Automatic Data Structure Repair for SelfHealing Systems

1
Automatic Data Structure Repair for Self-Healing
Systems

• Brian Demsky
• Martin Rinard
• Laboratory for Computer Science
• Massachusetts Institute of Technology

2
Motivation
Broken Data Structure

• Errors
• Missing elements
• Inappropriate sharing
• Dangling references
• Out of bounds array indices
• Inconsistent values

F 20 G 5
F 20 G 10
I 5
J 2
3
Goal
Broken Data Structure
Consistent Data Structure
F 10 G 5
F 20 G 10
F 2 G 1
F 20 G 5
F 20 G 10
Repair Algorithm
I 3
I 5
J 2
J 2
4
Goal
Broken Data Structure
Consistent Data Structure
Consistency Properties From Developer
F 10 G 5
F 20 G 10
F 2 G 1
F 20 G 5
F 20 G 10
Repair Algorithm
I 3
I 5
J 2
J 2
5
What Does Repair Algorithm Produce?

• Data structure that
• Satisfies consistency properties, and
• Heuristically close to broken data structure
• Not necessarily the same data structure as
  (hypothetical) correct program would produce
• But enough to keep program operating successfully

6
Precursors

• Data structure repair has historically appeared
  in systems with extreme reliability goals
• 5ESS switch hand coded audit routines
• IBM MVS operating system hand coded failure
  recovery routines
• Key component of these systems

7
Where Is This Likely To Be Useful?

• Not for systems with slack - can just reboot
• Cause of error must go away after reboot
• Must be OK to lose volatile state
• Must be OK to wait for reboot
• Persistent data structures
• (file systems, application files)
• Autonomous and/or safety critical systems
• Monitor/control unstable physical phenomena
• Largely independent subcomputations
• Moving time window

8
Architecture
Broken Abstract Model
Repaired Abstract Model
Internal Consistency Properties
External Consistency Properties
Model Definition Translation
1011100110001111011 1010101011110011101 1010111000
111101110
1010011110001111011 1010110101110011010 1010111011
001100010
Broken Bits
Repaired Bits
9
Architecture Rationale

• Why go through the abstract model?
• Simple, uniform structure
• Sets of objects
• Relations between objects
• Simplifies both
• Expression of consistency properties
• Repair algorithm
• Enables system to support full range of
  efficient, heavily encoded data structures

10
File System Example
abst
intro

0
2
1

-5

1

-1
Directory Entries
Disk Blocks
struct Disk Entry dirNumEntries Block
blockNumBlocks Disk D

• struct Entry
• byte nameLength
• int firstBlock
• struct Block
• int nextBlock
• data byteBlockSize

11
Model Definition

• Sets of objects
• set blocks of integer partition used free
• Relations between objects values of object
  fields, referencing relationships between objects
• relation next used, used

blocks
used
free
next
12
Model Translation

• Bits translated to sets and relations in abstract
  model using statements of the form
• Quantifiers, Condition ? Inclusion Constraint
• for i in 0..NumEntries, 0 ? D.diri.firstBlock
  and D.diri.firstBlock lt NumBlocks ?
• D.diri.firstBlock in used
• for b in used, 0 ? D.blockb.nextBlock and
  D.blockb.nextBlock lt NumBlocks ?
  ?b,D.blockb.nextBlock? in next
• for ?b,n? in next, true ? n in used
• for b in 0..NumBlocks, not (b in used) ? b in free

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Model in Example
abst
intro

0
2
1

-5

1

-1
Directory Entries
Disk Blocks
blocks
used
0
next
free
1
3
next
2
14
Internal Consistency Properties

• Quantifiers, Body
• Body is first-order property of basic
  propositions
• Inequality constraints on values of numeric
  fields
• V.R E, V.R lt E, V.R ? E, V.R ? E, V.R gt E
• Presence of required number of objects
• size(S) C, size(S) ? C, size(S) ? C
• Topology of region surrounding each object
• size(V.R) C, size(V.R) ? C, size(V.R) ? C
• size(R.V) C, size(R.V) ? C, size(R.V) ? C
• Inclusion constraints V in S, V1 in V2.R,
  ?V1,V2? in R
• Example for b in used, size(next.b) ? 1

15
Internal Consistency Violations

• Evaluate consistency properties, find violations
• for b in used, size(next.b) ? 1 is false for b 1

blocks
used
0
next
free
1
3
next
2
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Repairing Violations of Internal Consistency
Properties

• Violation provides binding for quantified
  variables
• Convert Body to disjunctive normal form
• (p1 ? ? pn ) ? ? (q1 ? ? qm )
• p1 pn , q1 qm are basic propositions
• Choose a conjunction to satisfy
• Repair violated basic propositions in conjunction

17
Repairing Violations of Basic Propositions

• Inequality constraints on values of numeric
  fields
• V.R E, V.R lt E, V.R ? E, V.R ? E, V.R gt E
• Compute value of expression, assign field
• Presence of required number of objects
• size(S) C, size(S) ? C, size(S) ? C
• Remove or insert objects from/to set
• Topology of region surrounding each object
• size(V.R) C, size(V.R) ? C, size(V.R) ? C
• size(R.V) C, size(R.V) ? C, size(R.V) ? C
• Remove or insert pairs from/to relation
• Inclusion constraints V in S, V1 in V2.R,
  ?V1,V2? in R
• Remove or add the object or pair from/to set or
• relation

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Repair in Example
for b in used, size(next.b) ? 1 is false for b
1 Must repair size(next.1) ? 1 Can remove either
?0,1? or ?2,1? from next
blocks
used
0
next
free
1
3
next
2
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Repair in Example
for b in used, size(next.b) ? 1 is false for b
1 Must repair size(next.1) ? 1 Can remove either
?0,1? or ?2,1? from next
blocks
used
0
next
free
1
3
2
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Acyclic Repair Dependences

• Questions
• Isnt it possible for the repair of one
  constraint to invalidate another constraint?
• What about infinite repair loops?
• What about unsatisfiable specifications?
• Answer
• We require specifications to have no cyclic
  repair dependences between constraints
• So all repair sequences terminate
• Repair can fail only because of resource
  limitations

21
External Consistency Constraints

• Quantifiers, Condition ? Body
• Body of form V E, V.F E, V.FI E
• Example
• for b in free, true ? D.blockb.nextBlock -2
• for ?i,j? in next, true ? D.blocki.nextBlock
  j
• for b in used, size(b.next) 0 ?
  D.blockb.nextBlock -1
• Repair simply performs assignments
• Translates model repairs to bit repairs

22
Repair in Example
Inconsistent File System
Repaired File System
23
When to Test for Consistency and Repair

• Persistent data structures
• Repair can be independent activity, or
• Repair when data written out or read in
• Volatile data structures in running program
• Under programmer control
• Transaction-based approach
• Identify transaction start and end
• Repair at start, end, or both
• Failure-based approach
• Wait until program fails
• Repair and restart from latest safe point

24
Experience

• We acquired four benchmarks (written in C/C)
• CTAS (air-traffic control tool)
• Simplified Linux file system
• Freeciv interactive game
• Microsoft Word files
• We developed specifications for all four
• Very little development time (days, not weeks)
• Most of time spent figuring out Freeciv and CTAS
• Each benchmark has
• Workload
• Fault insertion methodology
• Ran benchmarks with and without repair

25
CTAS

• Set of air-traffic control tools
• Traffic management
• Arrival planning
• Flow visualization
• Shortcut planning
• Deployed in centers around country (Dallas/Ft.
  Worth, Los Angeles, Denver, Miami,
  Minneapolis/St. Paul, Atlanta, Oakland)
• Approximately 1 million lines of C/C code

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CTAS Screen Shot
27
Results

• Workload recorded radar feed from DFW
• Fault insertion
• Simulate error in flight plan processing
• Bad airport index in flight plan data structure
• Without repair
• System crashes segmentation fault
• With repair
• Aircraft has different origin or destination
• System continues to execute
• Anomaly eventually flushed from system

28
Aspects of CTAS

• Lots of independent subcomputations
• System processes hundreds of aircraft problem
  with one should not affect others
• Multipurpose system
  (visualization, arrival planning, shortcuts, )
  problem in one purpose should not affect others
• Sliding time window anomalies eventually flushed
• Rebooting ineffective system will crash again
  as soon as it sees the problematic flight plan

29
Simplified Linux File System


intro
110



0

1011













directory block
inode bitmap block
block bitmap block
inode
inode

super block
group block
disk blocks
inode block

• Some Consistency Properties
• inode bitmap consistent with inode usage
• block bitmap consistent with block usage
• directory entries refer to valid inodes
• files contain valid blocks only
• files do not share blocks

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Results

• Workload write and verify several files
• Fault insertion crash file system
• Inode and block bitmap errors
• Partially initialized directory and inode entries
• Without repair
• Incorrect file contents because of inode and disk
  block sharing
• With repair
• Bitmaps repaired preventing illegal sharing,
  correct file contents

31
Freeciv
Terrain Grid

• Consistency Properties
• Tiles have valid terrain values
• Cities are not in the ocean
• Each city has exactly one reference from city
  location grid
• City locations are consistent in
• City structures and
• tile grid

O Ocean
P
O
M
M
P Plain
O
O
M
P
M Mountain
P
O
M
M
City Structures
P
P
M
P
loc 3,0
loc 2,3
32
Results

• Workload Freeciv software plays against itself
• Fault insertion randomly corrupt terrain values
• Without repair program fails (seg fault)
• With repair
• Game runs just fine
• But game plays out differently because of the
  different terrain values

33
Microsoft Word Files

• Files consist of a sequence of streams
• Streams stored using FAT-based data structure
• Consistency Properties
• FAT blocks exist and contain valid entries
• FAT streams are properly terminated
• Free blocks properly marked
• Streams contain valid blocks
• No sharing of blocks between streams

abst
1
intro




7
0
1
9
2
-1
-1
-2
1
Directory Entries
FAT
Disk Blocks
34
Results

• Workload several Microsoft Word files
• Fault insertion scramble FAT
• Without repair
• If blocks containing the FAT were incorrectly
  marked as free, Word successfully loads file
• Otherwise, The document name or path is
  not valid
• With repair
• Word loads all files

35
Extensions

• Elimination of external consistency constraints
• Eliminates problems with translating repairs on
  the abstract model to the actual data structure
• Repair algorithm analyzes model definition rules
  to generate repair actions for the actual data
  structure

36
Extensions

• Support for doubly linked data structures
• Enables the repair algorithm to regenerate back
  links

37
Extensions

• Compilation and optimization of consistency
  checking
• Achieved significant speedups (n x) by compiling
  the specification
• Achieved further speedups () by partially
  optimizing away the construction of the abstract
  model

38
Related Work

• Hand-coded repair
• Lucent 5ESS switch
• IBM MVS operating system
• Self-stabilizing algorithms
• Log-based recovery for database systems
• Recovery-oriented computing
• Recursive restartability
• Undo framework

39
Conclusion

• Data structure repair interesting way to
  (potentially) improve reliability
• Specification-based approach promises to make
  technique more widely applicable
• Moving towards more robust, probabilistic,
  continuous concept of system behavior

40
Formalizing Repair DependencesConstraint
Dependence Graph

• Nodes Constraint, Conjuncts from DNF
• Edges
• constraint to its conjunctions
• conjunction to dependent propositions
• if repairing conjunction could falsify
  proposition, or
• if repairing conjunction could increase
  quantifier scope

P
(b1 ? ? bn )
(a1 ? ? an )
Q
T
(c1 ? ? cn )
(d1 ? ? dn )
(e1 ? ? en )
(f1 ? ? fn )
41
Consistency Properties

• The FAT blocks exist
• FAT contains valid values only
• -1 terminates FAT streams
• -2 indicates free blocks
• Valid disk block index next block in stream
• FAT streams properly terminated
• Free blocks properly marked
• Streams contain valid blocks only
• Streams do not share blocks

42
Formalizing Repair DependencesConstraint
Dependence Graph

• Absence of cycles implies valid repair schedule
• Conjunction removal for cycle elimination
• (must leave at least one conjunction per
  constraint)

P
(b1 ? ? bn )
(a1 ? ? an )
Q
T
(c1 ? ? cn )
(d1 ? ? dn )
(e1 ? ? en )
(f1 ? ? fn )
43
Formalizing Repair DependencesConstraint
Dependence Graph

• Absence of cycles implies valid repair schedule
• Conjunction removal for cycle elimination
• (must leave at least one conjunction per
  proposition)

P
(b1 ? ? bn )
(a1 ? ? an )
Q
T
(c1 ? ? cn )
(d1 ? ? dn )
(e1 ? ? en )
44
Pointers

• Sets in model can include
• Primitive types (int, char, )
• Structs (identified by pointer to struct)
• Standard linked list example
• struct node int value node next
• set nodes of node
• relation next node, node
• for n in nodes, true ? n.next in nodes
• for n in nodes, true ? ?n,n.next? in next

45
What About Corrupted Pointers?

• System only allows valid structs in model
• struct must be completely in valid memory
• one struct may be nested inside another struct
  (but must agree on memory format)
• If encounter invalid or null pointer, the
  (invalid) struct does not appear in model
• Implementation must track operations that affect
  valid regions of address space
• malloc, free
• mmap, munmap

46
CTAS in Action
FAST at DFW TRACON
TMA at Fort Worth Center
47
Usage Scenarios

• Reduced development effort
• Invest less effort in finding and fixing bugs
• Rely on repair to deliver reliable system
• Afraid to fix bug
• Cheap insurance policy
• No good quantitative justification
• But repair seems like a good idea

48
Issues

• Unclear relationship between repaired bits and
  bits from correct execution of program
• Identifying results involving repaired data
• Characterizing likely errors
• Data races in multithreaded programs
• Failure to update correlated data structures
• Caching inconsistencies
• Unanticipated failures/exit points
• Constraint language expressivity
• Coverage of desired properties
• Limitations from acyclicity requirement
• When to test for consistency and repair

49
What About Corrupted Pointers?

• Sets may contain pointers to structs
• System only allows valid structs in model
• struct must be completely in valid memory
• one struct may be nested inside another struct
  (but must agree on memory format)

Invalid Struct
Valid Struct
Valid Structs
Valid Memory
Invalid Memory
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Interesting Nuggets

• Small specifications
• Global invariant advantages