Trace-Based Debugging in Constraint Programming

1

Ludovic LangevineSICS

Joint work with Mireille Ducassé (IRISA)and Pierre Deransart (INRIA)

SweConsNet Workshop

March 7, 2005, Lund

Trace-Based Debugging in Constraint Programming

2

Outline

• Debugging needs in CP(FD)

• Towards a generic debugging

• Observational semantics

• Tracers

• Dynamic trace analysis

3

CP and Debugging[Meier95,DiSCiPl97]

CP is very declarative but● Numerous variables and constraints (105)

What is the state of the system?● Data flow embedded in the solver

What is the behavior of the execution?

Specific debugging tools are needed

4

Observation of Constraint Programs

Four kinds of observation tools exist:– Observation of the search space

– Observation of the constraint propagation

– Explication of value withdrawal

– Application-domain oriented views

5

Observation of the Search Space [Schulte96,Simonis00,Ilog01,Fages02]

Abstract visualization of the behavior of the search (choices, failures, solutions, backtracks)

search-tree

[Fages02]

6

Observation of the Propagation[Simonis00, Paulin01]

Precise view of some points of the execution:- each domain reduction- each constraint awakening

• Detailed effects of the constraints• Variables that are hard to value• Relevance of the filtering algorithms

7

Explication of Value Withdrawal [Jussien et al. 00, Ågren 02, Lesaint 04]

• On each domain reduction, the solver records the cause of the value withdrawal

• Linking those causes provides a precise explanation of the inconsistency of a precise value

Dealing with over-constrained problems Diagnosis of missing solution

Solver implementation has to be designed for computing those explanations

8

Addressed Problem

Various complementary tools existEach tool needs to collect specific data during

the execution

By now, a dedicated instrumentation of the solver is implemented for each tool

High intrusion, repetitive and delicate development

Needs access to solver source code

9

Ad hoc Connections

Platform 2

DebuggingTool 1

Platform n...

DebuggingTool 2

DebuggingTool m

...

Platform 1

Each connection is hard and costly to develop

10

Current Situation

Platform 2

Platform n...

Platform 1

Few platforms support few tools. No sharing of tools

DebuggingTool 1

DebuggingTool 2

DebuggingTool m

...

11

Towards a Better Situation

DebuggingTool 1

Execution

DataDebugging

Tool 2

DebuggingTool m

...

Platform 1

12

Execution Data

• Execution data (trace)– Sequence of events of interest– Reflects the behavior of the execution

• Trace schema = definition of– relevant events– attached information

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Tracer

Guiding Principle

Debugging tools can be built on top of an execution trace

Execution to

observe Trace

DebuggingTool 1

DebuggingTool 2

DebuggingTool m

...

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Towards a Generic Trace Schema

Tracer 2Platform 2 Trace

Schema

Generic

Tracer nPlatform n...

Platform 1Tracer 1

DebuggingTool 1

DebuggingTool 2

DebuggingTool m

...

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Key Issues

What is the content of the trace?Define relevant events and attached data

(trace schema)Pb.: Tools have versatile needs Trace has to be rich

How to produce the trace efficiently?Pb.: Overhead Non usability of the tools

A compromise has to be found

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Rich And Efficient is Possible

Tracer 2Platform 2

Tracer nPlatform n

...

Platform 1Tracer 1

GenericTrace

Requests

Driver

Driver

DriverDebugging

Tool 1

DebuggingTool 2

DebuggingTool m

...

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The Results

• A generic trace schema– Based on an observational semantics

• Three formal specializations of the generic semantics (GNU-Prolog, Choco, PaLM)

• Four tracers (GNU-Prolog, Choco, PaLM, CHIP)

• An architecture to efficiently adapt the trace– The “tracer driver”

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Generic Trace Schema

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Observational Semantics

• The solver state is formalized by observed state(The abstract view we have of its state)

• Each modification of the observed state is traced as an execution event state transition rule

• Trace = sequence of elementary events sufficient to follow the evolution of the observed state

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Observed State

Model of the state of a FD solver• Set of variables V, domain function D• Set of constraints on V, C• Su: set of domain updates to propagate

Search-tree: set of observed states identified as choice-points.

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Propagation

ActiveA

Entail

ScheduleReduce

Reject

Entailed

Rejected

Post

Suspend

Sleeping

Sc Su

Awake

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Example of Transition Rule: reduce

“c is the active constraint. An update u has to be propagated. Some values of c are inconsistent for variable v. Values Δv

c are removed from Dv, while recording the updates u in Su.”

(c,u) A v var(c) Δvc Dvreduce

Dv Dv – Δvc, Su Su u

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Two Specializations of reduce

(c,u) A v var(c) Δvc Dv

Dv Dv – Δvc, Su Su u

reduce(generic)

Ac = {c} v var(c) Δvc Dv Δv

c R = reduce(GNU-Prolog) Dv Dv – Δv

c, Q Q uuu, c, dependence(c,u)

reduce(PaLM)

A = {(c,u)} v var(c) Δvc,u Dv Δv

c,u R =

DvDv – Δvc,u, QQ {u’ }, (v,d,E) | dΔv

c,u

(E1, …, Ek) |var(c) such that E = {c} Ei

i=1

k

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Benefits of Formalization

• The trace has a clear semantics– Limits required understanding of solver’s internals– Helps give meaning to views built on top of the trace

• Design of the trace guided by its usability rather than by implementation issues– Set of removed values considered “impossible to

trace”

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Trace Implementations

- Codeine for GNU-Prolog- Lazy: trace only what is needed, dynamically parameterized- Can trace the whole observed state at each event

- Choco/PaLM: “trace aspect” added at compile-time- The trace can be statically parameterized- Can trace all the modifications of the trace event(work by Jussien and Rochart)

- CHIP

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GNU-Prolog Trace Example

fd_element(I,[2,5,7],A), (A #= I ; A #= 2).

1 [1] choicePoint node(0)2 [1] newVariable v1 [0-268435455]3 [1] newVariable v2 [0-268435455]4 [1] newConstraint c1 fd_element([v1, [2,5,7], v2])5 [1] post c16 [1] reduce c1 v1 delta=[0, 4-268435455]7 [1] reduce c1 v2 delta=[0-1, 3-4, 6, 8-268435455]8 [1] suspend c19 [2] choicePoint node(1)…

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Tracer Performance

• 8 classical programs, from 200k to 400M events– (without the cost of the communication means)

• Minimal cost (tracer) : [+3%, +27%] avg.: +9% The tracer can be always active

• Cost of the search-tree (tree) : [+3%, +27%] avg.: +9%– No extra-cost

• Cost of the attributes (default) : [x3, x7,4] avg.: x5– Similar to existing tracers for declarative languages

[Somogyi, Appel]

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Dynamic Trace Analysis

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A Rich Trace

• The trace is very rich (1s 2GBytes)– Costly to generate (tracer)– Costly to communicate (IPC)– Costly to process (debugging tool)

• A given tool needs only a small subpart of this huge trace

Adapt the trace to the needs of the tool: we propose a tracer driver

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Tracer driver

• A module of the tracer which drives the trace generation

• The tool describes its needs– event patterns: When and What to trace

• The needs can be incrementally updated– Cope with the evolving needs of a tool

• Tracer and tool can be synchronized or not– Can investigate some execution states

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Principles of the Tracer Driver

Solver

Data

(store,

domains,

...)

Solver Tracer Driver AnalyzerFiltering of the evt

...

Evt. iEvt. i+1Evt. i+2

Evt. i+3Evt. i+4

Evt. i+5

AsynchronousEvt. Handler

Trace data

Synchronous

Evt. Handler

Trace data

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Event Patterns

Trace of the search-treesearch_tree: when port in [choicePoint, backTo,

solution, failure] do current(port, chrono, node)

Full Trace predicate Class of relevant events

Event Dataselectionfunction Selection of trace data

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Driver Performance

Its efficiency is inversely proportional to the mean duration of a trace event

OK for CP (a trace event 50ns)

2 orders of magnitude better than the “generate and dump” architecture– We pay only for what we need to trace– The size of the trace is drastically decreased

• Search-tree: 1/100

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The Tracer Driver

Is indeed a good compromise

• Rich trace possible

• Only the requested trace is generated

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• Is the “generic” semantics… generic?– 4 tracers implements it (GNU-Prolog, Choco, PaLM,

CHIP)• Does the trace schema contain the needed data?

– Existing tools have been rebuilt– Innovative tools have been developed

• Is the tracer driver powerful?– Several existing architectures can be implemented in

this framework (e.g. Opium [Ducassé92], Morphine [Jahier99])

– Monitoring, debugging and visualization are enabled in parallel

Qualitative Assessment

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Connectivity

Codeine

Pavot(Arnaud,

Inria)

InfoVis(Ghoniem,

EMN)

Discovery(Baudel, Ilog)PaLM

(EMN)

Generic

Trace

Schema

Choco

(EMN)

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Conclusion

• A framework to debug programs with constraints

• A generic trace schema has been defined

• Various tools can be fed with this trace

• Development of new debugging tools is easier

• A rich trace can be efficient!

38

Ludovic LangevineSICS

Joint work with Mireille Ducassé (IRISA)and Pierre Deransart (INRIA)

SweConsNet Workshop

March 7, 2005, Lund

Trace-Based Debugging in Constraint Programming