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How Centralized Scripting Tools Coordinate QA Team Test Models

Scripting Tools

Present-day powerfully dynamic computing systems require that developers and QA teams extensively validate software and network operations under varied conditions. Today’s business requirements to radically lessen cycle time increments makes test automation increasingly crucial to strategic enterprise goals. The challenge is to stay on top of the volatile pace of increasing customer demand for software deployment while also reducing risk by retaining the assured quality of software releases. The solution must be either the cost intensive increase in personnel or more centralized testing through test automation.

Customer demand, coupled with multiple QA teams, multiple projects, multiple versions, and prototyping of new technologies can place QA departments in operational distress. The speed required to meet deployment due dates can cause teams to ‘run in circles’ and can derange cross-functional team operations.

Another common scenario in team dysfunction is when an actual concerted crew of testers is supporting several diverse and unrelated projects or applications. Each project which follows a new testing strategy causes a hindrance when testers move among different tasks and incentives, especially in respect to needed production time within the test environment. Cross purposes in testing operations can also detract from productivity in developing newly required testing strategies.

Manual evaluations, while informative, can be uncoordinated, repetitious, prolonged, and tedious. Central automation of the process through key scripting alternatives can alleviate the validation process. The automated process of centralized scripting effortlessly provides the information required to inspect and analyze software and network systems.

One way to manage testing challenges is to re-engineer test scripting into automated frameworks that can quickly and efficiently run test cases. Automated consolidation is the key. Developing scripting formats continuously grows the process of application development and deployment, even among diverse projects.

Centralized scripting is automated using a scripting tool. Automation has always been an industry standard for software testing, with Agile processes and methodologies having increased the demand for automated test scripts. Scripting knowledge is essential. Automated testing requires that QA testers be experienced in script writing. Test script automation smooths out the process of achieving a balance between testing speed and testing quality, allowing testers to focus on software functions and to identify defects. When test scripting is automated QA teams can also effortlessly access and run past scripts to re-evaluate software functions.

Automated Scripting

Automated scripts can be run using build server technology, which automatically executes test cases and reports test case results to QA testers and developers. Build servers frame scripts by creating automated scripting structures, along with the compiling, source code, binary code, and automated testing functions associated with scripting. Build servers construct script automation, meaning that they automate the compiling of computer source code into binary code for the testing of software systems. Builds can be programmed for continuous processing, as well as moderated through process controls. QA testers need to first be familiar with script writing to efficiently activate builds for accurate results. Rerunning the build procedure several times to ensure the smoothest scripting path and process assures precision in execution.

Using automated scripting tools, QA can centralize the scripting of test cases. When QA team members have performed extensive analytics, refined quality metrics, and tested scripts against a virtual database, but continue to see cascading red error messages, one indication is that QA scripting is not centralized through automation.

At times QA teams do not realize the importance of retaining test scripts generated through automated testing. As definitive sets of instructions that validate the software system, automated test scripts maintain consistently qualifiable and quantifiable levels of validation for software functionalities. Software system verification using script automation not only allows QA teams to quickly and efficiently execute current scripting processes, but also share automated scripts for use in subsequent projects. Reuse of automated test scripts is a prime asset in that the tools provide subsequent cost-effective validation capabilities.

Avoiding in-process detailed coding requirements, test automation tools effectively generate efficient test scripting. Different tools have different scripting languages. Common automated testing scripts are:

  • JavaScript is a scripting language developed by Netscape which enables Web developers to design and test interactive sites
  • Python is scripting which is object-oriented and compatible with most operating systems
  • Perl, or Practical Extraction and Report Language, is designed for processing text, and thereby works well with scripting
  • Ruby, like Python, is object-oriented, as well as readable, compact, and easily maintained, making it compatible with scripting
  • Tcl, or Tool Command Language, through the use of custom libraries, works well with scripting common gateway interfaces (CGIs)
  • VBScript, or Visual Basic Scripting, is a scripting language developed by Microsoft which centers on activating and testing interactive controls for Web pages

Test management tools provide the consolidated QA performance that centralizes testing procedures for adherence to common goals.

Data Driven Testing Flow

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Data driven scripts

Data driven scripts help QA testers think past the project into application-specific methods which accommodate variable data. Scripting is integrated from other test cases or manually coded, then modified to comply with the data to which scripting will apply. Data driven automation allows test scripts to apply to varied data sets without requiring changes in the test case. Data variables are used within key application inputs and programming, allowing for script-driven applications developed from calling routines that initiate access to external data. 

Certain data driven scripts are termed ‘keyword driven’ or ‘table driven’ scripting. Keyword driven scripting is application-independent using keywords which are autonomous to the test automation tool used in their execution. Keyword driven scripting can also be used for manual testing, but its attributes truly shine with automated test management. Keywords which exist within data table records describe the testing activities to be performed. Data tables also contribute additional data that is required or appropriate to the application, as well as keywords that identify the state of application adherence to key performance indicators.

Hybrid scripting accommodates both data driven scripts and keyword driven test cases. The structure of hybrid scripting allows data driven scripts to activate within the same dynamic data libraries as keyword driven scripts and to function as keyword driven scripting. Hybrid scripting allows for more succinctly delivered scripts which are less inclined to dysfunction. Hybrid scripting functions can also guide the progressive conversion of existing scripts to keyword driven frameworks, as well as carry out scripting which is otherwise difficult to execute in keyword formats.

Generic, data driven, and keyword automated scripting are actually executed by a scripting engine, which generates component functions and data libraries. Scripting engines also provide the cycle drivers and test tables used in data driven and keyword scripting. All automated scripting elements interface with application maps which link the automation framework to the application being tested.

Automation Process

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Accommodating Automated Scripting Tools

The quality of scripting tool performance is crucial to efficient test execution and operation. To connect the application to automated tool processes, centralized scripting tools nonetheless require a certain degree of up-front time investment and testing talent. Within the test planning phase, the organization must decide whether resources are available to accommodate automated scripting. Modifications can at times expand capabilities, but enabled resources and capacities to meet tooling requirements are required prerequisites. Resource requirements include:

  • Testing strategies which allow that reasonable test initiatives be designed, developed, and implemented via automated scripting
  • Testing strategy which allows within on record that each test include step-by-step performance, formatted input data, and detailed expected results
  • Scripting frameworks developed to integrate both traditional scripts and keyword driven testing
  • Scripting frameworks designed to be entirely independent of the application with the ability to test numerous distinct applications
  • Scripting designed to be fully recorded and published
  • A scripting framework that can be re-implemented for subsequent testing and development

Organizational infrastructures must be set up to accommodate the varied requirements for the scripting tool format selected to optimize QA test production.

Automated Scripting Tool Standards

Initial to planning centralized scripting, QA teams must determine the standards for source code files and libraries which define and contextualize reporting. Automated scripting standards begin with structured documentation which delineates the purpose of the routine or subroutine module design and execution. By value, call routines initiate access to subroutine scripting and import test data. Each function includes defined arguments, the respective exit status, and generated errors. Standards also require the documenting of variables, dependencies, constraints, and procedures related to testing modules.

Centralized scripting coordinates inter-team and intra-team test activities. Test and script automation consolidates the testing process with standards launched within actual software testing programs. QA teams are thereby held to defined test platform requirements for script execution. Infinite flexibility in scripting is enhanced throughout standardized automated formats, while risk is mitigated by abating errors, and cost-to-market is reduced through adherence to timelines.

Centralized Scripting Tools and Business Strategic Goals

Centralized script automation is simply a tool to incentivize, maximize, and augment QA testing. The extent to which an automated scripting tool will compel QA team fulfillment of targeted strategic goals depends on the incentives which promote design and implementation of the scripting process. The skills, talents, and understanding on where/how QA is placed within the overall strategic plan determine the extent to which business incentives are addressed and risk is mitigated.

QA teams possessing a clear understanding of coordinated objectives and how QA goals support organizational strategies are best placed for smooth adherence to organizational needs. Once team members understand individual tasks and how tasks effect company goals, they can begin to engage in the purpose of meeting project and enterprise requirements.

To stay on track with business priorities QA units must assess the value of script automation against benefits to the organization. Cost-effective measures that reduce risk and time-to-market, thereby enhancing ROI for the enterprise, are overriding considerations for any competitive organization. Honest and continuous communication among QA teams, developers, IT, and business stakeholders will best ensure consolidated targeting of purpose and projected outcomes.

Stakeholders can motivate team and team member participation, as well as define project and business direction, by boiling down overall goals into conceptually consumable portions that specifically address team functions. Providing visibility of how incremental progress ties into increased enterprise stability is another approach to engaging team awareness. Management can emphasize how shared responsibility engenders, promotes, and requires integrated processes and defined objectives to coalesce QA teams in the common execution of targeted goals.

Coordinated QA productivity is critical to increased profit margins and reduced risk for the enterprise and for enterprise standing within the industry.

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