M ODEL T RANSFORMATION T ESTING , T HE S TATE OF THE A RT Gehan - PowerPoint PPT Presentation

M ODEL T RANSFORMATION T ESTING , T HE S TATE OF THE A RT Gehan Selim, James Cordy, Juergen Dingel, Presented by: Lobna AbuSerrieh

I ION NT RODUCT Mo d e l Drive n De ve lo pme nt Mode l T ransformations Code 2

T ION C ORRE SS RANSF ORMAT CT NE F o rma l Me tho d s : He a vywe ig ht T e sting : - e xe c ute s a tra nsfo rma tio n o n input mo de ls the n va lida te s the a c tua l o utput ma tc he s the e xpe c te d o utput. - Auto ma ta b le te st a c tivitie s - L ig htwe ig ht, L o w c o mputa tio na l c o mple xity 3

P HASE S OF M ODE T ION T ING L RANSF ORMAT E ST 1. T e st Ca se Ge ne ra tion 2. T e st Suite Asse ssme nt 3. Building the Ora c le 4. E xe c ute a nd e va lua te 4

P HASE 1: T CASE GE ION E ST NE RAT  De fine te st a de q ua c y c rite ria , the n Build te st c a se s tha t a c hie ve s its c o ve ra g e . And it c a n b e do ne b y using : − Bla c k- Box te sting : b a se d o n tra nsfo rma tio n spe c ific a tio n. − a y- box te sting : b a se d o n the a c c e ssib le pa rts o f Gr tra nsfo rma tio n imple me nta tio n. − White - Box te sting : b a se d o n tra nsfo rma tio n imple me nta tio n 5

B L ACK - B OX T CASE GE ION E ST NE RAT M E L COVE RAGE T AMODE  Ad e q ua c y c rite ria fo r Cla ss d ia g ra ms − Asso c ia tio n e nd multiplic ity c rite rio n − Ge ne ra liza tio n c rite rio n − Cla ss a ttrib ute c rite rio n 6

B L ACK - B OX T CASE GE ION E ST NE RAT M E L COVE RAGE T AMODE  Ad e q ua c y c rite ria fo r Inte ra c tio n d ia g ra ms − E a c h me ssa g e o n a link − All me ssa g e pa th − Co lle c tio n c o ve ra g e − Co nditio n c o ve ra g e − F ull pre dic a te c o ve ra g e − T ra nsitio n c o ve ra g e 7

B L ACK - B OX T CASE GE ION E ST NE RAT M E L COVE RAGE T AMODE  Ad e q ua c y c rite ria fo r sta te c ha rts − F ull pre dic a te c o ve ra g e − All c o nte nt- de pe nde nc y re la tio nships − T ra nsitio n c o ve ra g e − tra nsitio n- pa ir c o ve ra g e − Co mple te se q ue nc e c o ve ra g e − All c o nfig ura tio ns tra nsitio n c o ve ra g e 8

B L ACK - B OX T CASE GE ION E ST NE RAT C ONT COVE RAGE RACT Ac hie ving input c o ntra c ts o f Mo de l tra nsfo rma tio n  Co nstruc ting me ta mo de l o f o nly tho se e le me nts a re a c tua lly use d in pre / po st c o nditio ns o f tra nsfo rma tio n  Co mb ine c o ntra c t-b a se d a nd me ta mo de l b a se d. And fo o tprints(numb e r o f time s te st mo de l c o ve rs e a c h c rite rio n). 9

W HIT E - B OX T CASE GE ION E ST NE RAT  Mo st o f the Studie s a re do ne witho ut c a se studie s a nd no de ta ile d re sults.  T ra nsfo rming rule s to a so urc e me ta mo de l te mpla te .  Asse ssing AT L rule s b y pro filing : 1. Co mpila tio n re sulte d XML file to e xtra c t the rule s. 2. T ra nsfo rma tio n to b e e xe c ute d. And using the re sulte d lo g file to a sse ss the c o ve ra g e (rule , instruc tio n, de c isio n).  Gra mma r te sting , E a c h rule to b e trig g e re d in e ve ry 10 po ssib le c o nte xt.

P HASE 2: T S UIT E A SSE E ST SSME NT  Ac hie ve d Co ve ra g e to a sse ss the te st suite q ua lity.  Muta tio n a na lysis, e va lua te the se nsitivity o f the te st c a se to fa ults in tra nsfo rma tio n.  Inje c ting fa ults b y a pplying muta tio n o pe ra to rs a nd g e ne ra te muta nts. − Diffe re nt re sults: K ille d muta nt. − No fa ults: the muta nt is a live 11

P HASE 3: B UIL DING T HE ORACL E F ION UNCT Co mpa re s T he a c tua l o utput with e xpe c te d o ne .  if the e xpe c te d o utput is a va ila b le , the n Co mpa re .  If it is no t a va ila b le , va lida te s the re sulte d o utput with the pre de fine d o utput pro pe rtie s o r c o ntra c ts 12

P HASE 3: B UIL DING T HE ORACL E F ION UNCT C OMPARISON if the e xpe c te d o utput is a va ila b le , the n Co mpa re : Test Case Constructor (Input Model, Expected Output, Transformation Strategy) Test Engine Execute, Compare Test Analyzer Visualize using colors and shapes A fra me wo rk use s Mo de l c o mpa riso n 13

P HASE 3: B UIL DING T HE ORACL E F ION UNCT C ONT S RACT If the e xpe c te d o utput is no t a va ila b le , va lida te s the re sult with the pre de fine d o utput pro pe rtie s o r c o ntra c ts.  T ra c ts, se t o f OCL c o nstra ints a nd a tra c t te st suite .  Impro ving T ra nsfo rma tio n c o ntra c ts: 1. Vig ila nc e : dyna mic a lly de te c t e rro rs 2. Dia g no sa b ility: e ffo rt to lo c a te a fa ult 14

P HASE 3: B UIL DING T HE ORACL E F ION UNCT C ONT S RACT  Vig ila nc e c a n b e impro ve d b y Ana lyzing a te st suit a nd re pe a te dly using muta tio n a na lysis, until a c hie ving a n a c c e pta b le muta tio n sc o re .  Othe r pro po se d a n impro ve d vig ila nc e a nd dia g no sa b iliy b y using ma the ma tic a l mo de ling . 15

Q UE IONS ST  Gra y-Bo x T e sting , is it fe a sib le to de pe nd o n pa rtia l imple me nta tio n while c o nside ring o the r pa rts a s b la c k b o x te sting ?  Cla ss dia g ra ms, sta te c ha rts, a nd se q ue nc e dia g ra ms a re the c o mmo n use d while te sting tra nsfo rma tio n, wha t a b o ut o the r type s o f dia g ra ms?  I s Mo de l c o mpa riso n a s o ra c le func tio n c le a r e no ug h?  Sinc e 2012 whe n this pa pe r wa s writte n, a nd ma ny re la te d studie s we re witho ut c a se studie s o r re lia b le re sults, a ny ne w upda te s we re a dde d to te sting MDT ? 16