1. Bandera: Extracting Finite-state Models from Java Source Code James Corbett Matthew Dwyer John Hatcliff Shawn Laubach Corina Pasareanu Robby Hongjun Zheng Faculty Students and Post-docs Roby Joehanes Ritesh Desai Venkatesh Ranganath Oksana Tkachuk

2. Goal: Increase Software Reliability Trends: Size, complexity, concurrency, distributed Cost of software engineer………………………. Cost of CPU cycle……………………………….. Future: Automated Fault Detection

3. The Dream Program Requirement Checker OK Error trace or void add(Object o) { buffer[head] = o; head = (head+1)%size; } Object take() { … tail=(tail+1)%size; return buffer[tail]; } Property 1: … Property 2: … …

4. Model Checking OK Error trace or Finite-state model Temporal logic formula Model Checker  Line 5: … Line 12: … Line 15:… Line 21:… Line 25:… Line 27:… … Line 41:… Line 47:…

5. Why use Model Checking? In contrast to testing, gives complete coverage by exhaustively exploring all paths in system, It’s been used for years with good success in hardware and protocol design Automatically check, e.g., –invariants, simple safety & liveness properties –absence of dead-lock and live-lock, –complex event sequencing properties, “Between the window open and the window close, button X can be pushed at most twice.” This suggests that model-checking can complement existing software quality assurance techniques.

6. What makes model-checking software difficult? Model construction OK Error trace or Finite-state model Temporal logic formula Model Checker  State explosion Problems using existing checkers: Property specification Output interpretation Line 5: … Line 12: … Line 15:… Line 21:…

7. Model Construction Problem Semantic gap: Model Description Model Checker Program void add(Object o) { buffer[head] = o; head = (head+1)%size; } Object take() { … tail=(tail+1)%size; return buffer[tail]; } Gap Programming Languages Model Description Languages methods, inheritance, dynamic creation, exceptions, etc. automata

8. What makes model-checking software difficult? Model construction OK Error trace or Finite-state model Temporal logic formula Model Checker  State explosion Problems using existing checkers: Property specification Output interpretation Line 5: … Line 12: … Line 15:… Line 21:…

9. Property Specification Problem Difficult to formalize a requirement in temporal logic “Between the window open and the window close, button X can be pushed at most twice.” []((open /\ <>close) -> ((!pushX /\ !close) U (close \/ ((pushX /\ !close) U (close \/ ((!pushX /\ !close) U (close \/ ((pushX /\ !close) U (close \/ (!pushX U close)))))))))) …is rendered in LTL as...

10. Property Specification Problem We want to write source level specifications... (((_collect(heap_b) == 1)\ && (BoundedBuffer_col.instance[_index(heap _b)].head == BoundedBuffer_col.instance[_index(heap _b)].tail) )\ || ((_collect(heap _b) == 3)\ && (BoundedBuffer_col_0.instance[_index(heap _b)].head == BoundedBuffer_col_0.instance[_index(heap _b)].tail) )\ || ((_collect(heap _b) == 0) && TRAP)) Heap.b.head == Heap.b.tail We are forced to write model level specifications... Forced to state property in terms of model rather than source:

11. What makes model-checking software difficult? Model construction OK Error trace or Finite-state model Temporal logic formula Model Checker  State explosion Problems using existing checkers: Property specification Output interpretation Line 5: … Line 12: … Line 15:… Line 21:…

12. State Explosion Problem Moore’s law and algorithm advances can help –Holzmann: 7 days (1980) ==> 7 seconds (2000) Explosive state growth in software limits scalability Bit x1,…,xN2^N states Cost is exponential in the number of components

13. What makes model-checking software difficult? Model construction OK Error trace or Finite-state model Temporal logic formula Model Checker  State explosion Problems using existing checkers: Property specification Output interpretation Line 5: … Line 12: … Line 15:… Line 21:…

14. Output Interpretation Problem Raw error trace may be 1000’s of steps long Model Description Program void add(Object o) { buffer[head] = o; head = (head+1)%size; } Object take() { … tail=(tail+1)%size; return buffer[tail]; } Gap Error trace Line 5: … Line 12: … Line 15:… Line 21:… Line 25:… Line 27:… … Line 41:… Line 47:… Must map line listing onto model description Mapping to source is made difficult by –Semantic gap & clever encodings of complex features –multiple optimizations and transformations

15. Bandera: An open tool set for model-checking Java source code Checker Inputs Checker Outputs Optimization Control Transformation & Abstraction Tools Model Checkers Java Source void add(Object o) { buffer[head] = o; head = (head+1)%size; } Object take() { … tail=(tail+1)%size; return buffer[tail]; } Bandera Temporal Specification Graphical User Interface Error Trace Mapping Bandera

16. Addressing the Model Construction Problem Numerous analyses, optimizations, two intermediate languages, multiple back-ends Slicing, abstract interpretation, specialization Variety of usage modes: simple...highly tuned Model extraction: compiling to model checker inputs: Java Source void add(Object o) { buffer[head] = o; head = (head+1)%size; } Object take() { … tail=(tail+1)%size; return buffer[tail]; } Model DescriptionModel Compiler Static Analyses Abstract Interpretation Slicing Optimizations

17. Addressing the Property Specification Problem An extensible language based on field-tested temporal property specification patterns []((open /\ <>close) -> ((!pushX /\ !close) U (close \/ ((pushX /\ !close) U (close \/ ((!pushX /\ !close) U (close \/ ((pushX /\ !close) U (close \/ (!pushX U close)))))))))) Using the pattern system: 2-bounded existence Between {open} and {close} {pushX} exists atMost {2} times;

18. Addressing the State Explosion Problem Aggressive customization via slicing, abstract interpretation, program specialization Java Source void add(Object o) { buffer[head] = o; head = (head+1)%size; } … Model DescriptionsModel Compiler Property Generate models customized wrt property! Result: multiple models --- even as many as one per property

19. Addressing the Output Interpretation Problem Run error traces forwards and backwards Program state queried Heap structures navigated Locks, wait sets, blocked sets displayed Like a debugger: error traces mapped back to source Java Source void add(Object o) { buffer[head] = o; head = (head+1)%size; } Object take() { … tail=(tail+1)%size; return buffer[tail]; } Model Compiler Model Checker Intermediate Representations Error trace Line 5: … Line 12: … Line 15:… Line 21:… Model Description + simulator

20. Bandera Architecture BIRC BIR Simulator Abstraction Engine Slicer Analyses Translators SPIN dSPIN SMV JPF Property Tool Java Jimple Parser Error Trace Display

21. Property Specification /** * observable * EXP Full: (head == tail); */ class BoundedBuffer { Object [] buffer; int head, tail, bound; public synchronized void add(Object o) {…} public synchronized Object take () {…} } Requirement: If a buffer becomes full, it will eventually become non-full. Bandera Specification: FullToNonFull: forall[b:BoundedBuffer]. {!Full(b)} responds to {Full(b)} globally;

22. Property Specification

25. Property-directed Slicing slicing criterion generated automatically from observables mentioned in the property backwards slicing automatically finds all components that might influence the observables. Source program Resulting slice Slice mentioned in property indirectly relevant

26. Property-directed Slicing /** * @observable EXP Full: (head == tail) */ class BoundedBuffer { Object [] buffer_; int bound; int head, tail; public synchronized void add(Object o) { while ( tail == head ) try { wait(); } catch ( InterruptedException ex) {} buffer_[head] = o; head = (head+1) % bound; notifyAll(); }... } Included in slicing critirion Slicing Criterion All statements that assign to head, tail. indirectly relevant removed by slicing

27. Property-directed Slicing Thread 1Thread 2 Data Dependence x := 3; y = x + 1; Control Dependence z<0 Interference Dependence x := z; z := 4; Synchronization Dependence enter monitor(o) Ready Dependence notify(o) wait(o) [SAS’99] Dependencies for concurrent Java

28. Abstraction Engine int x = 0; if (x == 0) x = x + 1; Data domains (n<0) : neg (n==0): zero (n>0) : pos Signs negposzero int Code Signs x = zero; if (x == zero) x = pos; Collapses data domains via abstract interpretation:

29. Abstraction Component Functionality Variable Concrete Type Abstract Type Inferred Type Abstraction Library Bandera Abstraction Specification Language BASL Compiler PVS Jimple Abstraction Engine Abstracted Jimple x y done count o b int bool Object Buffer int …. Signs intAbs Bool …. Point Buffer

30. Abstraction Specification abstraction Signs abstracts int begin TOKENS = { NEG, ZERO, POS }; abstract(n) begin n {NEG}; n == 0 -> {ZERO}; n > 0 -> {POS}; end operator + add begin (NEG, NEG) -> {NEG} ; (NEG, ZERO) -> {NEG} ; (ZERO, NEG) -> {NEG} ; (ZERO, ZERO) -> {ZERO} ; (ZERO, POS) -> {POS} ; (POS, ZERO) -> {POS} ; (POS, POS) -> {POS} ; (_,_)-> {NEG, ZERO, POS}; /* case (POS,NEG), (NEG,POS) */ end public class Signs { public static final int NEG = 0; // mask 1 public static final int ZERO = 1; // mask 2 public static final int POS = 2; // mask 4 public static int abstract(int n) { if (n < 0) return NEG; if (n == 0) return ZERO; if (n > 0) return POS; } public static int add(int arg1, int arg2) { if (arg1==NEG && arg2==NEG) return NEG; if (arg1==NEG && arg2==ZERO) return NEG; if (arg1==ZERO && arg2==NEG) return NEG; if (arg1==ZERO && arg2==ZERO) return ZERO; if (arg1==ZERO && arg2==POS) return POS; if (arg1==POS && arg2==ZERO) return POS; if (arg1==POS && arg2==POS) return POS; return Bandera.choose(7); /* case (POS,NEG), (NEG,POS) */ } Compiled

31. Specification Creation Tools abstraction Signs abstracts int begin TOKENS = { NEG, ZERO, POS }; abstract(n) begin n {NEG}; n == 0 -> {ZERO}; n > 0 -> {POS}; end operator + add begin (NEG, NEG) -> {NEG} ; (NEG, ZERO) -> {NEG} ; (ZERO, NEG) -> {NEG} ; (ZERO, ZERO) -> {ZERO} ; (ZERO, POS) -> {POS} ; (POS, ZERO) -> {POS} ; (POS, POS) -> {POS} ; (_,_)-> {NEG, ZERO, POS}; end Automatic Generation Forall n1,n2: neg?(n1) and neg?(n2) implies not pos?(n1+n2) Forall n1,n2: neg?(n1) and neg?(n2) implies not zero?(n1+n2) Forall n1,n2: neg?(n1) and neg?(n2) implies not neg?(n1+n2) Proof obligations submitted to PVS... Example: Start safe, then refine: +(NEG,NEG)={NEG,ZERO,POS}

32. Abstraction Library Current Library Contains : Range(i,j) : i..j modeled precisely, e.g., –Range(0,0) is the signs abstraction –Range(2,4) has tokens {lt2,2,3,4,gt4} Modulo(k), e.g., –Modulo(2) is the even-odd abstraction Specific(v,…) : identifies values of interest, e.g., –Specific(10) has tokens {eq10,not10} User extendable for base type predicates

33. Back End Bandera Intermediate Representation (BIR) –guarded command language –includes: locks, threads, references, heap –info to help translators (live vars, invisible) entermonitor r0 r1.count = 0; … loc s5: live { r0, r1 } when lockAvail(r0.lock) do { lock(r0.lock); } goto s6; loc s6: live { r1 } when true do invisible { r1.count = 0;} goto s7; Jimple BIR

34. Bounded Buffer BIR process BoundedB() BoundedBuffer_ref = ref { BoundedBuffer_col, BoundedBuffer_col_0 }; BoundedBuffer_rec = record { bound_ : range -1..4; head_ : range -1..4; tail_ : range -1..4; BIRLock : lock wait reentrant; }; BoundedBuffer_col : collection [3] of BoundedBuffer_rec; BoundedBuffer_col_0 : collection [3] of BoundedBuffer_rec; ……. ………. loc s34: live { b2, b1, add_JJJCTEMP_0, add_JJJCTEMP_6, add_JJJCTEMP_8 } when true do invisible { add_JJJCTEMP_8 := (add_JJJCTEMP_6 % add_JJJCTEMP_8); } goto s35; loc s35: live { b2, b1, add_JJJCTEMP_0, add_JJJCTEMP_8 } when true do { add_JJJCTEMP_0.head_ := add_JJJCTEMP_8; } goto s36; loc s36: live { b2, b1, add_JJJCTEMP_0 } when true do { notifyAll(add_JJJCTEMP_0.BIRLock); } goto s37; loc s37: live { b2, b1, add_JJJCTEMP_0 } when true do { unlock(add_JJJCTEMP_0.BIRLock); } goto s38;

35. Bounded Buffer Promela typedef BoundedBuffer_rec { type_8 bound_; type_8 head_; type_8 tail_; type_18 BIRLock; } … loc_25: atomic { printf("BIR: 25 0 1 OK\n"); if :: (_collect(add_JJJCTEMP_0) == 1) -> add_JJJCTEMP_8 = BoundedBuffer_col. instance[_index(add_JJJCTEMP_0)].tail_; :: (_collect(add_JJJCTEMP_0) == 2) -> add_JJJCTEMP_8 = BoundedBuffer_col_0. instance[_index(add_JJJCTEMP_0)].tail_; :: else -> printf("BIR: 25 0 1 NullPointerException\n"); assert(0); fi; goto loc_26; }

36. Translators Plug-in component that interfaces to specific model checker –Translates BIR to checker input language –Parses output of checker for error trace Currently –SPIN, dSPIN, SMV translators complete –JPF (from NASA Ames) integrated –XMC, FDR translators in progress

37. Case Studies Small examples thus far (< 2000 loc) –illustrating use of property-pattern system and other components Scheduler from DEOS real-time OS kernel –(1600, 22 classes, seven tasks) Now trying systems up to 20,000 loc –collection of 15 open-source 100% pure Java –Jigsaw web-server from W3C –Tomcat, James (from Apache/Jakarta) In general, 1-2 minutes for model extraction on (~2000k systems) State space reductions can dramatically reduce cost

38. Summary Bandera provides an open platform for experimentation Separates model checking from extraction –uses existing model checkers –supports multiple model checkers Specialize models for specific properties using automated support for slicing, abstraction, etc. Designed for extensibility –well-defined internal representations and interfaces We hope this will contribute to the definition of APIs for software model-checkers

39. Other Work on Software Model-checking Java –JPF (NASA Ames) –JCAT (Torino) –Java to SAL (Stanford) C –SLAM (Microsoft Research) –AX, FeaVer (Lucent)

40. Current Status A reasonable subset of concurrent Java –not handled: recursive methods, exceptions, inner classes, native methods, libraries(*) Public release: October 2000 Demo tomorrow morning http://www.cis.ksu.edu/santos/bandera

41. Ongoing Work Property specification –Define state predicates –Quantify over class instances More sophisticated abstractions Translators to more model checkers

42. Design Goals Separate model checking from extraction –Use existing model checkers –Support multiple model checkers Provide automated support for abstraction –Slicing –Abstract interpretation –Specialization Specialize models for specific properties Design for extensibility –Well-defined internal representations and interfaces

43. Lack of Integration Problem Existing Quality Assurance techniques and tools: Testing Debugging Simulation Run-time monitoring Visualization Monitoring drives checker path selection Model checking tools and artifacts should be integrated: Error traces drive test case generation Debugging/Visualization of error traces Closing environments test harnesses Static Analysis

44. Bandera Toolset Model Checkers Property Source code Checker Inputs Checker Outputs Source trace Bandera

45. What makes model-checking software difficult? Model construction OK Error trace or Finite-state model Temporal logic formula Model Checker  State Explosion Problems using existing checkers: Property specification Output Interpretation

46. Goal: Increase Software Reliability Trends: Software Size Concurrency Complexity Cost of Engineer Cost of CPU cycle Future: Automated Fault Detection

47. Front End Translates Java source to Jimple IR Supports specification of property Provides debugger-like step facilities for error traces if (x > 0) x = y * 2; Label1: if (x <= 0) goto Label2; t0 = y * 2; x = t0; Label2: … Java Jimple

48. Model Checking OK Error trace or Finite-state model Temporal logic formula Model Checker  Line 5: … Line 12: … Line 15:… Line 21:… Line 25:… Line 27:… … Line 41:… Line 47:…