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000-646 - Rational Manual Tester - BrainDump Information

Vendor Name : IBM
Exam Code : 000-646
Exam Name : Rational Manual Tester
Questions and Answers : 50 Q & A
Updated On : October 18, 2018
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000-646 exam Dumps Source : Rational Manual Tester

Test Code : 000-646
Test Name : Rational Manual Tester
Vendor Name : IBM
Q&A : 50 Real Questions

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New Open source ERP Suite Written In ILE RPG | killexams.com Real Questions and Pass4sure dumps

October 15, 2018 Alex Woodie

There’s whatever thing fairly novel being introduced these days on the Fall commonplace convention in Pittsburgh: An open supply ERP equipment written in free-kind RPG. Dubbed intERPprise, the application undertaking is supposed to harness core IBM i strengths – its built-in database and ILE environment – but primarily, deliver an illustration for what contemporary and native open supply software can appear to be on IBM i.

The intERPrise venture (www.i-nterprise.org) become spearheaded through a bunch of IBM i advocates, together with Chris Hird and Marinus van Sandwyk, who wanted to demonstrate what a modern business software would appear to be – and chiefly, what a modern application may do – on the IBM i platform.

“We wanted something that we may get the frequent RPG developer worried in and in fact get them to start modernizing their functions from the ground up, as an alternative of inserting flashy front-ends over databases which are, to say the least, suspect in loads of circumstances,” says Chris Hird, the president of look after advanced options in Ontario, Canada. “We desired to delivery from scratch and construct this as a very good, strong application that truly suggests the place the IBM i shines, it's, its database and its RPG atmosphere and ILE.”

The intERPprise challenge presently carries core fiscal modules, including everyday ledger, cashbook, debts payable, and accounts receivable. anyone can down load the application, which is at the moment in alpha, and use it freely below an Apache 2 license. The assignment founders intend for different IBM i ILE developers to construct upon the bottom and doubtlessly present different modules (such as for manufacturing, and many others.) which can be also open supply or offered below a top rate distribution model. The venture should be maintained on GitHub.

The enterprise logic in the back of the product is based on the data-logic ERP gadget from Axiom systems, a South African company that developed in the Synon 2E fourth-era language (4GL) atmosphere and compiled it as RPG III code. The company common sense expressed in Axiom’s Synon fashions changed into “harvested” using tools from van Sandwyk’s TEMBO expertise Lab and re-generated as new free-kind ILE RPG objects that govern the software from within the Db2 for i database.

“all the validations are enforced by the use of triggers within the database, all of the ensuing processing is finished via means off alter trigger, and all of the relationships are enforced by way of constraints,” says van Sandwyk, who's CEO and founding father of South Africa-based mostly TEMBO and a staunch recommend for adoption of the model-view-controller (MVC) architectures and, certainly, modernizing monolithic RPG code stacks via re-engineering it to work within Db2 i’s enforcement paradigms and to leverage its SQL question Engine, which is used by intERPrise.

“So there’s complete and absolute separation between the database and a really thin what we call orchestrator layer that some people will confer with as your controller, and then definitely rendering JSON as the preliminary birth mechanism,” van Sandwyk says. “We do not intend to assist display info in any method shape or kind. It’s completely separation, and we’ll render a JSON payload that can also be consumed via different features on other platform or an HTML net web page.”

The group is working with Healdsburg, California-based mostly e-PFR applied sciences and its IBM i-primarily based iWebSrv product to carry a graphical interface for intERPrise the usage of the JSON output.

The ILE point of intERPrise cannot be overstated, says Hird, who has criticized IBM’s open supply approach, which leans heavily on porting purposes, tools, and technologies from Linux to run on IBM i under its AIX-based mostly PASE runtime environment.

“They’re doing ports to AIX and then it runs in PASE. unfortunately there’s loads of stuff that just doesn’t work naturally in PASE, and we’re not taking expertise of any of the IBM i’s strengths, which is its built-in database and ILE,” Hird says. “PASE doesn’t talk very well to Db2. It’s now not connected between PASE and Db2, so any open supply that you simply download for PASE is written for Linux and Linux functions commonly don’t have a Db2 database. And if it does, it tends no longer to be open supply because IBM doesn’t ship Db2 within the open source market.”

Hird, who developed his HA4i utility basically in the ILE C environment, emphasised that, by means of pushing the free-kind ILE RPG good judgment into the database with intERPrise, better enterprise effects will emerge for the company that makes use of it.

“We’re pushing the enterprise common sense into the database, and asserting, ‘adequate then, we’re not going to let anything contact that records except it follows those constraints and people drivers, and that capability we’re now not going to get bad records in the database,'” he says. “if you depart it in the software degree, the software developer can say, ‘good enough, I’m going to push this facts into the database because it can healthy. i can shove binary statistics into a character container, and it'll save it.’ If we put constraints in, it gained’t allow it to take place. it'll say, no that doesn’t in shape our standards.”

Van Sandwyk stressed that he has no hobby in the industrial advantage of intERPrise, and that his intention is to aid the IBM i neighborhood see what up to date applications on the platform can appear to be. “We have not even touched the commercialization of this,” he says. “this is actually a present to the neighborhood when it comes to what we trust a new native IBM i software should still look like.”

Too many IBM i stores are combating just conserving legacy code, not to mention considering re-architecting their methods the usage of enhanced concepts, reminiscent of MVC and records-driven building paradigms, similar to Synon 2E, which Van Sandwyk keeps changed into a long time forward of its time.

“It come again to old dialogue – why the heck would I buy a Rolls Royce and drive it round like a scotch cart,” van Sandwyk says, the use of a South African time period for a wheelbarrow. “We believe so a good deal within the platform, let’s leverage its inherent strengths, as a result of we comprehend that we can deliver business transaction processing at a fraction of the charge different structures can do, with a level of protection and a level of integration that the other platforms can best dream about.”

The plan requires intERPrise to development from alpha to beta code over the next six month, and emerge as a frequently accessible product next spring, in time for regular’s POWERUp convention in Anaheim, California. The code remains quite pliable for the time being, and the structure may exchange between now after which, which is why undertaking supporters wish to get the enter of alternative IBM i developers and architects.

what will not trade, however, is the decision to demonstrate the IBM i world what a contemporary and native IBM i application can do.

“We’re making an attempt to get a grassroots circulation to say, this is how it should still be written,” Hird says. “The fact that it’s open supply potential that you could take it and you can comply with that same pattern for your own construction.”

displaying ILE builders – most of whom code in RPG – that an open supply venture IBM i doesn’t have to mean falling down the PASE rabbit gap is an additional purpose.

“We’re trying to deliver to lots of people who understand RPG and nothing else the ability to construct whatever special from the ground up,” Hird says. “this is simply the start. this is the alpha free up, which is just going to be the core in it. we will advance that extra earlier than the popular unlock at standard subsequent 12 months, however it all depends on what americans should see, and what you need to do.”

related experiences

more Transparency obligatory For Open supply working on IBM i

Native Open source: Why It’s Time for IBM i


provider Stubbing With JMeter and Docker | killexams.com Real Questions and Pass4sure dumps

in this article collection about Docker (with JMeter, distributed, IBM MQ and Cloud) I described how Docker adoption simplifies the efficiency testing process with Apache JMeter™ and makes it more authentic. These benefits are acquired thanks to the flexibility of container virtualization, it's a key function of Docker.

listed here, i will be able to present another Docker applicability to efficiency testing: carrier stubbing with Docker containers. through replicating dependencies through stubbed capabilities, testers can overcome the challenges dependency systems create to their check method: fragility, instability, and greater. listed here i'll demonstrate how to try this with Docker, and with JMeter to duplicate the provider. Then, which you could use JMeter as the checking out device.

You should be would becould very well be shocked how stubbing will also be combined with Docker, but in the article i'll introduce the crucial ideas and some useful examples. Let's get begun.

carrier Stubbing for efficiency checking out: An Introduction

With the expanding complexity of testing projects, further and further testing flows of the equipment below verify are impacted by way of dependency gadget(s). when I say "dependency equipment" i'm relating to:

  • A legacy system no longer littered with present building
  • a 3rd birthday party service that belongs to yet another company
  • A equipment developed with the aid of your corporation with an doubtful roadmap
  • The presence of dependency methods brings every manual or automatic trying out task in a condition like the one described in the picture below.

  • testing Actors - within the diagram i am displaying a checking out project that stress tests the device beneath test to validate its exceptional in alternative ways, both manually and with automation.
  • device below test (SUT) - a complex architecture composed of heterogeneous services and infrastructure that implement a company requirement.
  • extra methods - these features collaborate with the closing utility however are out of the mission management scope. maybe, a few of their necessities are doubtful. These are the dependencies.
  • within the picture above it's important to center of attention on the arrows too. These arrows describe the techniques' perimeters and the interfaces used to change messages/information:

  • The crimson arrow symbolizes the examine specification that is run within the testing tool (JMeter during this case).
  • The grey arrow symbolizes that there is a relationship of functionality that the tester knows little about. This could potentially waste your time, in case you be mindful too late that dependencies broke your verify logic. So, plan in advance, find out about the dependencies, stub them, boost your plan and proceed with the test.
  • The presence of dependency systems can produce a series of unpleasant consequences all the way through the checking out assignment (both for guide and computerized trying out):

  • Fragility - the examine becomes more fragile with the increasing variety of uncontrolled dependencies, since you may get a failed look at various when the difficulty is with the dependency and not the SUT, rendering the check unreliable.
  • Instability - dependencies can deliver the gadget down when the SUT is up, affecting the verify effect devoid of a transparent correlation to the SUT.
  • Time consuming - developing look at various statistics might also take days/weeks and or not it's doubtlessly error-prone.
  • Unavailability - the trying out group can also spend time looking forward to the availability of dependencies programs.
  • Frustration - the human factor of the remember:
  • Testers - you could suppose pissed off because you cannot do your job easily
  • Managers - you could think pissed off because your crew wastes time as a result of its work is blocked
  • To get rid of, or incredibly cut back, these consequences, one answer is to decouple the test system completed on the SUT from the uncontrolled dependencies. a technique to decouple is adopting stubbed interfaces, with the goal of replicating the behaviour of dependencies. in this manner, the checking out method does not stumble upon unpredictable behaviour as it would with the common dependencies equipment. accordingly, the look at various perimeter will now consist of the stub capabilities as a result of they're part of testing system. So, we can add a new endpoint to the checking out perimeter in our diagram.

    To create stubbed interfaces in out verify plan we deserve to:

  • Add a new device known as a stub service that replicates the interface to be stubbed
  • define which calls should be stubbed in line with the deliberate verify method
  • understand that the stub is a part of the verify suite and is included within the look at various perimeter
  • within the graphic above I delivered a new entity, a stub service, into the trying out perimeter. The stub service acts like the normal dependency when queried, most effective it answers with selected messages coherent to the trying out scopes. A stub can reproduce each practical features, as well as non-purposeful qualities, akin to response instances or gradual connections.

    Let's consider the circulation of the message/information alternate:

  • The red arrow has the same feature to the previous photo with a little change: the testing group has produced a precondition with the stub and the SUT
  • The green arrow - is the stubbed interface that reproduces a subset of all feasible requests/responses from the precise dependencies equipment. How do you decide which requests/responses you'll want to stub? This depends upon two components:
  • checking out insurance - the testing group need to assure the high-quality of the SUT. This purpose is finished by the use of verify insurance. extra check insurance requires extra complex stubbing.
  • Stub setup effort - The checking out crew is answerable for constructing stubbed interfaces and protecting them. So, supplies must be allocated for this reason. this is important to have in mind as a result of some stubs may also be complicated to hold and the effort can become vastly sudden compared to the usual trying out plan.
  • Concluding this section: stubbing might possibly be the important thing to the success of a complex testing undertaking.

    Virtualization as a Shortcut for carrier Stubbing

    constructing a stub provider require big planning and implementation efforts. every so often, undertaking members adopt quick and soiled options to speed up the application lifecycle activities. They expect they will need a short period of stub usage (e.g. constructing one feature, checking out one feature). a brief and dirty solution is captivating nevertheless it tends to:

  • Have a short lifecycle with none guarantee of reproducibility over time.
  • Be used by using only 1 ambiance, typically the one where it's developed.
  • simple stub options are according to difficult coded and/or parameterized data. There are greater advanced stub functions, according to a data model answer. A setup of stub features turns into greater complicated and sometimes requires relevant practising, however obtaining stubbed features is greater recommended for a challenge with a wider ambition.

    listed here, we will describe the way to put into effect a stub provider the usage of a virtualization service. obtaining a virtual stub provider provides stub isolation from the relaxation of the ambiance. in addition, a virtual stub carrier enables migrating the stub provider over networks in situations when:

  • Departments require sharing stubs so they can collaborate and work with the same references right through subsystem building.
  • or not it's required to improve the stub provider infrastructure (e.g. computational load and bandwidth) right through testing (e.g. efficiency checking out).
  • The virtual stub provider will also be created using a virtualization layer. we can use a virtualization according to Docker, because Docker makes it feasible to execute a stub in an remoted context that reproduces handiest the necessary elements.

    Docker-primarily based Stub functions

    Docker presents the possibility to setup a stub carrier with ease and with a high degree of reliability. As we described in old articles, the possibility to reproduce up to now configured behaviour is reasonably instantaneous in Docker. additionally, the virtualization layer creates an isolation that executes the stubbed interfaces as an exterior provider.

    Now it's time for some examples for you to train us the way to do it. i will be able to latest two containers, and a stub selected service interface for every one. The proposed examples are my own: they use self assigned requirements with none correlation to a industrial situation.

    SUT: large information, Stub: records supply in keeping with S3 (illustration 1)

    in this illustration, we're required to deploy a stub for a data source in keeping with an S3 bucket that generates continuous statistics. This statistics may also be characterised in accordance with velocity, diversity, and volume. a possible SUT target for this stub is a large records software.

    Our examine necessities for this illustration stub are:

  • The stub generates the defined kB dimension of random chars as a S3 object
  • The stub uploads a new S3 object periodically
  • The stub sends the generated S3 object to assigned bucket
  • by way of inspecting these necessities we will extract parameters that we add to the stub implementation to customise our stub habits at boot time:

  • kbSize - the kB size of each object generated
  • sheetAtMinute - the indication of how many objects are uploaded each and every time
  • bucket - describes the target bucket name
  • With the defined interface parameters and the anticipated output behaviour, we are able to proceed with the stub architecture definition. we can undertake Docker as stub useful resource manager and break up our stub into three sub-techniques:

  • A Minio server container to reveal the S3 interface to the SUT
  • A JMeter container that runs in non-GUI mode to generate an information move
  • A community configured by the use of Docker so containers can speak and the SUT can see the bucket externally.
  • The last stub design is introduced in the photo above. This design assumes that the stub is queried through the testing method to check trying out desires (e.g. determine a file file in the bucket).

    Stub Code

    As always, right here is the code of the described software. that you could additionally discover it on GitHub. For this stub see the example code observed in the "s3-stub" folder.

    $DO_TOKEN="your-digitalocean-token" $MACHINE_NAME="my-desktop" docker-desktop create ` --driver=digitalocean ` --digitalocean-access-token=$DO_TOKEN ` --digitalocean-measurement=1gb ` --digitalocean-place=ams3 ` --digitalocean-inner most-networking=genuine ` --digitalocean-picture=ubuntu-16-04-x64 ` $MACHINE_NAME $MACHINE_IP = ((docker-computing device ip $MACHINE_NAME) | Out-String).trim() & docker-desktop env $MACHINE_NAME --shell powershell | Invoke-Expression

    This PowerShell code creates a Docker laptop while contemplating hardware necessities and the machine region (this may also be an additional requirement for our stub). within the end, the code extracts the real machine IP address and configures its present shell to execute the subsequent Docker command on the newly created Docker machine.

    Please notice: carrier stubbing frequently requires simulating a service observed over a community (e.g. local community, corporate network, international), so we need to be organized for a circumstance the place the stub vicinity may also be "rented" on the Cloud.

    $SUB_NET="172.18.0.0/16" $STUB_NET="mydummynet" docker community create ` --subnet=$SUB_NET $STUB_NET

    This code creates a custom Docker community where the containers our stub is composed of might be positioned. Please observe: the whole community and the connected containers are invoked on the native desktop, however completed on a remote computer because of the "env" command.

    $accessKey="AKIAIOSFODNN7EXAMPLE" $secretKey="wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY" docker extent create s3data docker extent create s3conf docker run ` -p 9000:9000 ` --detach ` --identify minio ` --env "MINIO_ACCESS_KEY=$accessKey" ` --env "MINIO_SECRET_KEY=$secretKey" ` --web $STUB_NET ` -v s3data:/statistics ` -v s3conf:/root/.minio ` minio/minio server /data

    This code units up a Minio server container, which takes the role of the S3 interface for our stub. The code steps are carried out in right here order:

  • Defining entry/secret keys as required to interact with the S3 bucket.
  • creating two Docker volumes that backup the Minio server configuration and the facts, in case of a container crash. it's helpful to post crash analyses.
  • creating a container in indifferent mode with the defined configuration.
  • $MACHINE_KEY="$env:HOMEPATH/.docker/computing device/machines/$MACHINE_NAME/id_rsa" # this command offers quintessential jar for Minio scp -o StrictHostKeyChecking=settle for-new ` -i $MACHINE_KEY ` ../../minio-4.0.2-all.jar root@$MACHINE_IP:~ scp -o StrictHostKeyChecking=accept-new ` -i $MACHINE_KEY ` ./script.jmx root@$MACHINE_IP:~ docker run ` --detach ` --identify jmeter ` --env "JMETER_USER_CLASSPATH=/root/" ` --env "MINIO_ACCESS_KEY=$accessKey" ` --env "MINIO_SECRET_KEY=$secretKey" ` --quantity /root/:/root/ ` --internet $STUB_NET ` vmarrazzo/jmeter ` -n -t /root/script.jmx

    in the final a part of the PowerShell code, we launch a JMeter container in indifferent mode. This container executes the common sense of periodically uploading a new S3 object to the bucket. before container execution or not it's indispensable to upload right here on the Docker computing device by way of the scp command:

  • minio-4.0.2-all.jar - a crucial library for executing Groovy code in a JMeter script
  • script.jmx - the JMeter script with the stub common sense (e.g. scheduling and object advent)
  • The picture above suggests the examine plan constitution of the JMeter script used for stub. This script

  • Takes stub arguments from the Docker run command.
  • Establishes a connection with the Minio server by the use of its Java API.
  • Periodically iterates the generation of a random S3 object and its upload on an outlined bucket.
  • For implementation details, see the Groovy code dedicated on GitHub. When stub containers are operating, it's possible to navigate over the bucket by way of the web through the use of the Docker computing device IP handle at port 9000.

    that you may now create your JMeter script for load trying out the software.

    SUT: software, Stub: IBM MQ Endpoint (example 2)

    This example covers messaging-oriented middleware by way of displaying how to stub an IBM MQ based mostly utility. the key elements that signify this middleware are asynchronicity, routing, and transformation. applications like IBM MQ are tremendously adopted the place it's necessary to facilitate message change with a typical API.

    The remaining stub can simulate a remote endpoint that the SUT sometimes queries all the way through the verify undertaking. This situation creates an advanced test and stubbing will also be a superb answer in an inexpensive period of time.

    As already seen in the previous instance, we have test requirements that define how the stub works:

  • IBM MQ version and its configuration
  • pattern message request received through the SUT
  • sample message response to be despatched to the SUT
  • inspecting these requirements, we should involve extra colleagues to unravel the advantage gap quintessential to setup our stub. In particular:

  • sysadmin - to identify the utility version and its configuration (e.g. TLS config)
  • developer - to attain a pattern edition of messages, like these:
  • Image title

    After an inquiry session and a sequence of "basic, my pricey Watson" we can adopt a stub architecture that has three subsystems (once again):

  • IBM MQ container to expose MQ interfaces to SUT
  • client/Producer request/response logic into ad hoc container in keeping with custom Java code
  • network configured via Docker, so the containers can speak and the SUT can see the bucket externally
  • The closing stub design is introduced within the graphic above. This design assumes that the stub is probably queried by using the testing procedure to verify the testing goals (e.g. verify queue stats).

    Stub Code

    earlier than describing the code it be quintessential to provide a technical description of the stub and its containers. In element:

  • IBM MQ container is in keeping with the picture "vmarrazzo/wmq" already viewed in the previous article. it's an IBM MQ V9 with two queue managers that differ to channel encryption with/with out TLS security. in this example we think that the SUT communicates with TLS safety and we now have the encryption key.
  • The "java-stub" is a customized project developed in Java, which interacts IBM MQ to the stubs anticipated MQ habits. This project makes use of Apache Maven as a build toolchain so it is positive to reuse Maven for our Docker container. The Maven graphic is beneficial for executing Maven goals in the isolated ambiance in keeping with the Docker container.
  • right here is the code of the described software. The code described during this paper is available on GitHub. For this stub see the example code located within the folder "ibmmq-stub".

    $MACHINE_KEY="$env:HOMEPATH/.docker/laptop/machines/$MACHINE_NAME/id_rsa" # this command uploads fundamental TLS for IBM MQ scp -o StrictHostKeyChecking=settle for-new ` -i $MACHINE_KEY ` ./my-cert.pfx root@$MACHINE_IP:~ # this command uploads integral TLS for Java Stub scp -o StrictHostKeyChecking=settle for-new ` -i $MACHINE_KEY ` ./my-cert.jks root@$MACHINE_IP:~ # this command uploads Java Stub source code scp -o StrictHostKeyChecking=settle for-new ` -i $MACHINE_KEY ` -r ./java-stub root@$MACHINE_IP:~ $destPath="~/java-stub/localrepository/com/ibm/com.ibm.mq.allclient/9.0.4.0" # this command provides jar for IBM MQ scp -o StrictHostKeyChecking=settle for-new ` -i $MACHINE_KEY ` <your_path>/com.ibm.mq.allclient-9.0.four.0.jar ` root@$MACHINE_IP: $destPath

    The above code is a compulsory precondition for container execution and it includes:

  • A keystore in PKCS #12 archive layout (pfx) for a TLS channel on IBM MQ
  • Java keystore (jks) required by Java stub to tackle IBM MQ messages
  • The "java-stub" source code undertaking that implements stub good judgment
  • The Java driver for the IBM MQ required by way of "java-stub" code
  • $QM_VOLUME_NAME="qm1data" $ks_file="my-cert.pfx" $ks_pass="changeit" docker quantity create $QM_VOLUME_NAME docker run ` --env MQ_TLS_KEYSTORE=/var/ks/$ks_file ` --env MQ_TLS_PASSPHRASE=$ks_pass ` --post 1415:1415 ` --put up 9443:9443 ` --name wmq ` --detach ` --net $STUB_NET ` --extent $QM_VOLUME_NAME:/mnt/mqm ` --quantity /root/:/var/ks ` vmarrazzo/wmq

    This code area is quite similar to the one already viewed in IBM MQ in the outdated Docker article. So after this Docker runs the command, a container is run with an IBM MQ example inner with a TLS channel on the 1415 socket.

    docker extent create --name maven-repo docker run ` -it --rm ` --internet $STUB_NET ` -v /root/:/decide/maven ` -v maven-repo:/root/.m2 ` -w /decide/maven ` maven:three.5-jdk-10 ` mvn clean collect exec:java -DIBMMQ_HOST=wmq

    here's the closing PowerShell part and it's related to the execution of a Maven container. This Docker runs a command that executes the stub leading classification by using a venture file descriptor referred to as a pom file. additionally:

  • The container is performed in a created network where IBM MQ is running
  • The container receives the IBM MQ container name as input, so the Docker network resolves this name with the IP handle container
  • After the execution of Docker run instructions, the resulting stub is able to be engaged by the SUT via producing right here actions:

  • Listening for incoming messages on the IBM MQ queue to be parsed
  • After appropriately receiving the message, it generates the answer message the use of the records carried to the request message.
  • according to this existing article and a outdated one, the reader can put into effect a load script to check the ultimate stub conduct.

    Conclusion

    listed here, I showed another way to make use of Docker in a performance assignment, by using service stubbing in keeping with Docker virtualization. I also described examples that used quite a few Docker containers we started working with in old articles. These acquired stub features display container flexibility in distinctive contexts (e.g. Maven container is for constructing goal).

    After developing your gadget, you could run performance checks on it with BlazeMeter. Create your JMeter script, scale it in BlazeMeter, share your checks with colleagues and bosses, and analyze results.

    To are trying out BlazeMeter, request a live demo from one in all our efficiency engineers.




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    Rational Manual Tester

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    Rational CLM a collection of updated legacy IBM tools | killexams.com real questions and Pass4sure dumps

    IBM's application lifecycle management (ALM) suite is a collection of products known as IBM Rational collaborative lifecycle management (CLM). IBM Rational CLM covers requirements management, quality management, change and configuration management, project planning and tracking all on one platform.

    The IBM Rational ALM suite aims to enhance productivity by eliminating working in silos, which can often cause project delays, lower quality results and cause budget overruns. This tool also offers in-context team collaboration, lifecycle traceability across disciplines, real-time planning and development intelligence that allows developers and project managers to make fact-based decisions. The IBM Rational CLM products are compatible with several operating systems, including Windows, Mac OS, Linux, Solaris, AIX, IBM I and z/OS.

    IBM Rational CLM is a set of three integrated tools: Rational Team Concert, Rational Quality Manager and Rational DOORS Next Generation.

    Rational Team Concert

    Rational Team Concert (RTC) integrates task tracking, source control and Agile planning with continuous builds and a configurable process to adapt to varying work styles. RTC also provides collaborative change management capabilities and integrated features including work-item, build and software configuration management.

    RTC provides visibility into activities and progress with multilevel dashboards and reporting features, and facilitates planning and execution of projects with planning tools and templates, including a new Scaled Agile Framework template. In addition, RTC offers advanced source control, which helps distributed teams communicate and collaborate. Pricing for RTC is flexible and licensing is role-based with multiple platform support in a single release, allowing the implementation of individual components at purchase or in the future.

    Rational Quality Manager

    Rational Quality Manager (RQM) delivers capabilities for test management including test planning, creation and execution. RQM helps teams share information and use automation to accelerate project schedules. It helps quality assurance teams share project information and status updates, reduce labor-intensive activities and report on project metrics more reliably. It allows users to create and manage test plans that describe project quality goals and exit criteria, while tracking responsibilities and prioritized items for verification and validation.

    RQM uses a browser-based interface built on Java and Web 2.0 technology that includes customizable dashboards made from a large set of predefined widgets. Users can communicate within and among teams using features such as event feeds, integrated chat, review and approval and automated traceability.

    It also includes a comprehensive text editor that can capture textual test steps alongside embedded images for accelerating manual testing using rich-text, in-line images, and assisted data entry and validation for text definition and execution. Testers can share common steps between tests via keywords, and the minimum number of tests required for a given level of environment coverage is automatically identified.

    RQM uses risk-based testing for prioritizing the features and functions to be tested based on importance and likelihood or impact of failure, supporting risk management best practices, as well as test lab management for tracking, scheduling and executing tests on physical and virtual lab assets. Visit the RQM product page for pricing information.

    Rational DNG

    Rational DOORS Next Generation (DNG) captures, manages and traces requirements throughout the application development lifecycle. By having all requirements available from a central, accessible and secure location, this application is good for users to gain transparency and increase reusability. DNG provides a central and accessible location for requirements, concurrent editing, automated versioning and prioritization.

    DNG allows users to track changes in text documents or spreadsheets -- recording time, user and edit history -- and enables users to view history, reviews and discussion comments within the context of the document. DNG also lets users access requirements databases concurrently across multiple profiles without conflict or disruption, while ensuring that teams use consistent terminology with an integrated glossary.

    Users can create multiple views that use filters and display settings for different roles and tasks. Documents and project templates have predefined and customizable options. Customizable dashboards and automated reports visualize information, and users can edit, author and analyze artifacts on a Web client that also supports commercial servers. DNG can also import documents, CSVs, and ReqIF or work with the provided project and module templates.

    DNG can be purchased on a fixed-term license, an Authorized User Single Install, or a Floating User Single Install basis, along with a 12-month subscription to the support services. Prices vary by license type. Rational DNG is an upgrade to Rational DOORS 9, unifying its features into a single-server or Web-based requirements platform that allows for better collaboration among development teams.


    Best Automated Testing Tools (Top 10) for DevOps and Continuous Delivery | killexams.com real questions and Pass4sure dumps

    DevOps is a set of practices that highlights collaboration, communication, and automation throughout the application development lifecycle. Continuous Delivery allows teams to release a build after continuous testing automatically any time.

    Both methodologies work to achieve the same goal; releasing applications in short incremental cycles with numerous feedback from across different teams right from the planning phase for better attention to detail.

    The continuous repeatable release of software ensures speedy delivery of stable quality software to end user. Automation has an essential role to play in both DevOps and Continuous Delivery. Automating DevOps and Continuous Delivery helps your organization provide continuous delivery to the users faster and manage a business with low risk.

    Testing needs to be fast and dynamic to match with the goals of DevOps and Continuous Delivery. With traditional testing approaches and tools, this is a seemingly difficult task. And, without the right testing approach, it will be difficult to meet the DevOps and Continuous Delivery standards.

    The right automation testing tool must be used after evaluating the capabilities of the tool closely. It should be capable of meeting end-to-end automation testing requirements. Thus make the test automation program really effective in the agile environment.

    Here’s a guide that briefly discusses a few Automated testing tools that can help ship code and deliver quality software on time:

    1. Selenium With Robot Framework

    Selenium is unarguably the most popular web automation testing tool available.

    One of the main reasons for its widespread use is that it is open source. There are a number of frameworks implemented in different languages using Selenium, which offer more capabilities in automation testing.

    Selenium supports multiple operating systems (Windows, Mac, Linux) and browsers (Chrome, Firefox, IE, and Headless browsers). Test Scripts can be developed in various languages such as Java, Groovy, Python, C#, PHP, Ruby, and Perl.

    You need frameworks on top of Selenium to enable continuous testing, there are a number of tools and frameworks built on Selenium. Robot Framework is one of the most popular frameworks used with Selenium for Continuous Testing.

    With Robot, you can run a variety of automated tests; both UI element based and API tests, with the assistance of Selenium Webdriver.

    It uses keyword-driven approach for acceptance testing and acceptance test-driven development (ATDD). The test capability can be further extended by implementing additional test libraries using Python and Java. Robot Framework can not only be used to test web apps but also to Android and iOS apps.

    However, Selenium itself is not sufficient for all your Continuous Testing requirements. It needs to be integrated with a bunch of Tools that serve distinct purposes in the SDLC. Also, Selenium demands advanced programming skills and a dedicated time and effort to build the automation framework to meet specific testing needs.

    More about Selenium

    2. Testsigma

    Testsigma is a unified AI-driven test automation platform with a Shift-Left approach that integrates Continuous Testing in an end-to-end continuous delivery ecosystem. Testsigma provides agility to both functional and automation teams by eliminating the technical complexity of test automation.

    Automated tests are written in simple, natural language and requires no complex programming which makes it easy for functional testers embarking upon Automation Testing. Testsigma maximizes the reusability through reusable step groups and Centralized Object Repository and uses AI to reduce the test maintenance overhead significantly.

    Testsigma allows for multiple open source and third-party integrations and supports thousands of test environments with different device/browser/OS combinations on the cloud to match with the dynamic testing requirements continuously.

    Testsigma provides all the essential features for enterprise-class test automation and continuous testing like, Data-Driven Testing, Cross Browser testing, Reusability, Test Suites, Schedules, Test Data Management, Email and Slack Notifications, Parallel Test Execution, Centralized Object/Element Repository, Comprehensive Reports, Integration with CI tool and Automatic Bug Reporting etc..

    As a cloud-based Automation Testing tool, Testsigma offers support for various application types like Web, Mobile Web, Android, iOS apps and RESTful services.

    Learn more about Testsigma

    3. IBM Rational Functional Tester

    RFT is another promising tool in this category. It is capable of Functional, API, Performance Testing and Regression testing.

    Rational Functional Tester creates automated functional tests by using record and playback and compares the actual result produced by the system at the time of execution, with the expected result stored at the time of recording.

    IBM supports a wide variety of applications and offers integrations with multiple other tools in addition to its Rational Performance Tester, IBM Rational Quality Manager, etc.

    The IBM Rational Test Workbench family tool supports regression testing at the API level, the user interface level, and the overall system level to help achieve these goals of testing within the DevOps or continuous delivery lifecycle.

    Check out IBM's RFT

    4. Tricentis Tosca

    Tricentis Tosca is a Continuous Testing platform that accelerates testing to keep pace with Agile and DevOps. Tricentis Tosca applies a model-based testing approach and makes script maintenance easy. Tosca can run numerous tests a day continuously.

    Tricentis Tosca uses risk-based test design to suggest the most effective test cases and identify the risk contribution of each test cases. It maximizes the reusability and increases maintainability with model-based test automation

    Through service virtualization, Tosca provides access to dependent systems earlier in SDLC so that tests can execute completely, reliably, and continuously.

    Tricentis Tosca seamlessly integrates into the most common enterprise software environments and continuous integration development workflow.

    Learn about Tosca tool

    5. UFT

    Unified Functional Test is one of the popular cross-platform automation testing tools. It allows the execution of tests using both keywords and manual scripting. It supports integration with CI tools, provides web, mobile, and API testing, and has a smart object recognition function.

    UFT uses VBScript as the scripting language and requires knowledge in this domain.

    It has Reusable Test Components, which reduces redundancy in Test Steps, easy conversion of Manual Tests to Automated ones, shift-left compliance, and Test Execution on multiple machines and devices.

    Check out UFT

    6. Parasoft

    This allows an organization to "shift left" the testing effort and accelerate the SDLC to meet the growing time-to-market pressure for software applications.

    Parasoft Continuous Testing Platform which allows users to create, manage, and deploy virtual test assets and environments through a web interface as well as integrate them with their continuous integration system.

    With the integration of end-to-end testing, test environment management, it reduces the time and cost and helps in delivering a reliable software.

    Parasoft provides access to realistic test environments at any time and ensures a better project quality by removing undiscovered defects early on.

    Learn about Parasoft

    7. TestComplete

    TestComplete gives testers the ability to create automated tests for Microsoft Windows, Web, Android (operating system), and iOS applications. Tests can be recorded, scripted or manually created with keyword driven operations and used for automated playback and error logging.

    While Selenium can only execute tests in a browser (and mobile apps using Appium), TestComplete supports Windows applications.

    With the support of custom extensions and plugins, the TestComplete functions can be extended as per need. Your team can keep up with the quickening pace of development and deployment without making trade-offs between quality, speed, and cost.

    Learn about TestComplete

    8. SeaLights

    SeaLights is a platform enabling the continuous release of software products. They shorten software release cycles as much as possible and streamline testing across the company while improving the reliability of the test.

    SeaLights helps in measuring the code coverage for regression, API, and integration testing and maintaining the test status and quality metrics across all testing tools and environments automatically. It also helps in identifying the Black holes, which are untested or high risks from both unit and functional testing.

    It ensures that untested code does not reach production without any validation.

    Check out SeaLights

    9. Watir

    Watir is limited to web apps, works only on Windows, and is targeted for executing simple and easily maintainable tests.

    Watir is an open-source testing tool for web automation testing based on Ruby libraries. Watir supports cross-browser testing including Firefox, Opera, headless browser, and IE. It also supports data-driven testing and integrates with BBD tools like RSpec, Cucumber, and Test/Unit.

    Watir with frameworks like cucumber and integrations with CI tools help you achieve the goals of testing within the DevOps or continuous delivery lifecycle.

    Learn about Watir

    10. Your Choice

    What other tools help meet your Continuous Testing needs? Leave your comments below to include a couple more tools from the comments to this list!

    Bottom Line

    Above mentioned are some of the best Automated Software Testing Tools that enable DevOps and Continuous Delivery of software.The evolution of DevOps and Continuous Delivery(CD) are an example of how Agile methodologies are shaping the future of software development and delivery.

    Transforming the way software is delivered, Continuous Delivery is a methodology that extends agile's potential by involving in CI and DevOps practices and tools.

    These methodologies are designed to improve the process of software delivery and ensure reliable software releases.  Ultimately, it enables the systematic, repeatable, and more frequent release of quality software to end customers.

    Today’s changing business needs demand an agile thinking and processes into DevOps and Continuous Delivery.

    Choose the right set of automation testing tools that can track the project, keeps the release cycles short and continuously provide actionable feedback and organize the team's progress.

    The above list of test automation tools can help you in your evaluation process and ensure that a high quality, reliable solution is delivered continuously.


    Can Rational Arguments Actually Change People's Minds? | killexams.com real questions and Pass4sure dumps

    Are we, the human species, unreasonable? Do rational arguments have any power to sway us, or is it all intuition, hidden motivations, and various other forms of prejudice? The answer isn't simple, but we may not be irrational creatures after all.

    This post originally appeared on Contributoria.

    The question has been hanging over me because of my profession. I work as a cognitive psychologist, researching and teaching how people think. My job is based on rational inquiry, yet the picture of human rationality painted by our profession can seem pretty bleak. Every week I hear about a new piece of research which shows up some quirk of our minds, like the one about people given a heavy clip board judge public issues as more important than people given a light clip board. Or that more attractive people are judged as more trustworthy, or they arguments they give as more intelligent.

    Commentators and popularizers of this work have been quick to pick up on these findings. Dan Ariely has a book calling us Predictably Irrational, and the introduction tells us "we are pawns in a game whose forces we largely fail to comprehend. We usually think of ourselves [with] ultimate control over the decisions we make [but] this perception has more to do with our desires... than reality." Cordelia Fine's book A Mind of Its Own has the subtitle "how your brain distorts and deceives," whilst David McRaney doesn't pull any punches with the title of his You Are Not So Smart.

    The wider context is the recent progress in the sciences that puts our species in the biological context of the animals, a project that most psychologists are signed up to, to some degree. A reflection of this is all the experiments which attempt to give a mechanistic —that is natural—account of the mind, an account which downplays idiosyncrasy, subjectivity, and non-determinism. The philosopher John Gray was reflecting on this trend in research, as well as giving vent to his own enthusiastic pessimism, when he wrote:

    We think our actions express our decisions. But in nearly all of our life, willing decides nothing. We cannot wake up or fall asleep, remember or forget our dreams, summon or banish our thoughts, by deciding to do so. When we greet someone on the street we just act, and there is no actor standing behind what we do. Our acts are end points in long sequences of unconscious responses. They arise from a structure of habits and skills that is almost infinitely complicated. Most of our life is enacted without conscious awareness.

    The science, and those who promote it, seem to be saying that we're unreasonable creatures. That's a problem, given that many of our social institutions (such as democracy) are based on an assumption that rational persuasion can occur. If I believed the story told in these books I would be forced to choose between my profession as a cognitive scientist and political commitment as a citizen and democrat.

    Fortunately, as a cognitive scientist, I don't have to believe what I'm told about human nature—I can look into it myself. So I set out to get to the bottom of the evidence on how we respond to rational arguments. Does rationality lose out every time to irrational motivations? Or is there any hope to those of us who want to persuade because we have good arguments, not because we are handsome, or popular, or offer heavy clipboards.

    Persuasion and Arguments

    One of the most famous examples of the way our minds twist arguments is an experiment performed by Charles Lord, Lee Ross, and Mark Lepper way back in 1979. These American social psychologists recruited participants who had views for or against the death penalty. They then presented them with reports of studies which seemed to support or oppose the death penalty. Here's a pro-death penalty example:

    Kroner and Phillips (1977) compared murder rates for the year before and the year after adoption of capital punishment in 14 states.

    In 11 of the 14 states, murder rates were lower after adoption of the death penalty.

    This research supports the deterrent effect of the death penalty.

    Lord and colleagues found that people didn't change their minds in the direction of the arguments presented to them—far from it. Rather, people who had pro-death penalty views found flaws and biases in the anti-death penalty studies, and vice versa. The participants in the experiment ended up with more extreme views than they started with—the pro- people becoming more pro and the anti- becoming more anti. This "biased assimilation effect," whereby we only believe evidence that fits with what we already believe, is no historical artifact. Adam Corner and colleagues from the University of Cardiff showed in 2012 that this bias holds for a very contemporary topic—climate change. People who were more skeptical about climate change rated editorials supporting the reality and importance of climate change as less persuasive and reliable than those people who were less skeptical.

    At first glance, evidence like this looks like a triumph for the "we're all irrational" team. And don't be tempted to dismiss this as evidence that the people in the experiment are bad thinkers or somehow not qualified think about the topic. Another recent study showed that the more scientific education a climate skeptic had, the stronger their skepticism was likely to be.

    But I want to persuade you that this is evidence of the power of reason, not unreason. Psychologists perform their interventions on participants who are far from a blank slate—they are all adults, usually University educated (our great weakness is performing most psychology experiments on psychology students), all probably having spent years developing their opinions about the world. It is not really surprising that their views can't be dislodged with a few choice anecdotes. Who'd want opinions if they were shifted by the slightest counter-argument. That's not rationality.

    To really look at the power of reason, we need to look at the effect of strong rather than weak arguments. Unfortunately, as two leading researchers wrote in a 1998 review, "relatively little is known about what makes an argument persuasive."

    Two decades earlier, one of the authors of this report, Richard Petty, had been involved in a piece of research which showed an important qualification you need to take account of if you want to measure how persuasive good arguments can be. Along with John Cacioppo, Petty ran an experiment looking at how involvement in an issue affected the power of arguments to persuade. The experimenters tried to persuade undergraduates at the University of Missouri that University regulations should be changed so that all students would have to pass an additional comprehensive exam before being allowed to graduate. Previous work had revealed that such a change was "strongly counter-attitudinal for most college students." That's psychology code for "they hated the idea." Cacioppo and Petty varied the kinds of arguments they used on their volunteers. Half received strong arguments in favor of the change, and half weak arguments—arguments that had obvious flaws or simple counter-arguments. A second factor was manipulated: how involved people felt in the argument. Half the volunteers were told that this change was under consideration for the University of Missouri. In other words, that it would affect them, possibly requiring them to pass an extra exam or flunk their degree. The other half were told that the change was being considered at North Carolina State University (approximately 1000 miles away).

    The results show that when people have low involvement in an argument, neither the strong or weak arguments were persuasive. People's minds were made up, and no argument shifted them. But in the high involvement condition both the strong and weak arguments had a significant effect. Weak arguments entrenched people's positions—they shifted their attitude to be more against the final exam. Strong arguments, however, had the effect you might expect from reasonable people; they shifted their attitudes to be less against the final exam idea (it still wasn't very popular, but it was less unpopular).

    This research, and research that followed on from it, showed that strong arguments can be persuasive, but only when people are motivated to deliberate on the issue. Recently, a team led by Joseph Paxton of Harvard University showed that, in the domain of moral arguments, strong arguments were only persuasive if people were given some deliberation time before being forced to answer. Like crimes, it seems, reasoning requires both motive and opportunity, but if both are there even in crude psychology experiments we can show that strong arguments persuade.

    Truth Wins

    The strongest evidence on the power of argument comes from domains where there is a right answer. For public issues like the death penalty, or moral arguments, it will never be clear what the right answer is. Because of this, one person's strong argument won't be the same as another's. In logic or mathematics, however, because a correct answer can be defined precisely, so can strong arguments.

    For a long time, Psychologists have used a logic task called the Wason Selection Task as a lens on our power of reasoning. The task works like this: imagine there are cards which always have a letter on one side and a number on the other. You are shown, flat on the table, four cards. Their up-facing sides show E, G, 7, and 6, and you are told that you need to test this rule: "All cards with a vowel on one side have an even number on the other side." Which cards do you need to turn over to test if this rule is true?

    In experiments using this task, over 80% of people test the rule by picking the cards showing "E" and "6" and they are wrong. The result is often held up as an example of the weakness of our powers of logic, showing how unsuited our minds are to formal reasoning.

    The correct answer is that you need to turn over the "E" and the "7" cards. If the "E" card doesn't have an even number on the other side, the rule is false: a vowel did not lead to an even number. Similarly, if the "7" card has a vowel on the other side, the rule has also been shown to be false: a vowel led to a non-even number. Turning over the "6" card doesn't tell you anything, since the rule doesn't say anything about what even numbers cards ought to have on the other side (i.e. it doesn't say that non-vowels can't lead to even numbers too).

    But what is often held up as a testimony to our irrationality can also be a laboratory for examining our rationality. Whilst the selection task is normally completed by individuals, you can also ask small groups to try and solve the task. When you do this, two remarkable things happen. Firstly, the success rate jumps massively so that most groups solve the task correctly (75% or more, compared to a success rate of less than 10% for individuals). Secondly, we can observe the process of discussion that generates the correct solutions, enabling us to discern something powerful and encouraging about group reasoning.

    Transcripts of groups reasoning about the selection task show that in the process of discussion groups manage to construct arguments in favor of the correct answer, i.e. the answer that is in line with the logic of hypothesis testing. Other work on group reasoning, this time using mathematical problems, has shown that often it is enough for a single member of group to realize the correct answer for the group to submit this as their final decision. This "Truth Wins" scenario is in total contrast to what psychologists will normally tell you about group function. In most domains, from creativity to tug-of-war, a phenomenon called "social loafing" holds, whereby the performance of the group is less than the sum of expected effect of individuals acting alone.

    This encouraging story about the power of reason needs to be put in the context of the research on persuasion. The groups in these experiments have a common goal and, we must assume, trust each other and are committed to the task. Furthermore the solutions can be demonstrated to be correct. In these circumstances rational argument is productive.

    Prove Me Wrong

    Another result that comes from analyzing transcripts of the these types of experiments is that people are only persuaded when they can be shown that the answer they are currently advocating is wrong. Insight into how to do this comes from experiments on the so-called "Illusion of Explanatory Depth." The illusion concerns our beliefs about how well we understand complex systems—ranging from the forces driving global terrorism to how a flush toilet works. The original research which framed the phenomenon asked people to self-rate their understanding of how things work. Examples for this experiment were taken from the classic children's book The Way Things Work. The volunteers were asked to rate how well they understood things like "How a speedometer works," "How a helicopter flies" or "How a cylinder lock opens with a key." After they give these ratings, the participants were asked to write out a full explanation of how the items worked. They then answered test questions about their understanding. They then rated their original understanding again. After the trying to provide explanations, participant's ratings of understanding dropped. After the test questions they dropped even further, revealing that most people have a far less confident understanding of these things than they initially believe.

    There is a lesson here for all of us about over confidence. The authors of the study, Leonid Rozenblit and Frank Keil from Yale University, ascribe the effect to the ease with which we interact with these systems, allowing us to directly appreciate their effects (e.g. we make the car go faster, and the speedometer shows the new speed). We, they argue, then mistake this sampling of the environment for our own knowledge. Without the working system in front of us, we're actually pretty ignorant of its internal operation.

    But for me the interesting lesson is that the study participants came to realize they were wrong in their original assessments. Although full of confidence initially, they moved to re-rating their understanding as dramatically lower—they were, in other words, persuaded to change their minds about something (in this case, about how much they knew). How did this happen?

    Follow up work published last year confirms that asking people to provide mechanistic explanations can play a vital role in persuading them they are mistaken. Philip Fernbach, of the University of Colorado, and colleagues asked participants in an experiment to provide opinions on policies which are generally contentious in the US, things like healthcare, social security and tax. So, for example, they indicated their support for polities such as transitioning to a single-payer health care system. Whether they were for or against the policy, the average participant was a long way from neutral. Half were then asked to give reasons why they felt like they did, and the other half asked to give an explanations of how the policy would have effects. Both groups then re-rated their position for or against the policy and these "after" scores were compared with the "before" scores. The "reasons" group didn't shift their views at all, remaining just as entrenched in their positions, for or against, as when they started the experiment. The "explanations" group did change, on average becoming more moderate in their positions. The authors conclude that the illusion of explanatory depth supports political extremism, and that when we are asked to provide explanations for how we think the world works, some of that illusion evaporates, undermining our previous certainty.

    This research goes some way to explaining why causal reasons have been found to be more persuasive than statistical ones (in this case arguing that you cannot catch AIDS from touching someone with AIDS, because transmission occurs via HIV in bodily fluids, compared to arguing that you cannot catch AIDS from touching someone with it because no one ever has).

    Argumentation

    This raises the general topic of how we react to arguments. More recent research has shown that even children as young as three prefer an argument that uses reasons to a circular argument

    So it seems that, despite all the biases we're subject to, we are sensitive to reason—we discriminate better arguments from worse ones, often recognize the truth when it can be demonstrated, and adjust the strength of our beliefs when we discover we can't justify them as fully as we thought. Other work has shown that the skill of recognizing and developing arguments can be taught.

    A movement called deliberative polling uses group discussion as a way of measuring people's opinions (rather than the "stop them in the street and get a knee-jerk reaction" strategy). Typically, this approach gathers less extreme views— for example, people's opinions on the value of prisons as way of treating crime are more moderate, less in favor—as well as leaving participants better informed, more willing to compromise and more aware of nuances in the issue debated.

    The Power of Reason

    These successes of group reason are in stark contrast to the known weaknesses of individual reasoning, which is beset with a susceptibility to logical fallacies (as we saw in the Wason selection task), and biases such as confirmation bias.

    So striking is the success of reason when deployed in the service of argument that two cognitive scientists, Dan Sperber and Hugo Mercier, have even proposed that this is what reason evolved to do —convince other people in arguments, a legacy of our biological nature to live in social groups. This explains the success of groups on problems that confound individuals, and also explains why we are so good at thinking up reasons why we're right, even when we're wrong. If the purpose of reason is to persuade others that we're right, rather than find the truth directly, then this is just what you'd expect.

    This theory connects with that of another important theorist of rationality, Jonathan Haidt. In his book The Righteous Mind, Haidt argues that intuitions come before reasons in arguments about moral issues, and that our social natures means that it is next to impossible to persuade someone under conditions of group competition (such as the current conditions of US politics).

    Haidt isn't saying that we can't persuade other people about in arguments about moral issues, just that reason and argument are less important than group membership and intuition.

    If you're interested in irrationality in persuasion then the very first place to start is the book Influence by social psychologist Robert Cialdini. This classic work looks at six major factors which can help persuade other people. For example, one major factor is "reciprocity," whereby we feel compelled to give something back when people have given something to us (for example when a car salesperson has agreed to cut the price by 10%, maybe we feel we should raise the amount we're willing to pay in return). There's no need to labor the opportunities for the unscrupulous to take advantage of this kind of habit of mind. None of Cialdini's important persuasion factors are rational argument, so at first glance it looks as if Cialdini's manual of persuasion is coming firmly from the "we're irrational" side. But a second look might give us pause. Much of the evidence on which the power of these factors to aid persuasion is based assumes a situation where you have an at least half-way rational argument to begin with. A closer look at the factors Cialdini highlights shows that some of them are things we would expect to be possessed by someone whose thinking was generally rational. For example, one of Cialdini's principles is the need for people to appear consistent, so that if people first say they support protecting the environment, for example, they are then far more likely to agree to donate money to a green charity. But although our desire to be consistent can tie us in knots, for a reasoning person it is far preferable to the alternative which is to revel in inconsistency and to feel no compulsion to avoid contradiction.

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    Other persuasion factors highlighted by Cialdini are things which, you could argue, naturally accrue to someone who is more rational: they are more likeable, have more authority, are more like to gather social proof (lots of people will agree with them). Maybe relying on these factors to judge whether you should be persuaded can lead to irrational mistakes, but in the long term they might help distinguish more rational from less rational arguments.

    Paul Bloom is a proponent of the power of reasoning in moral persuasion, arguing that we have direct evidence of the power of reasoning in cases where morality has changed —over time, people have been persuaded to accept gay marriage, for example, or to reject slavery. Reasoning may not be as fast as intuition, as Haidt claims, but it can play a role in where those intuitions come from.

    Bloom cites an idea Peter Singer describes in his book The Expanding Circle. This is that when you decide to make a moral argument—i.e. an argument about what is right or wrong—you must to some extent step outside of your self and adopt an impartial perspective. If you want to persuade another that you should have more of the share of the food, you need to advance a rule that the other people can agree to. "I should get more because I'm me" won't persuade anyone, but "I should get more because I did more work, and people who did more work should get more" might. But once you employ an impartial perspective to persuade you lend force to a general rule, which may take on a life of its own. Maybe tomorrow you slack off, so your own rule will work against you. In order to persuade you struck a bargain with the group's shared understanding of what's reasonable. Once you've done this, Singer argues, you breathe life into the internal logic of argument. The "impartial perspective" develops its own dynamic, driving reason forward quite apart from the external influences of emotion, prejudice and environment. Not only can the arguments you advance come back to bite you, but they might even lead you to conclusions you didn't expect when you first formulated them.

    Are We Rational or Not?

    So where does this leave us?

    Are we a rational animal, or as Robert Heinlein said, merely a rationalizing one? Sure, there's no shortage of evidence that our intuitions, emotions, prejudices and motivations can push reason around. Good luck to you if you want to use only argument to persuade, unless you've got people who already like you or trust you (ideally both) you're going to have a hard time, but amidst the storm and shouting of psychological factors, reason has a quiet power. People do change each other's minds, and if you can demonstrate the truth of your point of view, or help someone come to realize the short-comings of theirs, maybe you can shift them along. But beware Singer's warning: logic has its own dynamic. If you open yourself to sincerely engage in argument then it is as likely that your interlocutor will persuade you as the other way around, after all, none of us has sole claim on what it means to be rational.

    What's the evidence on using rational argument to change people's minds? | Contributoria

    Tom Stafford is a lecturer in Psychology and Cognitive Science at the University of Sheffield. This article was first published on Contributoria.com, the collaborative crowd funding platform for journalists.

    Photos and images by Alexandre Normand (Flickr), David McLeish (Flickr), Saaf Faruque (Flickr), Tambako the Jaguar (Flickr).

    Want to see your work on Lifehacker? Email Andy.



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