Analysis of Various Types of Bugs in the Object Oriented Java Script Language Coding

Transcription

1 Indian Journal of Science and Technology, Vol 8(21), DOI: /ijs/2015/v8i21/69958, Sepember 2015 ISSN (Prin) : ISSN (Online) : Analysis of Various Types of Bugs in he Objec Oriened Java Scrip Language Coding F. Fawzia Khan 1* and R. Mallika 2 1 Deparmen of Compuer Science, Karpagam Universiy, Coimbaore , Tamilnadu, India; fawziakhanphd@gmail.com 2 Deparmen of Compuer Science, CBM College, Coimbaore , Tamilnadu, India Absrac Objecive: The main goal of his work is o caegorize and undersand he various ypes of bugs presen in he Objec oriened java scriping language. By finding hese fauls one can find ou he naure of fauls which causes he run ime failure of programs. Mehods: There are various ypes of bugs presen in he OOJS environmen which needs o be caegorized well o undersand he naure of faul which has occurred in he OOJS language. By doing so, web pages can be prevened from he funcioning failure and can cause he generaion of more user flexible environmen. Faul Localizaion is he approach o analyse and deec he place of fauls presen in he java scriping language. Transducive Suppor Vecor Machine (TSVM) classificaion algorihm is inroduced o caegorize he fauls ino various sub ypes by classifying hem based on ypes of bugs. This classificaion is done on he bug repor daa se which was creaed by using he faul localizaion approach. Findings: The experimenal es conduced proves ha he proposed approach named TSVM based caegorizaion of fauls can deec he fauls efficienly which can be used furher for error deecion. The proposed approach improves in is performance in erms of improved accuracy deecion by caegorizing he fauls correcly hrough which fauls presen in he programming language can be done efficienly. Conclusion: From he findings i can be concluded ha he proposed approach improved in is performance in erms of improved accuracy. Keywords: Bug Repor, Faul Localizaion, Objec Oriened Java Scriping Language 1. Inroducion Objec Oriened Java Scrip is a scriping language which is used o provide a user ineracion form in a dynamic manner o he web pages for he cliens. The Objec oriened java scriping language is used o provide he user ineracion screen o he cliens o navigae and do some dynamic operaion over he nework. The Objec oriened java scrip language sricly differs from he java programming where he java is a real ime programming language. Whereas, he Objec oriened java scrip is a way o provide a logical communicaion o he web pages. Objec oriened java scrip canno be wrien direcly as he separae coding. I can only be wrien inside HTML language which enables he users who are accessing he corresponding web pages o download and view he Objec oriened java scrip conen. By doing so, a more flexible environmen can be creaed hrough which users can learn he informaion abou he web page which are accessed by some se of users. The Objec oriened java scriping language can be learned more quickly and efficienly. However a he ime of implemenaion i will be difficul o do he coding for creaion of web pages which needs more focus in order o avoid he failures of web page creaion. A he ime of creaion of web pages using he Objec oriened java scriping languages here are many facors o be considered in order o avoid many securiy issues. One of he securiy issues which migh possibly arise is corrupion of he files which are sored in he user file sysem. This occurs due o he web page access behaviour of he innocen users. The end user may open some of he web pages unaware of Objec oriened java scrip code exising in he corresponding HTML code. Generally Objec oriened java scrip code will sar o execue insanly a he ime of riggering he page. A he ime of riggering * Auhor for correspondence

2 Analysis of Various Types of Bugs in he Objec Oriened Java Scrip Language Coding he web page, Objec oriened java scrip can learn he informaion residing in he user file sysem. This needs o be prevened in order o avoid he user privacy violaion from he Objec oriened java scriping language. Anoher securiy issue which may arise due o Objec oriened java scriping language usage is ha he web page developers may be unaware of he advanced feaures presen in he Objec oriened java scriping language. Due o his siuaion here may be possibiliy of he occurrence of he bugs a he ime of program execuion. These bugs canno be analysed direcly because of hidden logical file races. These races need o be idenified locally in order o avoid he failure of he web pages execuion. The main conribuion of his work is o locae and analyse he ypes of bugs which arise in he Objec oriened java scriping language code creaion and preven from he web page failure during run ime. The idenified fauls have been classified in accordance o he faul caegories which can be used o idenify he behaviour and naure of he faul. I is done by gahering he various bug repors from differen web page developers. Afer gahering he bug repors, hose repors are analysed o find ou he races and i is caegorized as differen ypes of bugs. The organizaion of his work is given as follows: In secion 1 deailed descripion abou he inroducion of he Objec oriened java scrip language and he ypes of securiy issues which may arise in hem is discussed. In secion 2 previous researches has been discussed in a deailed manner o analyse he naure of fauls which has been deeced and analysed already. Secion 3 provides deailed descripion abou he proposed mehodology in his work wih he explanaion of he overall flow of his research. In secion 4 experimenal ess which has been conduced before has been discussed in a deailed manner. Finally in secion 5 resuls ha are obained are concluded in a manner of how i has improved in performance. In 1, bug generaions are found in he web applicaions in order o differeniae ypes of errors which can occur. I is done wih he help of es case generaion process and he explici sae model checking in which processing can be evaluaed wih he consideraion of various funcions and mehodologies ha are presen in he sysem. Differen ypes of es cases are generaed in order o evaluae he performance of he sofware in which various bug fields can be enumeraed. This is achieved by processing he various ypes of bugs and finding i over he web applicaions. In 2, a way o prioriize he bugs in erms of crash repor which has occurred in he differen scenarios is discussed. This is done by idenifying he ypes of bugs which happened in differen locaion in erms of various mehodologies. The prioriizaions of bugs are idenified wih he knowledge of he crashes which may happen due o he corresponding bug. This is done by analysing and inerpreing he various ypes of bugs ha happened in differen ypes of locaions in erms of various mehodologies. I is done by analysing and inerpreing he failure which happened in he sysem. In 3, disribuion of bugs presen in he paricular ype of sofware is idenified. I is inended o analyse he various ypes of bugs and he disribuion amoun of hose bugs in he sofware developmen environmen. I is done by considering he various parameers which can lead sofware o a failure mode due o large amoun of crashes presen in he sysem. I is done by considering he percenage of crashes ha occur in he sysem. This is achieved wih he help of disribuion funcion and he generaive model. I is overcome by he consideraion of various fields in which various ypes of bugs are disribued more. In 4, he concurren bugs are idenified in order o predic he decision which needs o be aken on hem o eliminae. I is done wih he help of finding he similariy presen among he various ypes of bugs which are presen in he nework. However i will be more difficul o idenify he concurren bugs, because of differen formas of bugs. I is done by achieving he similariy rerieval over he various ypes of bugs. This is done by finding he synchronizaion inenion presen among he differen bugs. To do so, invarian is idenified which is presen among he differen ypes of neworks. In 5,14, he bug repor can be creaed only by idenifying he differen ypes of bugs ha are presen in he sysem. I is done by considering he various ypes of bugs which is happening in he differen ypes of sysem. In his research, bug repors are creaed by localizing he faul and creae hem in accordance o he various fields. Faul localizaion is generally achieved by using he sofware esing and designing phase. And also idenified bugs are analysed and removed by using he approach called coincidenal correcness. I is done by analysing and idenifying he various ypes of fields. In 6, muliple ways for consrucing he sofware wihou error and consrucing he good base sofware is discussed. In his work, various sudies are conduced in erms of sofware availabiliy and he sofware requiremens ha are elicied. Efficien sofware can 2 Vol 8 (21) Sepember Indian Journal of Science and Technology

3 F. Fawzia Khan and R. Mallika be developed wih he help of uniqueness of sofware characerisics. Good sofware is differed from oher sofware in erm of is securiy level. Here securiy level is defined in erms of he sofware failure which will occur a he ime of sofware compilaion. And also, in his work, securiy level is divided ino wo levels and concenraed individually a he ime of sofware developmen. In 7, ways for building secure and reliable sofware wih he consideraion of he sofware developmen is discussed. Reliable sofware developmen can be obained wih he consideraion of he requiremens which are gahered from he differen phases in erms of previous hisory of similar ype of sofware. This analysis is done by he auhor in he produc which he has developed in his laboraory and he effeciveness is proved wih he consideraion of all ypes of securiy requiremens. This research resuls in an effecive way for consrucing he sofware wih more reliabiliy wihou sofware failure. In 8,13, a novel approach is inroduced o gaher he sofware requiremens from he various phases which inend o produce good qualiy sofware. Good qualiy sofware can be obained wih he consideraion of he complee sofware requiremens. However i is more difficul o gaher he sofware requiremens which are more relevan o he sofware which is ye o be developed. In his work, personal driven approach is inroduced which aims o saisfy he users wih he requiremens consideraion, which was gahered from hem. To achieve his user ineracion inerface is creaed which is named as he persona, and hrough which he user requiremens are gahered and processed effecively. In 9, an agile mehodology is inroduced o produce more secured sofware which can lead o a successful compleion of sofware developmen. The agile mehodology leads o a more effecive implemenaion of he sofware developmen which is based on he incremenal and ieraive sofware developmen. This mehodology will gaher he requiremens a each and every phase a he ime of sofware developmen in order o improve he sofware. The sofware developmen may lead o a successive ieraion of every cycle by gahering he requiremens based on he sofware developmen sage. In 10, a novel approach for gahering he requiremens in erms of reuse mehodology is discussed. A novel mehodology o gaher and process he requiremens in erms of he sofware developmen will be useful only for he corresponding sofware which is going o be developed whereas in his work, sofware is developed wih he consideraion of reuse mehodology. The requiremens gahered for he sofware developmen will be mainained in he daabase and hen i will be used furher for oher similar ypes of sofware. And also he characerisics of he curren sofware also will be gahered and sored in daabase o mainain good configurable sofware. 2. Objec Oriened Java Scrip Bug Analysis and Classificaion Objec oriened java scrip differs from he oher coding languages in wo ways 11. Those are absracion and encapsulaion. The absracion and encapsulaion process is defined as; he objec ha is creaed can be used o exrac he properies and mehods of he exernal objecs by inheriing hem. Mos Java Scrip libraries ha you can obain o make your java scrip coding easier uses Objec oriened java scrip wihin he library iself in order o make i easy for people o perform he asks ha he library is designed o provide. Absracion means ha once you sar using a library of objecs designed o perform given asks you no longer need o worry abou exacly how o perform hose asks wihou he library. You simply call he appropriae mehods for he appropriae objecs and he library does he res 12. The code wihin he objecs in he library is encapsulaed so ha he exac way in which hey implemen ha funcionaliy doesn affec he way you call i. The library auhors can rewrie code wihin he objecs in heir library and provided ha hey don change he public inerface you don need o change any of your code o use heir modified objecs. In his research differen ypes of bugs which have occurred in he Objec oriened java scrip programming language are aemped o be idenified and analysed. Objec oriened java scrip is a clien side scriping language which may consis of he various ypes of he funcions and modules o provide an advanced feaure for he creaion of he well-defined web pages. The bugs presen in he Objec oriened java scrip language may lead o a failure of web page creaion and will reduce he user s saisfacion level. Thus analysing of possible fauls which may arise in he Objec oriened java scrip language and classifying hem according o he faul caegories are more imporan in he case of real scenario. In his work his problem is resolved by inroducing he mehodology called he faul localizaion mehodology Vol 8 (21) Sepember Indian Journal of Science and Technology 3

4 Analysis of Various Types of Bugs in he Objec Oriened Java Scrip Language Coding which aims o analyse he number of fauls occurred in he Objec oriened java scriping language wih he deailed informaion of he faul and faul localizaion. Here, TSVM classificaion mehodology is inroduced which aims o classify he fauls based on is caegorizaion. TSVM is he classificaion mehodology which can able o classify he daa poins ha are parially labelled. TSVMs are basically ieraive algorihms ha gradually search he opimal separaing hyper plane in he feaure space wih a ransducive process ha incorporaes unlabeled samples in he raining phase. This procedure improves he generalizaion capabiliy of he classifier. Various ypes of faul caegories are analysed here. The ypes of faul caegories ha are assumed are: 2.1 Undefined/Null Variable Usage Trying o access an Objec oriened java scrip variable which has been no declared or declared wihou assignmen of values may lead o a bug. Tha is accessing objecs or mehods which have been defined wihou values. For example, rying o access a variable x using he propery bar, x.bar which is no been declared in he Objec oriened java scrip code. 2.2 Undefined Mehod As like previous undefined mehod bug will arise a he ime of accessing of mehods which has no been declared before in he Objec oriened java scrip code. For example rying o calling a mehod food() which has no been declared in he Objec oriened java scrip code. 2.3 Incorrec Mehod Parameer This ype of bug will arise a he ime of passing wrong values in o he mehods which is defined. The parameers ha are o be invoked will be defined a he ime of funcion declaraion. If i is done wrongly a he ime of funcion calling by sending wrong values, hen he bug will be creaed. For example, passing a sring value o he sedae() funcion insead of sending he ineger value which will lead o a failure of sofware execuion. 2.4 Incorrec Reurn Value If he values reurned are generaed wrongly due o some minor misakes exising in he logical programming, his ype of bug will be raised. 2.5 Synax-based Faul If he programming is done wihou following he synax rules defined in he Objec oriened java scriping language bin files, hen his ype of errors will occur. For example; insead of double quoaion we can use single quoaion o define a word. 2.6 Range based Faul This ype of faul will occur when he passing parameers values for he paricular aribues resides in arrange of values. Tha is varying of daa values based on he parameer range exiss among hem. 2.7 Incorrec Objec Suppor Defining or exracing he objecs which are no relevan o he concep of he mehods or funcions. The mehods and properies need o be defined properly. 2.8 Oher There are some errors occurred oher han he errors which are defined above. For example, he naming conflic presen among he funcion and aribues ha are defined. The above faul caegories are concenraed in his research for beer deecion of he bugs presen in he Objec oriened java scriping language. The bug deecion and classificaion algorihm is works as follows: Deec he place of errors exising in he Objec oriened java scriping language code. Localize he errors and hen analysing hem for deecing he reason for he occurrence of paricular faul. And hen find he source of faul by calling he funcion, in which he error has occurred. Then classifying he errors by using he TSVM machine learning algorihm Error Localizaion Firs he errors presen in he Objec oriened java scriping needs o be analysed in order o find he naure of faul which can cause he program execuion failure. This is done in wo seps: Error collecion. Error analysis. 4 Vol 8 (21) Sepember Indian Journal of Science and Technology

5 F. Fawzia Khan and R. Mallika These wo seps are followed o find he exac place where he error has occurred. In he error collecion phase, he errors in he Objec oriened java scriping coding will be analysed and idenified in an ieraive manner by execuing hem wih he minor changes. Afer collecion of he error evidences, hose errors will be analysed o know wha ype of errors has occurred and he naure of he evidences. These wo phases are discussed in deail in he following secion Error Collecion In he error collecion phase, he Objec oriened java scriping code will be analysed and searched o idenify he presence of error in he corresponding code. This is done by analysing he corresponding error presen in he Objec oriened java scrip. The error may be generaed a he ime of coding creaion which may lead o sofware failure. Thus every line of he code needs o be analysed a he ime of execuion of coding. The errors in he Objec oriened java scrip coding are colleced based on: The error line is presen in which funcion; The funcion o which he corresponding line number belongs o; Variable and funcions in he error lines; The previous values of he corresponding variable, in he previous execuion. Afer collecing hese errors which are presen in he Objec oriened java scriping language, he naure of errors will be idenified and he reason behind hose errors occurrences will be idenified. By doing so, he synchronous errors presen in he Objec oriened java scriping coding will also be idenified Error Analysis Afer collecion of errors and is locaion in he Objec oriened java scrip code, he analysis of he errors will be done o idenify he naure and behaviour of he errors. By doing so, he documen Objec model access which is responsible for he corresponding error in he Objec oriened java scriping will be idenified. Tha is, roo and source of he bug will be idenified and hen i will be analysed for he fuure prevenion from bugs. This is done by analysing he exac par of he coding which is responsible for he failure of he web page creaion, by segmenaion of he Objec oriened java scrip error code ino pariions. Afer segmenaion of errors in o he pariions, he relevan feaures will be idenified by looking for he DOM access conrol. Iniially, errors will be analysed in he documen by using an error marker and will ake an error as an even. The error will always be observed in he relevan sequence, since he program will be haled once he error occurs. Tha is, in his phase, he sequence of evens which are reason for he corresponding bug will be idenified in order o analyse and remove hem for providing he convenien environmen for he users. The corresponding errors will be analysed for he removal of such noise, hus he efficien and bug avoided Objec oriened java scriping can be implemened. Afer his process, he idenified bugs from he various modules and funcions will be caegorized and learned for he fuure use which can be used o avoid he same ype of failure a he ime of projec execuion Failure Caegorizaion Afer analysis of differen ypes of bugs presen in he Objec oriened java scriping language, he idenified bugs will be caegorized in accordance o he ypes of fauls which was discussed in he previous secion. This classificaion is done by using he classificaion algorihm called Transducive Suppor Vecor Machine which aims o classify he bugs ha are idenified based on heir ype and naure. This TSVM algorihm is used o avoid he convergence problem which may occur due o he large volume of daa. TSVM is he ieraive algorihm which aims o cover he unlabelled daa presen in search space wih he help of ransducive funcion by separaing he hyper plane opimally. In he raining phase of he TSVM, unlabelled daa will be considered for he classificaion. Tha is he bugs wihou label will be considered in he raining phase for he beer classificaion process. By using he TSVM mehodology, beer generalizaion capabiliy of he classifier can be achieved. Also, his mehodology aims o move he hyper plane gradually based on reaching a finer place. This mehodology aims o achieve a finer place by achieving he generalizaion capabiliy of he classifier. A finer hyper place posiion can be achieved by ieraively doing his mechanism. In his approach, beer Vol 8 (21) Sepember Indian Journal of Science and Technology 5

6 Analysis of Various Types of Bugs in he Objec Oriened Java Scrip Language Coding classificaion can be achieved by migraion of he daa ino he class labels which preend o avoid he misclassificaion of he daa by avoiding he discriminae funcions. This mechanism also aims o provide more accurae resuls han he exising mehodology. The convergence of he caegorizaion depends on he similariy presen among he differen class labels. The designing of TSVM for he faul caegorizaion is done in wo ways and i addresses wo issues. Those are: Selec he bugs wih he expeced accurae labelling. Choose he informaive knowledge source abou he Objec oriened java scrip bug. TSVM selecs he margin of he classificaion of bug samples by accuraely idenifying he upper and lower side of he samples by analysing and checking he following condiions. Those are, if P 1 (ie., falls below or above he hyper plane region will be idenified), hen he ransducive samples of bugs closes o he margin bounds will be assigned as class labels as +1 or -1 respecively. Else labelling will be done any way wihou any consideraion. A dynamic adjusmen is necessary, aking ino accoun ha he posiion of he hyper plane keeps changing a he ieraion. Typically, he mos confiden unlabelled paerns, ogeher wih heir prediced labels, are added o he curren raining se. The classifier is rerained and he process is repeaed. I is o be noed ha he classifier uses is own predicion o each iself. I is naural o imagine ha a classificaion error can reinforce iself. Therefore, i is imporan o ake a cauion in he selecion of ransducive samples because wrong labelling may subsanially degrade he performance of he classifier. Due o he fac ha suppor vecors conain he riches informaion among he informaive samples (i.e., he ones in he margin band), he unlabelled paerns closes o he margin bounds have he highes probabiliy o be correcly classified. Therefore, in he proposed approach, we design a selecion procedure (i.e., filering process) o increase he accepabiliy of he samples wih he expeced correc labelling. In oher words, an unlabelled sample should be considered as ransducive sample if he TSVM ensemble assigns he same label o i. We can expec his sample bearing he informaion wih an expeced accurae class label Oupu TSVM classifier wih original raining se and he ransducive se Begin 1. Iniialize he working se W (0) = S, previous ransducive (0) se A = f and specify C and C *. 2. Train SVM classifier wih he working se W (0). 3. Obain he label vecor of he unlabeled se V. For i = 1 o T // T is he number of ieraions. 4. Selec N+ posiive ransducive samples from he upper side of he margin and N negaive ransducive samples from he lower side respecively. 5. Selec posiive candidae se B+ conaining N+ posiive ransducive samples and negaive candidae se B conaining N negaive ransducive samples respecively. 6. (i) + - B = B È B 7. Updae he raining se: A = f W(i) = W È B (i-1) (i-1) (i) If (i) D = B Else End if (i) (i) D = A(i-1) Ç B(i) W = (W -D ) È D (i) (i-1) (i-1) (i) 8. (i) (i) A = B 9. Train TSVM classifier wih he updaed raining se W (i). 10. Obain he label vecor of he unlabelled se V. End for, End, The above classificaion algorihm is used o resul he caegorizaion of he failures due o bugs based on he faul ypes. Thus wih he knowledge of his algorihm one can analyse he deecion of bug ha are presen in he Objec oriened java scriping language coding easily. Finally, experimenal ess has been conduced o analyse he ypes of bugs have been presen in he Objec oriened java scriping language is prediced correcly or no Algorihm Inpu Labelled poins: S = [(x j, y j )], j = 1, 2,..., l and unlabelled poins: V = [(x j )], j = l + 1,..., n. Vol 8 (21) Sepember Experimenal Resuls The experimenal es has been conduced o compare he effeciveness of he algorihm in order prove he Indian Journal of Science and Technology

7 F. Fawzia Khan and R. Mallika improvemen in he proposed research han he exising research named AUTOFLOX which aims o localize he fauls ha are occurring in he Java Scrip language auomaically. The comparison is done based on he performance merics called he precision and he recall measures. In his work, Objec oriened java scrip based bug repors have been colleced from he various web page developer which consiss of deails abou he various ypes of bugs which may occur in he differen siuaions. By analysing he bug repor, he Objec oriened java scrip bug repor predicion is done and he ypes of fauls are caegorized. The ypes of bug which are presen in he Objec oriened java scrip coding has been classified in accordance o he naure of he bugs. The comparison based on hese performance merics are explained in he following secions: 3.1 True Posiive Rae (TP) I is he amoun of correc fauls ha are classified o correc class. d TP= c + d of bug repor creaion based on he rue posiive and he false posiive informaion. The equaion o calculae he precision value is defined as follows: The able ha liss he acual precision values ha are obained while processing he java scriping bug corpus is given in Table 1. True posiive Precision= True posiive+false posiive Table 1. Precision values Number PRECISION of bugs AUTOFLOX TSVM The comparison of precision value beween proposed sysem and he exising sysem are shown in he following graph: 3.2 False Posiive Rae (FP) I is he amoun of negaive fauls ha are classified ino correc class o which i does no belong o: b FP= a + d 3.3 False Negaive Rae (FN) I is he amoun of negaive fauls ha are classified o wrong class. c FN= c + d Figure 1. Precision comparison. Where, a is he number of correc predicions ha an insance is negaive. b is he number of incorrec predicions ha an insance is posiive. c is he number of incorrec of predicions ha an insance negaive. d is he number of correc predicions ha an insance is posiive. These are all he measures which are used o calculae he accuracy values Precision Precision value is used o indicae he successful predicion From he Figure 1, i is proved ha he precision obained in he exising work is lower han he proposed mehodology. In x axis, he number of bugs ha are analyzed are aken and in y axis precision value is considered Recall Recall value is calculaed based on he successful predicion a rue posiive predicion and false negaive. Recall value is calculaed by using he following equaion: The able ha liss he acual recall values ha are obained while processing he java scriping bug corpus is given in Table 2. Vol 8 (21) Sepember Indian Journal of Science and Technology 7

8 Analysis of Various Types of Bugs in he Objec Oriened Java Scrip Language Coding True posiive Recall= True posiive+false negaive Table 2. Recall values Number of bugs RECALL AUTOFLOX TSVM The comparison graph for recall value is depiced in he Figure 2. inroduced which aims o predic and classify he bugs ha are presen in he Objec oriened java scriping code based on he naure and behaviour of he bugs. In our work, six ypes of bugs have been considered for he effecive caegorizaion of he bugs ha are presen in he documen. The finding of his work demonsraes ha he proposed mehodology can lead o an efficien predicion of he bugs and heir classificaion which provides a convenien way for he web page developers o avoid he bugs during run ime. In he fuure scenario, auomaic classificaion of bugs occurring can be inroduced hrough which he ime complexiy can be reduced considerably. The various prospecs of he java scrip language need o be concerned more for supporing he higher echnology sofware. 5. References Figure 2. Recall comparison. Form he Figure 2 i is proved ha he recall value obained in he exising work is lower han he proposed mehodology. In x axis, he number of bugs ha are analyzed are aken and in y axis recall value is considered. From his analysis i can be proved ha he proposed mehodology can idenify he fauls accuraely han he exising approaches from which i has been proved ha he proposed approach provides 70% improvemen han he AUTOFLOX approach. 4. Conclusion and Fuure Work Objec oriened java scrip bug handling is he mos complex process in he real world web page developmen environmen. The small errors which arise during developmen of he clien side programming may lead o he enire corrupion of he execuion of he coding. Finding of bugs in he Objec oriened java scrip coding will also be more complex process due o he small logical errors which canno be idenified. In his work, faul localizaion and he faul caegorizaion mehodology is 1. Arzi S, Kie_zun A, Dolby J, Tip F, Dig D, Paradkar A, Erns MD. Finding bugs in web applicaions using dynamic es generaion and explici-sae model checking. IEEE Trans Sofware Eng July-Aug; 36(4): Kim D, Wang X, Kim S, Zeller A, Cheung SC, Park S. Which crashes should I fix firs?: Predicing op crashes a an early sage o prioriize debugging effors. IEEE Trans Sofware Eng May-June; 37(3): Concas G, Marchesi M, Murgia A, Tonelli R, Turnu I. On he disribuion of bugs in he eclipse sysem. IEEE Trans Sofware Eng Nov-Dec; 37(6): Lu S, Park S, Zhou Y. Deecing concurrency bugs from he perspecives of synchronizaion inenions. IEEE Trans Paralell Disr Sys June; 23(6): Zhang Z, Chan WK, Tse TH. Faul localizaion based only on failed runs. IEEE Compuer Sociey. 2012; 45(6): McGraw Gary. Building secure sofware: Beer han proecing bad sofware. IEEE Sofware Dec 16; 19(6): Fichinger B, Paulisch F, Panholzer P. Driving secure sofware developmen experiences in a diverse produc environmen. IEEE Compuer and Reliabiliy Socieies March-April; 10(2): Cleland-Huang J. Mee elaine: A persona driven approach o exploring archiecurally significan requiremens. IEEE Sofware, IEEE Compuer Sociey. 2013; ben Ohmane L, Angin P, Weffers H, Bhargava B. Exending he agile developmen approach o develop accepably secure sofware. Journal of IEEE Transacions on Dependable and Secure Compuing. 2014; 11(6): Hermoye LA, van Lamsweerde A, Perry DE. A reuse-based approach o securiy requiremens engineering. Proceedings of 9h Inernaional Workshop on Requiremens Engineering: Foundaion for Sofware Qualiy (REFSQ 03); Vol 8 (21) Sepember Indian Journal of Science and Technology

9 F. Fawzia Khan and R. Mallika 11. Arzi S, Dolby J, Jensen S, Moller A, Tip F. A framework for auomaed esing of java scrip web applicaions. ACM in Inernaional Conference on Sofware Engineering (ICSE); p Ocariza F, Paabiraman K, Zorn B. Java Scrip errors in he wild: An empirical sudy. Proceedings of Inernaional Symposium on Sofware Reliabiliy Engineering (ISSRE). IEEE Compuer Sociey; Hiroshima Nov 29-Dec 2. p Groeneveld F, Mesbah A, van Deursen A. Auomaic invarian deecion in dynamic web applicaions. Delf Universiy of Technology. Tech Rep; Zheng Y, Bao T, Zhang X. Saically locaing web applicaion bugs caused by asynchronous calls. Inernaional Conference on he World-Wide Web (WWW), ACM; p Vol 8 (21) Sepember Indian Journal of Science and Technology 9