Abstract  Design  level  class  cohesion  metrics  are  based  on  th e  assumption  that  if  all  the  methods  of  a  class  have  access  to  similar  parameter  types,  then  they  all  process  clos ely  related  information.  A  class  with  a  large  numbe r  of  parameter  types  common  in  its  methods  is  more  cohesive  than  a  class   with  less  number  of  parameter  types  common  in  its methods.  In  this  paper,  we  review  the  design  level  class  cohesion  me trics  with  a  special  focus  on  metrics  which  use  similarity  of  parameter  types  of  methods  of  a  class  as  the  basis  of  its  coh esiveness.  Basically  three  metrics  fall  in  this  category:  Cohesion  Among  Methods  of  a  Class  (CAMC),  Normalized  Hamming  Dista nce  (NHD),  and  Scaled  NHD  (SNHD).  Keeping  in  mind  t he  anomalies in the definitions of the existing metric s, a variant of the existing metrics is introduced.  It is named NHD Modified  (NHDM).  A  major  point  of  difference  is  that  the  NHD   metric  counts  a  disagreement  only  if  class  methods  taken  as  pairs  disagree  on  a  parameter  type  that  one  method  uses  b ut  the  other  method,  in  the  pair,  does  not  use.  It ignores  the  case  when  both  methods  of  a  pair  do  not  use  a  parameter  type.   NHD  indirectly  counts  it  as  an  agreement,  but  NHDM   considers  such  a  case  as  a  disagreement.  An  automated  metric  collect ion  tool  is  used  to  collect  the  metrics  data  from  an  open  source  Java  based software program containing 884 classes. Metr ics data is then subjected to statistical analysis. The NHDM metric shows  the  maximum  amount  of  variation  in  data  values  in  c omparison  to  other  metrics  in  the  group.  NHDM  is  st rongly  correlated  with CAMC. Unlike the previous studies, no signific ant correlation is found in CAMC and NHD.   

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