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On Using Tracer
Driver for External
Dynamic Process
Observation
Pierre Deransart
WLPE 2006
Pierre Deransart WLPE 06
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Les unités de recherche
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Rocquencourt
Loria
Rhône-Alpes
Irisa
Futurs
Pierre Deransart WLPE 06
Sophia Antipolis
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BASIC MOTIVATIONS
Dynamic Program Analysis:
typical recent works are based on trace analysis
•Ernst & al. 2001: “Dynamically discovering likely
program invariants…” from data computed by dynamic
execution
•Denmat & al. 2005 “Data mining and Cross-checking
of Execution Traces…” from a collection of traces
•Zaidman & al. 2005 “Applying Webmining Techniques
to Execution Traces…”
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WHY TRACES ?
Any phenomenon, any open system leaves traces
•Walking (persistent foot traces)
•Sedimentation (temporally accumulated traces), fossils
•Particles (light): objects only known by their physical or chemical properties
•Programs (outputs, observation)
•Communication (messages)
•Discourse abstract
•Human Memory…(persistent and reactive)
Traces are everywhere: we only know processes by their traces
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OBSERVING PROCESSES
Everybody watches everyones…..
Everybody receives from everyone
Everybody sends messages to …
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« Leave traces, not proofs, only traces give
dreams »
René Char
Poète
(1907-1988)
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We know and define complex objects
from the traces they leave
We know complex programs behaviour
by analyzing their traces
Causal analysis is not tractable
 likely causality
TRACE modeling is the right approach
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BUT, what IS a TRACE ???
HOW to ANALYSE IT ???
I want to leave these questions open
….small demo
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What IS a TRACE
???
the answer is:
Any possible understandable information
related to an observed phenomenon
PRO
•Any observing device will find in the trace what it needs
•If a process needs instrumentation to produce a trace, this
need only to be made once
•Analysis tools may be developed independently
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CON:
- it is not possible to broadcast such a huge
information flow
(communication slowing down)
-then the observed process always computes
a huge amount of unused data (construction
slowing down)
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SPECIFIC ASPECTS
Needs for trace standardization
•All levels of granularity accepted
•Different kinds of informations included (levels of abstraction)
•Each analyser must be able to recognize its relevant
information
•Use of XML to define possible standards
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SEEMS an UNREALISTIC GOAL !!!
the answer is:
Driven Tracer
SPECS
•selects in the trace what the observer needs
•keeps tracer listening to the analyzers (dialog between
server and clients)
•Leave the tracer to distribute and broadcast each specific
trace
•Allow workload repartition between tracer and analysers
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ORGANISATION
•History
•Virtual Full Trace
•Processes organization
•Workload analysis
•Driver requirements
•Conclusions
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HISTORY
•Ducassé, Opium: versatile analyzers
•Ducassé, Noyer, 1994, JLP: independence of tracer and analyzers
•Langevine & Ducassé & Deransart, 2003, ICLP’03: Codeine, First
Driven Tracer approach implementation for GNU-prolog
•Deransart & all, 2004, OADymPaC project: client/server architecture,
trace standardization (XML) for interoperability
•Langevine & Deransart & Ducassé, 2004, LNAI 3010: model of
« generic trace » for constraint programming
•Langevine & Ducassé, 2005, AADEBUG, WLPE: Driven Tracer for FD
constraints and experimentation
•Now, 2006: « theory » of generic trace and driven tracer =
virtual full trace
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VIRTUAL FULL TRACE (definition)
unbounded sequence of trace events of
the form
et: (t, at, St+1)
•et: unique identifier of the event
•t: chrono. Time of the trace
•St = p1,t..., pn,t : parameters at chrono t. In a
trace event the parameters are called attributes
and St the full current state
•at: action characterizing the step of the state
St to the state St+1. It can be described by a set
of transformations which describes the operations
carried out on the current state
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EFFECTIVE TRACE
a full trace of the form
et: (t, At)
such that, starting from the knowledge of
(St,At) one can deduce (at, St+1).
At denotes a set of attributes. The
effective trace is the trace emitted by a
tracer, which is actually ``visible''.
The virtual full trace is a particular case
of effective trace where the attributes At
are the actions at and the parameters St.
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EXAMPLE (effective trace)
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Call: '$call$'(bench(2))
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Call: bench(2)
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Call: 2>0
3
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Exit: 2>0
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Call: _182 is 2-1
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Exit: 1 is 2-1
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Call: bench(1)
....
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INCREMENTAL TRACE
the attributes are such that only the changes
affecting the current state are noted.
et: (t, Deltat+)
where Deltat+ contains the description of the
actions which modify the values of the
parameters at moment t.
To remain a full trace, this trace must satisfy
the following condition:
For every t
(t, at, St+1) can be deduced from (St, Deltat+)
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CLIENT/SERVER
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architecture
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CLIENTS/server
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architecture
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CLIENTS / server
architecture
Workloads are distributed among
•
•
Program (without connections with tracer)
T_prog
Tracer (parameters and attributes computation)
T_core +
T_extract
•
•
Driver (dialog and attributes selection)
T_cond
Broadcasting (all traces encoding)
T_encode-and-com
====================================================
•
•
•
•
Reception (dialog and post-selection)
T_filter
Trace decoding
T_decode
Trace rebuilding
T_rebuild
Analyzer execution
T_ana
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CLIENTS / server
architecture
Process
--------------|
|
T_prog + T_core1
Tracer and Driver
----------------------------------------------|
|
T_core2 + T_cond + T_extract + T_encode-and-com
=========================================================
Analyzer
-----------------------------------------|
|
T_filter + T_decode + T_rebuild + T_ana
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Workload =balance
=
=
=
Process and Tracer
Analyzer
=
=
--------------=
--------=
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=
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=
=
T_ana
T_prog + T_core
=
=
=
=
=
Analyzer
Driver
=
=
--------=
--------=
|
|
|
|
=
=
=
T_cond
T_filter
=
=
=
=
=
Analyzer
=
Tracer
=
=
--------=
--------=
|
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=
=
=
T_extract
T_rebuild
=
=
=
=
=
=
Tracer
Analyzer
=
----------------- =
--------=
=
|
| = |
|
=
T_ encode-et-com =
= T_decode
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OBSERVATIONAL SEMANTICS
Two levels
•Objects level: read the trace (parameters and
attributes description and relationships)
•Trace steps level: understand underlying model
(full state transformations)
It may be a rule semantics (finite number of rules)
a: Condition(S)  S’ := a(S)
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OBSERVATIONAL SEMANTICS
The OS is usually not a complete operational semantics
•Knowing S_t and S_t+1, one rule applies but the
knowledge of S_t is not always sufficient to know which
rules can be applied (to be studied)
•Not all attributes can be formalized in the OS (one
should have a full model of the observed process)
•There may be as many OS than observers
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DRIVER REQUIREMENTS
In addition to the tracer’s work, it must
•Analyze trace queries
•Store and manage requested trace patterns
•Manage the dialog between server (tracer) and clients
(analyzers)
•Tell the tracer what to extract and to broadcast
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GENERAL CONCLUSION :
•Possibility to implement very large virtual full trace without slowing
down excessively the observed process
•More sophisticated analyses will be performed, larger can be the virtual
full trace
•Trace selection and filtering can be very efficient using a tracer driver
•Effective trace size can be reduced by different means: compression
(delta and classical compression) or abstraction (transfer more complex
objects)
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QUESTIONS
•Is a « never more » - extensible full virtual trace possible?
•How to parameterize the compression (to specify the level
of abstraction of communicated objects)?
•Full virtual trace standardization (work on constraint
problems), how? XML effort?
•OS discovery from trace (trace mining), assuming trace
objects are known?
•Consider other fields where the notion of trace is relevant?
•TRA4CP project
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Thank you!
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