Tot_info `Domain:`

Algorithm `Functionality:`

Given a test case have $n$ tables $T_s=\{t^s_1,t^s_2,\ldots ,t^s_n\}$.For each table $t^s_i \in T_s$,tot_info prints $(info)^s_i,(df)^s_i$ and $q^s_i$,where $(info)^s_i,(df)^s_i$ and $q^s_i$ denote the Kullbacks information measure,the degree of freedom and the possibility density of $\chi^2$ distribution of $t^s_i$,respectively.In addition, tot_info prints $(tot\_info)^s,(tot\_df)^s$ and $(df)^s_i$,respectively,and $q^s$ is the possibility density of $\chi^2$ distribution calculated with $(tot\_info)^s$ and $(tot\_df)^s$ `Input:`

Given a source test case have $n$ tables $T_s=\{t^s_1,t^s_2,\ldots ,t^s_n\}$.And denote the $m$ tables in the follow-up test case as $T_f=\{t^f_1,t^f_2,\ldots ,t^f_m\}$ `Output:`

For $t_s$, the printed results are denoted as $(info)^s_i,(df)^s_i,q^s_i,(tot\_info)^s,(tot\_df)^s,q^s$;
For $t_f$, the printed results are denoted as $(info)^f_i,(df)^f_i,q^f_i,(tot\_info)^f,(tot\_df)^f$ and $q^f$.
Metamorphic slice: An application in spectrum-based fault localization https://doi.org/10.1016/j.infsof.2012.08.008

`Description:`

`Property:`

$T^f$ is constructed by duplicating all $t^i_s \in T_s$,that is,$T_f=T_s \cup T_s$ $\Rightarrow$ $(tot\_info)_f = 2*(tot\_info)_s$ and $(tot\_df)_f = 2*(tot\_df)_s$ `Source input:`

$T^s$ `Source output:`

$(info)^s_i,(df)^s_i,q^s_i,(tot\_info)^s,(tot\_df)^s,q^s$ `Follow-up input:`

$T^f$ `Follow-up output:`

$(info)^f_i,(df)^f_i,q^f_i,(tot\_info)^f,(tot\_df)^f,q^f$ `Input relation:`

$T^f$ is constructed by duplicating all $t^i_s \in T_s$,that is,$T_f=T_s \cup T_s$ `Output relation:`

$(tot\_info)_f = 2*(tot\_info)_s$ and $(tot\_df)_f = 2*(tot\_df)_s$ `Pattern:`

`Description:`

For an arbitrarily chosen table $t^s_i \in T_s$,suppose $t^s_i$ has $r^s_i$ rows and $c^s_i$ columns.In $T_f,t^f_i$ is defined to have $r^f_i$ rows and $c^f_i$ columns. `Property:`

$r^f_i=2*r^s_i$ and $c^f_i=c^s_i$,the content from the $(r^s_i+1)$th row to the $(2*r^s_i)$th row in $t^f_i$ is the duplicate of its first $r^s_i$ rows. $\Rightarrow$ $(info)^f_i=2*(info)^f_i$ and $(df)^f_i=(df)^s_i+r^s_i*(c^s_i-1)$ `Source input:`

$T^s$ `Source output:`

$(info)^s_i,(df)^s_i,q^s_i,(tot\_info)^s,(tot\_df)^s,q^s$ `Follow-up input:`

$T^f$ `Follow-up output:`

$(info)^f_i,(df)^f_i,q^f_i,(tot\_info)^f,(tot\_df)^f,q^f$ `Input relation:`

$r^f_i=2*r^s_i$ and $c^f_i=c^s_i$ `Output relation:`

$(info)^f_i=2*(info)^f_i$ and $(df)^f_i=(df)^s_i+r^s_i*(c^s_i-1)$ `Pattern:`

`Description:`

`Property:`

$T_f$ is constructed by defining $t^f_i$ such that each value in $t^f_i$ is the corresponding value in $t^f_i$ multiplied by $k$ $\Rightarrow$ $(info)^f_i=k*(info)^s_i$ and $(df)^f_i=(df)^s_i$ `Source input:`

$T^s$ `Source output:`

$(info)^s_i,(df)^s_i,q^s_i,(tot\_info)^s,(tot\_df)^s,q^s$ `Follow-up input:`

$T^f$ `Follow-up output:`

$(info)^f_i,(df)^f_i,q^f_i,(tot\_info)^f,(tot\_df)^f,q^f$ `Input relation:`

$T_f$ is constructed by defining $t^f_i$ such that each value in $t^f_i$ is the corresponding value in $t^f_i$ multiplied by $k$ `Output relation:`

$(info)^f_i=k*(info)^s_i$ and $(df)^f_i=(df)^s_i$ `Pattern:`