osmius 9 - ucmantares.sip.ucm.es/tarot09/index_files/osmius_tarot09.pdf · integrated data...

Osmius 9.07The OpenSource Monitoring Tool

José Luis Marina :: 2009 Osmius 9.07

You can't manage what you can't see.

Introducción::ÍndiceReinforcement Learning Bots

2Osmius 9.07: Professional Monitoring July 2009

What is Osmius?

Osmius allows you to monitor and keep track

of everything connected to a network


3July 2009

What is Osmius?

We've designed Osmius to monitor:Computers and Network devicesApplications and DatabasesUser transactions...

But also:Industrial sensors.Energy consumptions.Pollution levels in the neighbour.Stock shares.Any idea?

Osmius 9.07: Professional Monitoring



Why choose Osmius?

Briefly, with Osmius you can:

Monitor thousands of devices in Real Time. Align IT with the Business (SLA Management). Data Mining and Business Intelligence. Use the power of GIS to see/analyze data. Monitor new “things” in minutes. Send automatic notifications to the staff. Predict Capacity shortages (ITIL). Access ALL the code and documentation.



Who is behind Osmius?

Peopleware: Created in 2000

~ 30 people~ 2,000,000 € Last year billing

Services: Administration, Tuning and IT OperationsSoftware Development. Performance Demanding.Free Open Source Software.Information Security.R&D in collaboration with several Universities.

More:UNEENISO/9001:2000 in IT Consultancy & Operations

PeoplewareFunds to Help R&D

Investments

Technological Partners

Geographic Systems

Business Intelligence

Osmius Partners

InstallationAdministration

SupportTraining

DeploymentDevelopment

MultiplatformInstallers

http://www.sicingenieros.com/

http://www.stratebi.com/



Who is behind Osmius?

Community

In Osmius everything is Open... not just the “core” !!

First Stable version released in July 2008More than 4.000 downloadsSourceForgeRanking : ~ Top 50100


7

MA

AG1

AGn

MA

Osmius 9.07: Professional Monitoring July 2009

Architecture & Tecnology

With Osmius you can:

Monitor thousands of devices in Real Time. Align IT with the Business (SLA Management). Data Mining and Business Intelligence. Use the power of GIS to see/analyze data. Monitor new “things” in minutes. Send automatic notifications to the staff. Predict Capacity shortages (ITIL). Access ALL the code and documentation.

AG1

AGn

Master AgentPoint from which you want to monitor and deploy Agents.You can use 1 to N

MA

AG1

AGn

CS

Central ServerProcess to receive andcorrelate events andto manage all the agents

MySql

SSL

DataBaseOpen and documentedDataModel.Events, SLA, etc

TomCat

J2EE

WebConsoleJ2EE connecting tothe DBase.

InstancesSomething you want tomonitor (Web, DB, Temp)

AgentSpecialized on monitoringspecific instances likeMySQL, Web sites...


8

MA

AG1

AGn

MA

Osmius 9.07: Professional Monitoring July 2009

AG1

AGn

Master AgentC++ & ACEMultiplatformPersistent QueuesFault Tolerant

MA

AG1

AGn

CS

Central ServerC++ & ACE & MySql APIFast insert and CorrelationSecure Comms

MySql

SSL

DataBaseNormalizedExplain everythingStored Procs

TomCat

J2EE

WebConsoleJava J2EESprings – HibernateOpenLayers

InstancesUse APIReuse Connections

AgentC++ & ACEAPI (MySql, Curl,etc)Only new code

Architecture & Tecnology



Concepts: Easy to understand

Instance: Everything you want to monitor.

Instance Type or Class: Defines the kind of questions you can make to the instanceMySQL Database | Windows Server | Exchange

Instance Events: Depending on its type an Instance can receive certain eventsMySQL Database: # Users, Free Space, Kbytes Out,...Parameters: Every 10 seconds – Customized Warning & Critical Threshold

Event 1 :: Database Connections is: 250Event 2 :: Uptime is : 8h 30'

Event 1 :: Time to load Web is : 15 s

Event 1 :: CPU Load is : 80%




Correlation Engine I:The Active Events view should be as clean as possible:

Show only 1 row for repeated events.Automatic clean “bad” events when arrives a “good” one.If Temperature is OK clean previous CRITICAL events.

Active andHistorical

ViewsAccumulateOnly 1 row

Correlation Engine II (*)Identify dependencies between Instances:

If this servers fails DataBase and WebServer also fail.→Manual and automatic identification.


11July 2009


Service: A group of instances joined to offer a service to some usersNormally represents some functional group into your business

The Intranet...Will be down this afternoon from 15:00 to 17:00due to the upgrade of the Oracle Database from 9i to 10gDon't take this unavailability into account in the SLAs

SLA – Service Level Agreement: Defines objectives to your services.

The Intranet cannot be down more than 99.999 of its timeService Working Time

Are we using the Intranet 24x7? Services must accomplish SLAs within their Working Time Osmius also implements: Planned DownTimes



12

Firewall

July 2009


IntranetDB

SLA – Service Level Agreement: Defines objetives to your services.

The Intranet cannot be down more than 99.999 of its time

Service Working Time Are we using the Intranet 24x7?

Services must acomplish SLAs within their Working Time Osmius also implements: Planned DownTimes

IntranetIntranet

GoldGold SilverSilver

eComeCom eMaileMailCRMCRM

99.999 Up99.900 Ok

99.999 Up99.900 Ok


24x7 24x7 24x7

HostMoon

ExchangeServer

Exch.FrontE

WinHost

...

From M to FFrom 9 to 17

SLAManagement

ServiceLevel

Instance &TechnicalLevel

Events sent by the agents

RulesPropagation


13July 2009

Concepts: Easy to Manage


Manage the Configuration: Distribute changes from the console to the distributed agentsDistribute or upgrade agents with one click.

Create your own...Events using your customized scripts and distribute them.Agents: Calling Peopleware or building them yourself using the

Osmius Development Framework.


14July 2009

Integration

How to deal with millions of events? Round Robin Database for the individual events.

You don't need to know wich was the exact CPU load on 01012008 at 8:00.The older the data the lesser the detail you need.


Integrated Data WarehouseSpecific Osmius processes to aggregate daily info (seconds in each state, etc)

Silent ModeEvents in “silent mode” are only sent when there are changes in the Severity.“Send me the Temperature only when it raises 30 C”Prevents network and storage resources starvation.

User Notificacions & SubscriptionsLet Osmius inform you about changes.

email

SMS....

Service Availability Changes

Instance State Change

Subscribe to Reports

Working time

Not Working time

Out of officeJabber

Global Mark

Sending Osmius Event to othersStandalone Agents: Integrate the agents directly with email, Nagios, …Open Tickets automatically using notifications.Send Exchange Critical Events to another Monitoring system.

IntranetIntranet

eCommeComm

Receiving Events from othersWeb ServicesCommand Line Interface

whenusing


15July 2009

Osmius Advantages


Deal with thousands of Instances and millions of events.Integrates SLA management and ITIL best practices.Manage everything from a Central Point.Business Intelligence mining tool.Leverage the power of GIS.Real Open: There is no community downgraded version.You can influence the RoadMap.Well documented. We care about documentation.

16

Introducción

Osmius is supported by:Ministry of Science and Education

Ministry of Industry and TradeCDTI

European Funds

Next Step: Osmius and Passive Testing

What is PasTe?

PasTe: Passive Testing tool.

A library to perform passive testing approach for timedsystems.

Integrated into Osmius as an agent.

The PASsive TEsting tool and Osmius Las Navas del Marques, July 2009 17

Passive testing

In testing, there is usually a distinction between two approaches:

Active testing.

We can interact with the system (apply tests).We have an assesment of correctness before the system isrunning.

Passive testing.

The system is already running.We cannot interact directly with the system.We can observe its traces.

Example

Large systems working 24x7 since this interaction might produce awrong behavior of the system.


Timed Framework I

Specifications0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

Invariantsφ1 = login/option screen/[20, 40], ?/[0,∞],

disconnection 7→ {welcome screen}/[10, 20] B [35,∞]

φ2 = login 7→ {option screen, error user}/[10, 40] B [10, 40]

φ3 = data/profile screen/[10, 20], save 7→ {option screen}/[20, 40] B [35, 50]

φ4 = ?/option screen/[5, 35], marks 7→ {marks screen}/[20, 40] B [30, 70]


Timed Framework II

Implementation

Traces


Time Finite State Machines I

Extension of the classical finite state machine model.

The main difference with FSMs is the addition of time.

M = (S , I,O,Tr , sin)

S is a finite set of states

I is the set of input actions

O is the set of output actions

Tr is the set of transitions

sin is the initial state


Time Finite State Machines II

Transition: tr = (s, s ′, i , o, t)

s, s ′ ∈ S are the initial and final states

i ∈ I is the input action

o ∈ O is the output action

t ∈ IR+ is the time that the transition needs to be completed


Specification of SSadmin

s0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

i1= connecti2= logini3= disconnectioni4= profilei5= datai6= canceli7= savei8= marksi9= register

i10= data subjecti11= save registrationi12= return optiono1= welcome screeno2= option screeno3= error usero4= profile screeno5= marks screeno6= register screeno7= confirm screeno8= no confirmation screeno9= not spected


Usual interaction between a student andSSadmin I

Welcome page

The student wants to connect to the system.

She connects to the web page and the system shows thewelcome screen.

s0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

i1= connecto1= welcome screen


Usual interaction between a student andSSadmin II

Logging into the system

When the student sees the welcome screen she can login into thesystem. If an erroneous login is introduced then the system showsthe error user.

s0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

i2= logino2= option screeno3= error user


Usual interaction between a student andSSadmin III

Interaction

If the student introduces a correct login, then the system willshow the option screen (in 30 seconds).

If the student wants to disconnect, then she only has to pressdisconnection and SSadmin returns to thewelcome screen (in 15 seconds).

s0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

i2= logini3= disconnectiono1= welcome screeno2= option screen


Specifying properties: Invariants

Each time that a user applies a and observes z and the time required by thetransition verifies the restriction p.

Some actions are performed and the time required verifies the time restriction p.

If after performing some operations the user inputs i then he must observe andoutput in O, the time required by this transiction satifies the restriction p andthe time for all the sequence satisfies the restriction t.

Formal Definition of Invariants

φ is defined according to the following EBNF:

φ ::= a/z/p, φ |

? /p, φ′ | i 7→ O/p B tφ′ ::= i/z/p, φ | i 7→ O/p B t

p, t ∈ IR, i ∈ I, a ∈ I ∪ {?}, z ∈ O ∪ {?}, and O ⊆ O.








φ ::= a/z/p, φ | ? /p, φ′ |

i 7→ O/p B t

φ′ ::= i/z/p, φ | i 7→ O/p B t









φ ::= a/z/p, φ | ? /p, φ′ | i 7→ O/p B tφ′ ::= i/z/p, φ | i 7→ O/p B t



Invariant φ1

If we see in the log the input login followed byoption screen and an amount of time included in [20,40],...

and we observe any sequence of input/output/time and thenthe input disconnection ...

... then if we observe disconnection we have to see theoutput welcome screen in an amount of time belonging to[10, 20].

... In addition, the sum of all time values observed from thelogin until the welcome screen output belongs to [35,∞].

Invariant

φ1 = login/option screen/[20, 40],

? /[0,∞], disconnection7→ {welcome screen}/[10, 20]B [35,∞]


Invariant φ1





Invariant

φ1 = login/option screen/[20, 40],? /[0,∞], disconnection

7→ {welcome screen}/[10, 20]B [35,∞]


Invariant φ1





Invariant

φ1 = login/option screen/[20, 40],? /[0,∞], disconnection7→ {welcome screen}/[10, 20]

B [35,∞]


Invariant φ1





Invariant

φ1 = login/option screen/[20, 40],? /[0,∞], disconnection7→ {welcome screen}/[10, 20]B [35,∞]


Invariant φ2

After observing any occurrence of login in the log,

then we have to observe option screen or error user.

The amount of time associated with this input/output mustbelong to the time interval [10, 40].

Invariant

φ2 = login

7→ {option screen, error user}/[10, 40] B [10, 40]


Invariant φ2




Invariant

φ2 = login 7→ {option screen, error user}

/[10, 40] B [10, 40]


Invariant φ2




Invariant



Invariant φ3

After inserting the last change into the profile screen,

and after saving the current state of the system, theoption screen

and the time associated with these operations are included inthe intervals [10, 20] and [20, 40] respectively.

In addition, the total amount of time to perform this activitymust belong to the interval [35, 50].

Invariant

φ3 = data/profile screen

/[10, 20], save 7→ {option screen}/[20, 40] B [35, 50]


Invariant φ3





Invariant

φ3 = data/profile screen

/[10, 20]

, save 7→ {option screen}

/[20, 40] B [35, 50]


Invariant φ3





Invariant

φ3 = data/profile screen/[10, 20], save 7→ {option screen}/[20, 40]

B [35, 50]


Invariant φ3





Invariant



Invariant φ4

When the student is in the option screen (after any input),

if she inserts the input interaction marks, then themarks screen will appear within 20 and 40 time units.

All the interaction must take between 30 and 70 time units.

Invariant

φ4 = ?/option screen/[5, 35],

marks 7→ {marks screen}/[20, 40] B [30, 70]


Invariant φ4




Invariant

φ4 = ?/option screen/[5, 35],marks 7→ {marks screen}/[20, 40]

B [30, 70]


Invariant φ4




Invariant

φ4 = ?/option screen/[5, 35],marks 7→ {marks screen}/[20, 40] B [30, 70]


Algorithm: Correctness of invariants

Input: M = (S, I,O,Tr, sin), φ = {a1, . . . , an−1, in 7→ M} // either ak = ik/ok/Fk or ak = ?Output: Bool.I ′ ← I ; S′ ← S ; j ← 1; S′′ ← ∅; error ← false;

While (j < n)If (Head(I ′) = ?)

While (S′ 6= ∅)Choose s ∈ S′ S′ ← S′ \ {s}S′′ ← S′′ ∪ afterInp{s, ij+1}

elseWhile (S′ 6= ∅)

Choose sa ∈ S′ S′ ← S′ \ {sa}Tr′ ← afterCond{sa, ij , oj}

While(Tr′ 6= ∅)Choose (sa, sb, ij , oj , F ′) ∈ Tr′

Tr′ ← Tr′ \ {(sa, sb, ij , oj , F ′)}If(F ′ = Fj ) then S′′ ← S′′ ∪ {sb}

I ′ = Tail(I ′) j ← j + 1; S′ ← S′′; S′′ ← ∅;

If (S′ = ∅) error ← true

While (S′ 6= ∅)Choose sa ∈ S′ S′ ← S′ \ {sa} Tr′ ← afterCond{sa, in, ?}While(Tr′ 6= ∅)

Choose (sa, sb, in, o, F ′) ∈ Tr′ Tr′ ← Tr′ \ {(sa, sb, in, o, F ′)}If (〈o, F ′〉 ∈ M)

S′′ ← S′′ ∪ {sb}else error ← true

If (S′′ = ∅) then error ← trueReturn (¬error)


Global view, specification, invariant,implementation, and logs

Specifications0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80






m

Implementation

Traces


Global view, specification, invariant,implementation, and logs

Do not have a fullspecification

Partialspecification.

Only interested insome properties.






m

Implementation

Traces


Trace files

Since we assume that we have TFSM, logs will follow this pattern:

Input1/ Output1/ Time1,Input2/ Output2/ Time2,. . .

Inputn/ Outputn/ Timen

Trace


Algorithm: Correctness of traces with res-pect to invariants

Theorem

Let S (a specification) and I (animplementation) be two Timed FiniteState Machines,

Let φ be a correct timed invariant withrespect to S .

Let e be a log recorded from I .

If the invariant φ does not match e then I doesnot conform to S .


Core of PasTe

Invariants

Correctspec?

Spec

File

Correcttrace?

Traces


Core of PasTe

InvariantsCorrectspec?

Spec

File

Correcttrace?

Traces


Classification of different Invariant Suites

Specifications0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

⇔

Invariant Suite 2φ2 = login 7→ {option screen, error user}/[10, 40] B [10, 40]


Invariant Suite 1φ3 = data/profile screen/[10, 20], save 7→ {option screen}

/[20, 40] B [35, 50]


Question

Which one do we prefer? Invariant Suite 1 or Invariant Suite 2?


Mutants: Evaluating invariants I

Mutants are produced from the specification.

We generate traces from mutants.

An invariant suite is better if it kills more mutants.


Mutants: Evaluating invariants II

Specifications0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

ApplyingMutation ⇒Operators

Mutant 1s0s1

s2s3

s4

s5

s6s7

i1, o3, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

...

Mutant ns0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 25

i10, o6, 15

i11, o7, 80i11, o8, 80


Mutants: Evaluating invariants III

Changing an output

qa

qb

qc

a,x,1b,y,2

a,x,3

b,x,2

b,z,1a,y,3

qa

qb

qc

a,x,1b,y,2

a,y,3

b,x,2

b,z,1a,y,3


Mutants: Evaluating invariants IV

Changing the target state in a transition

qa

qb

qc

a,x,1b,y,2

a,x,3

b,x,2

b,z,1a,y,3

qa

qb

qc

a,x,1

b,y,2

a,y,3

b,x,2

b,z,1a,y,3


Mutants: Evaluating invariants V

Altering the time value

qa

qb

qc

a,x,1b,y,2

a,x,3

b,x,2

b,z,1a,y,3

qa

qb

qc

a,x,1b,y,2

a,x,3

b,x,17

b,z,1a,y,3


Core of PasTe

InvariantsCorrectspec?

Spec

Mutants

Traces

FileCorrecttrace?

generate

extract


Integration into Osmius

Masteragent

OsmiusLog Agent

PasTedaemon

Log fileImpl. traces


Running Example I

Mutant of SSadmin specification executing in real time.

Paste daemon detecting periodically errors in the trace of themutant.


Running Example II

Specification

TFSM

q0

q0 CONNECT WELCOMESCREEN 10 q1

q1 LOGIN ERRORUSER 30 q1

q1 LOGIN OPTIONSCREEN 30 q2

q2 DISCONNECTION WELCOMESCREEN 10 q1

q2 PROFILE PROFILESCREEN 20 q3

q2 MARKS MARKSCREEN 30 q4

q2 REGISTER REGISTERSCREEN 200 q5

q3 DATA PROFILESCREEN 10 q3

q3 SAVE OPTIONSCREEN 30 q2

q3 RETURNOPTION OPTIONSCREEN 10 q2

q3 RETURNOPTION NOTSPECTED 10 q2


q5 DATASUBJECT REGISTERSCREEN 10 q6


q6 DATASUBJECT REGISTERSCREEN 10 q6

q6 SAVEREGISTRATION CONFIRMSCREEN 80 q7

q6 SAVEREGISTRATION NOCONFIRMSCREEN 80 q7




Running Example III

Invariants

INVARIANTSI

LOGIN OPTIONSCREEN [ 20 40 ] , * [ 0 -1 ] ,

DISCONNECTION - < WELCOMESCREEN > [ 10 20 ] - [ 35 -1 ]

LOGIN - < OPTIONSCREEN , ERRORUSER > [ 10 40 ] - [ 10 40 ]

DATA PROFILESCREEN [ 10 20 ] , SAVE - < OPTIONSCREEN > [ 20 40 ] - [ 35 50 ]

? OPTIONSCREEN [ 05 35 ] , MARKS - < MARKSCREEN > [ 20 40 ] - [ 30 70 ]


Running Example IV


Current work

Planned applications

Analyze implementations of the Optimized Link State RoutingProtocol (OLSR). No formal specification(http://www.ietf.org/rfc/rfc3626.txt) currentresearch with Professor Ana Cavalli research group(Department of Network Software, TELECOM &Management SudParis).

Intrusion detection system (IDS). Invariants to expressbehavioral patterns of crackers, malware and/or disgruntledemployees.


http://www.ietf.org/rfc/rfc3626.txt

Current work I

Planned applications

Analyze implementations of the Optimized Link State RoutingProtocol (OLSR). No formal specification(http://www.ietf.org/rfc/rfc3626.txt) currentresearch with Professor Ana Cavalli research group(Department of Network Software, TELECOM &Management SudParis).

Intrusion detection system (IDS). Invariants to expressbehavioral patterns of crackers, malware and/or disgruntledemployees.


http://www.ietf.org/rfc/rfc3626.txt

Current Work II

Methods to extract a set of invariants

Extract⇒

Invariant Suite

φ1

. . .

φn

If we have a complete formal specification we have to checkthe correctness of the proposed invariant suite.

If we do not have a complete formal specification we assumethat the invariant suite is correct.


Current Work III

Specifications0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

Extract⇒

Invariant Suite

φ1

. . .

φn

We automatically derive invariants from the specification...but there are a lot!!


Current Work IV

Specifications0s1

s2s3

s4

s5

s6s7

i1, o1, 15

i2, o2, 30

i2, o3, 30

i3, o1, 15

i4, o4, 25i8, o5, 30

i9, o6, 200

i7, o2, 30

i5, o4, 15

i10, o6, 15

i10, o6, 15

i11, o7, 80i11, o8, 80

+

User Model

⇒

InvariantSuite

φ1

. . .

φn

We automatically derive invariants from the specification.

We combine this technique with other formal approaches likeusers models in order to obtain a relevant set of behaviours.


Current work V

Develop a native Osmius agent

Masteragent

OsmiusLog Agent

PasTedaemon

Log fileImpl. traces

OsmiusPasteAgent


Current work VI

Develop a native Osmius agent

Masteragent

OsmiusLog Agent

PasTedaemon

Log file

Impl. traces

OsmiusPasteAgent


References

Osmius http://www.osmius.net

Paste http://kimba.mat.ucm.es/paste/


http://www.osmius.net

http://kimba.mat.ucm.es/paste/

Publications

amn08b C. Andres, M.G. Merayo, and M. Nunez. Passive testing of timed systems. In 6th Int.Symposium on Automated Technology for Verification and Analysis, ATVA’08, LNCS 5311,pages 418–427. Springer, 2008.

amn09b C. Andres, M.G. Merayo, and M. Nunez. Formal correctness of a passive testing approachfor timed systems. In 5th Workshop on Advances in Model Based Testing, A-MOST’09 .IEEE Computer Society Press, 2009.

amn09c C. Andres, M.G. Merayo, and M. Nunez. Using a mining frequency patterns model toautomate passive testing of real-time systems. In 21st Int. Conf. on Software Engineeringand Knowledge Engineering, SEKE’09. Knowledge Systems Institute, 2009.

amn09d C. Andres, M.G. Merayo, and M. Nunez. Supporting the extraction of timed properties forpassive testing by using probabilistic user models. In Submitted to QSIC’09, 2009.

alr09 C. Andres, L. Llana, and I. Rodrıguez. Formally transforming user-model testing problemsinto implementer-model testing problems and viceversa. Journal of Logic and AlgebraicProgramming, pages 425-453, 2009.

amm09 C. Andres, M.G. Merayo, and C. Molinero. Advantages of mutation in passive testing: Anempirical study. In 4th Workshop on Mutation Analysis, Mutation’09. IEEE ComputerSociety Press, 2009.

amn09 C. Andres, M.G. Merayo, and M. Nunez. Passive testing of stochastic timed systems. In 2ndInt. Conf. on Software Testing, Verification, and Validation, ICST’09, pages 71–80. IEEEComputer Society Press, 2009.


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