Every day, your employees schedule appointments, request approvals, revise documents and workflows, route information, and look for status updates. In many businesses, people still perform these actions manually. This can be a struggle when you have to scroll through multiple email revisions, replies, and forwards to find the current version of a document. It can also be a challenge when you miss an email that gives you an approval before everything’s ready.
The objective of automated testing is to simplify as much of the testing effort as possible with a minimum set of scripts. If unit testing consumes a large percentage of a quality assurance (QA) team's resources, for example, then this process might be a good candidate for automation. Automated testing tools are capable of executing tests, reporting outcomes and comparing results with earlier test runs. Tests carried out with these tools can be run repeatedly, at any time of day.
Test automation on the other hand is the automated execution of predefined tests. A test in that context is a sequence of predefined actions interspersed with evaluations, that James Bach calls checks. These checks are manually defined algorithmic decision rules that are evaluated on specific and predefined observation points of a software product. And herein lies the problem. If, for instance, you define an automated test of a website, you might define a check that ascertains a specific text (e.g. the headline) is shown on that website. When executing that test, this is exactly what is checked—and only this. So if your website looks like shown in the picture, your test still passes, making you think everything is ok.
Our conversations to date with professionals in a wide range of fields—radiologists, financial advisers, teachers, architects, journalists, lawyers, accountants, marketers, and other experts of many kinds—suggest that whatever the field, any of the five steps we’ve just laid out is possible. Not all of them are right for a given individual, but if you can figure out which one is right for you, you’ll be on your way to an augmentation strategy.
Today’s software testing tool market offers testers more options—and more confusion—than ever before. Both the open source community and commercial vendors are introducing new software testing tools at an unprecedented rate. On top of that, the past couple years have brought tremendous turmoil in the software testing tools marketplace (think HPE-Micro Focus spin merge, the IBM Rational- HCL deal …). Given all the new choices and changes, it’s not surprising that there are now 100+ software testing tools lists making the rounds on blogs and software testing community sites.
Crispin and Gregory define Test-Driven Development (TDD) as the process of writing and automating small unit tests before writing the piece of code that will make the test pass. TDD is used for continuous integration testing to ensure small units of code work together first. A unit test verifies the behavior of a small part of the code in the overall system. These tests are the primary candidate for the majority of automated tests. Even teams that are not practicing Agile development use TDD to prevent defects and design software (Agile Testing, 2008).
Another term for this kind of automation is something Michael Bolton and James Bach call checking, a decision rule that can be interpreted by an algorithm as pass or fail. Computers can do this kind of work, and do it well. Having check automation run at the code level -- unit tests -- or user interface level can vastly improve quality and catch obvious errors quickly before a human even looks at the software.
Industrial automation incorporates programmable logic controllers in the manufacturing process. Programmable logic controllers (PLCs) use a processing system which allows for variation of controls of inputs and outputs using simple programming. PLCs make use of programmable memory, storing instructions and functions like logic, sequencing, timing, counting, etc. Using a logic based language, a PLC can receive a variety of inputs and return a variety of logical outputs, the input devices being sensors and output devices being motors, valves, etc. PLCs are similar to computers, however, while computers are optimized for calculations, PLCs are optimized for control task and use in industrial environments. They are built so that only basic logic-based programming knowledge is needed and to handle vibrations, high temperatures, humidity and noise. The greatest advantage PLCs offer is their flexibility. With the same basic controllers, a PLC can operate a range of different control systems. PLCs make it unnecessary to rewire a system to change the control system. This flexibility leads to a cost-effective system for complex and varied control systems.
IBM helps clients around the world transform and manage functional and industry-specific processes to achieve intelligent digital operations. These services rely on AI, process automation and advanced analytics to help deliver higher quality processes at lower cost with less risk. IBM process automation services address the four fundamentals of process design.