Architecture Evolution

Transcription

1 2IMP25 Software Evoluton Archtecture Evoluton Alexander Serebrenk

2 Announcements Remnder Assgnment 1 deadlne: Feb 19, 23:59. Do not wat tll 23:58 Guest lecture by Prof Vnju postponed to Feb 24. / SET / W&I 17/02/16 PAGE 2

3 Sources Archtecture reconstructon sldes Raner Koschke (n German) lehredetals.php?d=3&lehre_d=309 / SET / W&I 17/02/16 PAGE 3

4 Where are we now? Last tme: requrements Ths week: archtecture [IEEE Std ] Software archtecture s the fundamental organzaton of a system emboded n ts components, ther relatonshps to each other and to the envronment, and the prncples gudng ts desgn and evoluton. / SET / W&I 17/02/16 PAGE 4

5 Components? Relatons? Many vews: Kruchten s 4+1 Semens Zachman Perry and Wolf Clements et al. / SET / W&I 17/02/16 PAGE 5 M: module: statc structure decomposton use generalzaton layers CC: component & connectors: runtme structure ppe and flter shared data publsh and subscrbe clent server peer-to-peer communcatng processes A: allocaton: embeddng n organzatonal development context deployment mplementaton work assgnment

6 Archtecture As ntended evoluton As descrbed Archtecture Descrpton Languages Should express dfferent vews As mplemented Code, deployment evoluton From code to archtecture: reverse engneerng Should extract dfferent vews / SET / W&I 17/02/16 PAGE 6

7 Reverse Engneerng [Chkofsky, Cross II 1990] Reverse Engneerng s the process of analyzng a subject system to dentfy the system s components and ther nterrelatonshps and create representatons of the system n another form or a hgher level of abstracton. Reverse engneerng: dfferent meanngs / SET / W&I 17/02/16 PAGE 7

8 Our Reverse Engneerng [Koschke 2008] Archtecture reconstructon s the process of analyzng a subject system to reconstruct archtectural vews. Dfferent vews requre dfferent archtecture reconstructon technques! No slver bullets! / SET / W&I 17/02/16 PAGE 8

9 How can we choose the rght AR approach? GQ(V)M! Goals: What problem does the AR try to solve? Ex.: Changes affect too many modules Goal: Assess and mprove current modularsaton Questons: What do we need to know to acheve the goal? What are the dependences between the modules? How can one mprove the modularsaton? Vews: Whch vews are needed to answer the questons? Module-Use Vews: as-s + mproved Metrcs: How can we quantfy the answers? Number of dependences between the modules, / SET / W&I 17/02/16 PAGE 9

10 Archtecture Reconstructon UML UML De facto standard archtecture descrpton language Varous dagrams correspondng to dfferent vews Structure: Class dagrams, package dagrams Behavour: Today Sequence dagrams, state machnes, actvty dagrams AR s mplemented n many commercal, opensource and academc tools Assgnment CPP2XMI, I2SD / SET / W&I 17/02/16 PAGE 10

11 AR: Class dagrams Basc dea mport java.utl.*; class User { nt usercode; Strng fullname; statc nt nextcodeav = 0; publc User(Strng name) { fullname = Name; usercode = User.nextCodeAv++; } User usercode: nt fullname: Strng nextcodeav: nt User(Strng name) getcode(): nt } publc nt getcode() { return usercode; } Do not draw the lbrary classes / SET / W&I 17/02/16 PAGE 11

12 What about the relatonshps? Relatonshps Code Tonella, Potrch 2005 Assocaton / aggregaton class A { B b; } A B Dependency class A { vod f(b b) {b.g(); } } A B class A { vod f() {B b; b.g();} } Generalzaton A B Realzaton A B class A extends B { } class A mplements B { } / SET / W&I 17/02/16 PAGE 12

13 Lbrary example Lbrary Tonella, Potrch 2005 Loan user loan document User Document InternalUser Journal Book TechReport Looks strange No relatons between the lbrary, ts documents and ts users? / SET / W&I 17/02/16 PAGE 13

14 What s gong on? class Lbrary { Map documents = new HashMap(); Map users = new HashMap(); Collecton loans = new LnkedLst(); } publc boolean adduser(user user) { f (!users.contansvalue(user)) { users.put( new Integer( user.getcode()), user); return true; } return false; } Relaton between Lbrary and Map/Collecton Not drawn: lbrary classes Contaners are weakly typed Collect objects of the type that s not yet declared Relaton between Lbrary and User s mssed / SET / W&I 17/02/16 PAGE 14

15 What do we need? Flow of nformaton about objects creaton by allocaton statements, assgnment to varables, storage n class felds, usage n method nvocatons Data-flow analyss We need a data structure to propagate the nformaton n It should represent relatons between objects Both backward and forward propagaton ( n) / SET / W&I 17/02/16 PAGE 15 ( n) = n( n) gen( n) kll( n) out \ ( n) ( p) = out of p succ n ( n) = p pred ( n) out ( p)

16 Data-flow analyss Recall: We need a data structure to propagate the nformaton It should represent relatons between objects Soluton: Object Flow Graph Vertces: varables, felds, method parameters (everythng that can store data) Edges: represent data flow (see next slde) / SET / W&I 17/02/16 PAGE 16

17 Basc dea: Object Flow Graph Vertces: varables, x = y felds, method parameters, method nvocatons y x and returns x = y.m(a 1,, a k ) Method m(f 1,, f k ) y m.ths a 1 f 1 a k f k m.return x x = new c(a 1,, a k ) cs constructor of c a 1 f 1 a k f k cs.ths x / SET / W&I 17/02/16 PAGE 17

18 Example: Object Flow Graph publc boolean borrowdocument(user user, Document doc) { f (user == null doc == null) return false; f (user.numberofloans() < MAX_NUMBER_OF_LOANS && doc.savalable() && doc.authorzedloan(user)) { Loan loan = new Loan(user, doc); addloan(loan); return true; } return false; } Lbrary.borrowDocument.user User.numberOfLoans.ths Loan.Loan.usr / SET / W&I 17/02/16 PAGE 18 Document.authorzedLoan.user

19 Example: Object Flow Graph publc boolean borrowdocument(user user, Document doc) { f (user == null doc == null) return false; f (user.numberofloans() < MAX_NUMBER_OF_LOANS && doc.savalable() && doc.authorzedloan(user)) { } Loan loan = new Loan(user, doc); addloan(loan); return true; } return false; Loan.Loan.ths Lbrary.borrowDocument.loan Control-flow s gnored Felds, parameters and methods are encoded wth fully qualfed names Lbrary.addLoan.loan / SET / W&I 17/02/16 PAGE 19

20 Queston Does the path n the OFG always correspond to a possble executon? Loan.Loan.ths f (user!= null) Loan loan = new Loan(user, doc); f (user == null) addloan(loan); Lbrary.borrowDocument.loan Lbrary.addLoan.loan Ths approach s conservatve (safe): no path n the Object Flow Graph no executon can produce the flow path n the Object Flow Graph??? / SET / W&I 17/02/16 PAGE 20

21 How can we use our graphs? Problem: declared type actual type Subclasses and mplemented nterfaces Inhertance from a lbrary superclass/nterface s not vsble n a class dagram! In general: undecdable, we try our best For any x = new c node record c: Propagate ths nformaton through the graph: From creaton to use (forward) ( cs. ths) { c} gen = / SET / W&I 17/02/16 PAGE 21

22 Example gen(student.student.ths) = {Student} Student.Student.ths out(student.student.ths) 1 = {Student} UA.man.s out(ua.man.s) 2 = {Student} UA.addStudent.s out(ua.addstudent.s) 3 = {Student} BTN.BTN.x out(btn.btn.x) 4 = {Student} BTN.obj out(btn.obj) = {Student} / SET / W&I 17/02/16 PAGE 22

23 Example class BnaryTreeNode { BnaryTreeNode left, rght; Comparable obj; } publc BnaryTreeNode (Comparable x) { 4 obj = x; } class UnverstyAdmn { statc BnaryTree students = new BnaryTree(); } publc statc addstudent (Student s) { BnaryTreeNode n = new BnaryTreeNode(s); students.nsert(n); } publc statc vod man(strng args[]) { Student s = new Student( Jane Smth ); addstudent(s); } / SET / W&I 17/02/16 PAGE 23 gen(student.student.ths) = {Student} Student.Student.ths out(student.student.ths) 1 = {Student} UA.man.s out(ua.man.s) 2 = {Student} UA.addStudent.s out(ua.addstudent.s) 3 = {Student} BTN.BTN.x out(btn.btn.x) 4 = {Student} BTN.obj out(btn.obj) = {Student}

24 What about contaners? Contaners: Map, Lst, Collecton, Vector Weakly typed: Collect objects of the type that s not yet declared. Operatons: nsert and extract Informaton flow nsert element collecton extract collecton element The same approach works! / SET / W&I 17/02/16 PAGE 24

25 Back to the orgnal problem: Mssng lnk class Lbrary { Map documents = new HashMap(); Map users = new HashMap(); Collecton loans = new LnkedLst(); } publc boolean adduser(user user) { f (!users.contansvalue(user)) { users.put( new Integer( user.getcode()), user); return true; } return false; } Lbrary.addUser.user Lbrary.users / SET / W&I 17/02/16 PAGE 25

26 Back to the orgnal problem: Mssng lnk class Man { statc Lbrary lb = new Lbrary(); publc statc vod adduser(strng cmd) { 1 User user = new User(args[0], args[1]) 2 lb.adduser(user); } } gen(user.user.ths) = {User} User.User.ths 1 Man.addUser.user 2 Lbrary.addUser.user Lbrary.users out(lbrary.users) = {User} / SET / W&I 17/02/16 PAGE 26

27 Back to the orgnal problem: Mssng lnk Lbrary gen(user.user.ths) = {User} User.User.ths users Loan Man.addUser.user User Documen t Lbrary.addUser.user InternalU ser Journal Book TechRepo rt Lbrary.users out(lbrary.users) = {User} / SET / W&I 17/02/16 PAGE 27

28 Is ths all? Assocatons can be ntroduced by extracton: publc Lst searchdocumentbyttle(strng ttle) { Lst docsfound = newlnkedlst(); out(lbrary.documents) = {Document} Iterator = documents.values().terator(); Lbrary.documents } whle (.hasnext()) { Document doc = (Document).next(); f (doc.getttle().ndexof(ttle)!= -1) docsfound.add(doc); } return docsfound; gen(lbrary.sdbt.) = {Document} Lbrary.searchDocu mentbyttle. Lbrary.searchDocu mentbyttle.doc Data-flow analyss progresses backwards! / SET / W&I 17/02/16 PAGE 28

29 Concludng the example Lbrary Loan loans Tonella, Potrch 2005 documents users user loans loan document User Document InternalUser Journal Book TechReport Red assocatons were omtted by the basc AR technque. / SET / W&I 17/02/16 PAGE 29

30 Concludng the example Lbrary Loan User Document InternalUser Journal Book TechReport Red assocatons were omtted by the basc AR technque. / SET / W&I 17/02/16 PAGE 30

31 Summary so far: AR Class dagrams Implemented n many tools How precse? Depends on the tool Basc technque s very smple but mprecse Improvng precson necesstates data-flow analyss / SET / W&I 17/02/16 PAGE 31

32 Is ths the Holy Gral?.. / LaQuSo / Mathematcs & Computer Scence 17/02/16 PAGE 32

33 Packages Hgher level of abstracton OO-languages usually contan explct mechansm: packages (Java), namespaces (C++), modules (Modula) Easly derved from the class dagram Lbrary Loan User Document InternalUser Journal Book TechReport / SET / W&I 17/02/16 PAGE 33

34 Better vsualzatons / SET / W&I 17/02/16 PAGE 34

35 What f the packages are unknown? When can t happen? Sutablty for evoluton Packagng s beng assessed for approprateness Implementaton of evoluton Legacy language wth no packagng Inapproprate packagng What can we do? Let the user do t her/hmself! Do t automatcally: Jon smlar classes together: clusterng Packages can be composed nto larger packages: Herarchcal clusterng / SET / W&I 17/02/16 PAGE 35

36 What s a good modularzaton? Many ntra-package dependences: hgh coheson A = µ N 2 or A = N µ ( N 1) µ - Number of dependences n package N - Number of classes n package / SET / W&I 17/02/16 PAGE 36

37 What s a good modularzaton? Many ntra-package dependences: hgh coheson A = µ N 2 A = ( N 1) Few nter-package dependences: low couplng E, j = ε, j 2N N or j N µ ε, j - Number of dependences between packages and j / SET / W&I 17/02/16 PAGE 37

38 What s a good modularzaton? Many ntra-package dependences: hgh coheson A = µ N Few nter-package dependences: low couplng E, j = Jont measure MQ = / SET / W&I 17/02/16 PAGE 38 2 ε, j 2N N or j A = N µ ( N 1) k k 1 k 1 2 A k = 1 k( k 1) = 1 j= + 1 E, j k - Number of packages

39 Modularty Qualty Coheson Couplng MQ = 1 k 2 k 1 k A k( k 1) = 1 k = 1 j= + 1 E, j What does MQ = -1 mean? No coheson, maxmal couplng MQ = 1? No couplng, maxmal coheson / SET / W&I 17/02/16 PAGE 39

40 Herarchcal Clusterng Int: every element s a cluster on ts own Whle (#clusters > 1) do Calculate smlarty between all pars of clusters Select two most smlar clusters Sngle lnkage: max parwse smlarty Reduces couplng Complete lnkage: mn parwse smlarty Increases coheson Usually more mportant Merge these clusters / SET / W&I 17/02/16 PAGE 40

41 Herarchcal clusterng example A B C D E F G H / SET / W&I 17/02/16 PAGE 41

42 Herarchcal clusterng: Classes Class descrpton: feature vectors Dmenson: feature Methods called, types used, words n the descrpton Coordnate: number of references to ths feature NB: Should be dscrmnatng enough Classes Varables and felds of the user-defned classes / SET / W&I 17/02/16 PAGE 42

43 When are two vectors smlar? x,..., 1 x n y 1,..., yn Dstance between and : n = 1 x y or n ( x ) y = 1 2 What happens f the vectors are almost empty? Dstance s small Clusterng s mprecse d(red,green) = d(green,purple) green and purple are more smlar / SET / W&I 17/02/16 PAGE 43

44 Better alternatve: Smlarty measures Cosne measure: n = 1 n = 1 x 2 x y n = 1 y 2 sm(red,green) = 0 sm(green,purple) = Many more can be found n the lterature / SET / W&I 17/02/16 PAGE 44

45 Back to the lbrary example Class descrpton: feature vectors Dmenson: feature Methods called, types used, words n the descrpton Coordnate: number of references to ths feature Lbrary Loan Document Book Journal TR User Internal User Lbrary <0, 5, 12, 0, 0, 0, 10, 0> Loan <0, 1, 3, 0, 0, 0, 3, 0> Document <0, 2, 1, 0, 0, 0, 3, 0> Book <0, 0, 0, 0, 0, 0, 0, 0> Journal <0, 0, 0, 0, 0, 0, 1, 0> TR <0, 0, 0, 0, 0, 0, 1, 0> User <0, 3, 1, 0, 0, 0, 1, 0> InternalUser <0, 0, 0, 0, 0, 0, 0, 0> / SET / W&I 17/02/16 PAGE 45

46 Herarchcal clusterng: Lbrary Lbrary Loan Document Book Journal TR User Internal User Lbrary <0, 5, 12, 0, 0, 0, 10, 0> Loan <0, 1, 3, 0, 0, 0, 3, 0> Document <0, 2, 1, 0, 0, 0, 3, 0> Book <0, 0, 0, 0, 0, 0, 0, 0> Journal <0, 0, 0, 0, 0, 0, 1, 0> TR <0, 0, 0, 0, 0, 0, 1, 0> User <0, 3, 1, 0, 0, 0, 1, 0> InternalUser <0, 0, 0, 0, 0, 0, 0, 0> Book / SET / W&I IntUser Journal 17/02/16 TechncalReport PAGE 46 User Document Lb. Loan

47 From clusters to packages Where can we put the cutlne(s)? Evaluate the MQ! Book InternalUser Journal TechncalReport User Document Loan Lbrary Packages are created by cut ponts Subpackages are created by more cut ponts / SET / W&I 17/02/16 PAGE 47

48 Algorthm: what have we done? Some cluster partton Int: every element s a cluster on ts own Whle (#clusters > 1) do Calculate smlarty between all pars of clusters Select two most smlar clusters Sngle lnkage: max parwse smlarty Reduces couplng Complete lnkage: mn parwse smlarty Increases coheson Usually more mportant Merge these clusters We can stop earler, when the MQ no longer mproves Mnor change n cluster partton / SET / W&I 17/02/16 PAGE 48

49 Ths s a combnatoral optmzaton problem! Hll Clmbng: Start wth a random cluster parttonng As long as the optmzaton functon ncreases Select a best neghbour partton Neghbour: small change Best: wth the hghest opt. func. value A: there may be more than one such partton Problems: local maxma, plateau, rdges There are better search technques Search-Based Software Engneerng / SET / W&I 17/02/16 PAGE 49

50 What have we seen today? Reverse engneerng/archtecture reconstructon Dfferent vews dfferent approaches Goal Queston Vews Metrcs Class dagrams Basc approach: smple, mprecse Better precson requres data-flow analyss Package dagrams Fxed or user-defned packages Automated technques: Clusterng Search-based, e.g. Hll clmbng / SET / W&I 17/02/16 PAGE 50

51 Assgnment 2: Tll March 9! Pars Archtecture reconstructon: Usng Rascal buld a small archtecture reconstructon tool for Java, and apply t to study evoluton of CyberNeko HTML Parser Dec 2007 vs June 2014 / SET / W&I 17/02/16 PAGE 51

52 Rascal??? Meta-programmng language Developed at CWI Jurgen Vnju and hs team Next Wednesday: Guest lecture of Jurgen Vnju about Rascal / SET / W&I 17/02/16 PAGE 52