How Machine Learning Is Changing Test Automation

Everybody wants to be part of the next big thing, whether that’s some shiny new test management strategy or an emerging technology like Artificial Intelligence (AI). In fact, so many people want to be part of the AI movement that there’s a real tendency to describe things as AI when they’re really just automation or advanced analytics. This puts decision-makers on the test bench in something of a tricky spot—you need to perform your due diligence to make sure you’re getting what you think you are out of a solution.

When it comes to Machine Learning (ML)—a specific sub-concept within the larger AI-sphere—there’s less confusion. Why? Because ML refers to a particular set of processes that revolve around structuring and analyzing unstructured data, in order to find insights and draw conclusions. Thus, while there are potentially infinite ways AI might transform test automation, there are a few defined, concrete applications for ML in the test lab. This includes Quality of Experience (QoE) testing, SLA monitoring, and fraud detection, all of which can significantly contribute to achieving ROI for your test operations.  

What is Machine Learning?

Before we talk about some of the specific ways ML can impact test automation, let’s first figure out precisely what ML means. Per the MIT Technology Review, “Machine-learning algorithms use statistics to find patterns in massive amounts of data. Here, data encompasses a lot of things—numbers, words, images, clicks, what have you. If it can be digitally stored, it can be fed into a machine-learning algorithm.” It notes that recommendation engines on sites like Netflix and YouTube are often powered by this kind of statistical technology—to say nothing of mission-critical business insights. Using machine learning algorithms like the ones being described, you can extract value from data that would be impossible for a human to comb through.

For our purposes, the most important applications of machine learning technology are those in which it’s combined with streaming algorithms. These algorithms sequence random, unstructured data to create a “sketch” that stakeholders can understand. For instance, throughout your automated testing workflows, you might be collecting tons of data points on different network states, along with signal traces, CDRs, etc. Though you probably have to pay to store this data somewhere, there’s not much you can do to extract value from it by hand. Enter the streaming algorithm: by properly “querying” the system, data can immediately be extracted without sifting through and synchronizing tons of detailed records. Maybe there are dependencies in the arrangements you’ve made with your roaming partners that interfere with your legacy fallback procedures, which might account for a recent uptick in dropped calls. Conversely, you might discover snippets of code in your OSS/BSS systems that are adversely impacting user experience on your network.

How Machine Learning Impacts Churn Rates

As part of its broader ability to wrangle large and complicated caches of data, ML algorithms can also help testers to add new metrics and KPIs to their existing test reports, to localize faults better and improve their services. To wit, ML can be a big help when it comes to generating QoE (quality of experience) metrics to complement your existing QoS (quality of service) measurements. By modeling your audio quality as a mean opinion score using POLQA (Perceptual Objective Listening Quality Analysis), for instance, you can go beyond the usual purview of an end-to-end test to answer some critical questions:

  • How would subscribers rate the audio quality they’re experiencing, above and beyond the fact that the audio is connected?
  • What factors might be negatively impacting audio QoE for your subscribers, and how can you address them?
  • What critical facets of the user experience are your more objective QoS metrics leaving out or eliding over?

Since user satisfaction is closely correlated with the kinds of intangibles that QoE tracks, then the more objective QoS measures like latency and packet loss, combining QoE and QoS in this way can go a long way towards mitigating the factors that impact user churn. With machine learning algorithms to synthesize these network realities for you, you can finally pinpoint the issues that are causing users to seek other providers or carriers. You can work to address them in an end-to-end manner.  

Challenges in Machine Learning Integration

Hopefully, this doesn’t sound too good to be true—because it isn’t. This is real technology that’s being deployed to improve customer experience and decrease churn among telco testers worldwide. It’s also being used to speed up service verification across the board via a reduction in a manual effort. The question is, how can you deploy it within your operation? For starters, you need to collect and aggregate all of the test data that your ML algorithms will be combing through; this means using a centralized test management system that can handle distributed testing processes with a high degree of visibility.

It can help leverage new network topologies like network slicing, SDN/NFV (Software Defined Networking/Network Function Virtualization), and cell densification and improve network operations through increased visibility that ML methods provide. This gives the machine learning processes even more relevance, and it enhances the quality of the insights you’re receiving from it via apt data collection. The better those insights get, the more effectively you’re able to save time for human testers and engineers, address customer concerns before they lead to subscriber churn, and create a more stable and effective network.

Again, this isn’t science fiction—this is something that testers can employ right now to improve their processes, boost their ROI, and future-proof their offerings. The trick is to make sure you build out your testing processes with a genuinely flexible and data-driven framework. This will give you the foundation you need to take full advantage of machine learning-based improvements, to say nothing of any new technologies that emerge in the next few years.

Download our latest Test Automation Ebook.

Search

Interested in our Products ?

Scroll to Top
Segron logo black blue

Senior SaaS System Administrator

Technical Skills :
  • Oversee the sysadmin related tasks in our SaaS infrastructure (partially cloud based, partially bare metal)
  • Daily operation and maintenance of the system
  • Analysing and resolving incidents
  • Follow and help improving the incident and change management procedures
  • Design procedures for system troubleshooting and maintenance
  • Incorporating base OS updates and security patches
  • Ensure that systems are safe and secure against cybersecurity threats by raising change requests where potential threat is possible
  • Performing SW updates for the Segron SaaS SW stack (distributed architecture with clusters)
  • Configuring solutions like reverse proxy, firewalls, etc.
  • Building tools to automate procedures & reduce occurrences of errors and improve customer experience
  • Tutoring & coaching newcomers & less senior experts in the team
  • Interworking with the architects and IT admins of Segron to have the SaaS procedures inline with the Segron processes
Non-technical skills:
  • We are looking for a self-motivated, self-improving individual with a highly independent mindset and open and straightforward technical communication to help us to improve and maintain our cloud infrastructure of our powerful end-to-end testing solution ATF (Automated Testing Framework)
  • 3+ years hands-on experience with operation and monitoring of cloud / linux systems
  • 3+ years of hands-on experience with network devops elements: configuring routers, switches, networks
  • Hands-on experience with running live systems with infrastructure as a code mode of operation
  • Specific knowledge which brings direct advantage: Docker, Docker Compose, Grafana, Prometheus, Ansible, Debian Linux OS administration, Security
  • Experience in building and maintaining distributed systems (incl. redundancy, resiliency, load-balancing) is welcome
  • Excellent knowledge of English
Location :
  • Place of work: Bratislava (partially home office possible)
  • Rate: from 30 EUR/hour (possible higher rate, depends on experience)
Segron logo - The Next Generation of Active Testing
Segron logo black blue

CI/CD Senior Developer

Technical Skills :
  • A senior role with a proven expertise in software development, cloud computing, DevOps, and CI/CD
  • Experience in planning, designing, and overseeing the CI/CD strategy and architecture on the level of organization
  • Ability to tailor testing strategies which define and follow the best practices, standards, and policies for the software delivery process
  • Hands-on experience in creating and managing CI/CD pipelines and workflows (PaaC)
  • Ability to evaluate and recommend the best tools, technologies, and methodologies for the CI/CD implementation
  • Prior hands-on experience working with different CI/CD toolsets (Jenkins, Bitbucket, GitLab, artifactory, Ansible ..)
  • Proficient with DevOps tools API automation capabilities
  • Proficient with Atlassian Tools (BitBucket, Jira, Confluence) and agile SW development methodologies
  • Familiar with cloud patterns and best practices
  • Familiar with web performance best practices
  • Comfortable working in cloud DevOps ecosystem
  • Comfortable working with Linux platforms
  • Initial working experience in SW development is an advantage.
Non-technical skills:
  • Effective communication with technical as well and business stakeholders
  • Self-motivating, self-improving mindset
  • Ownership of relevant industry certificates is a plus
Location :
  • Location: Bratislava, Slovakia (with hybrid flexibility)
  • Rate: from 30 EUR/hour (possible higher rate, depends on experience)
Segron logo - The Next Generation of Active Testing
Segron logo black blue

Test Automation Engineer

Job description, responsibilities:

Hardware Testing: Conduct verification and testing of hardware during the HW/SW products
assembly process.
Technical Support: Provide technical assistance during testing activities and troubleshoot any
hardware issues that arise. Support to internal teams and customers by managing priorities and
meeting deadlines.
Equipment Maintenance: Configure and maintain SEGRON laboratory and customer equipment.
Logistics Support: Handle hardware ordering and logistics.
Troubleshooting: Analyze and resolve SEGRON product issues through effective problem-solving.
Ability to troubleshoot and resolve issues that arise during the integration process.
Collaboration: Work with the SEGRON Development Team on product or software issues and assist
the Project Team with planned activities.
Root Cause Analysis: Investigate production errors to identify underlying causes.
Software Deployment: Implement software updates and fixes.
Team Collaboration: Ability to work collaboratively in a team environment, especially in serving global
customers.

Requirements/ Skills:

Networking knowledge: Understanding TCP/IP networks and LAN/WAN configurations. Routing and
switching and related protocols strongly desired.
Hardware Proficiency: Understanding of hardware components, including servers, routers, and
peripherals, to ensure proper assembly and integration. Experience in data centers is a plus.
Travel Abilities: Willing to travel for customer on-site support for hardware installations, migrations,
upgrades, troubleshooting, etc. (few times a year, 3-5 days)
Hand Tools: Proficiency in using hand tools like screwdrivers, pliers, crimpers, and punches for
assembling and disassembling components.
Operating Systems: Knowledge of Linux and Windows. VM experience (Hyper-V, VMWare, Oracle
Virtual Box, Proxmox etc.)
Tools Proficiency: Basic understanding of Ansible.
Telecommunications Experience: Previous experience in the telecom sector is a plus.
Education: Degree in Computer Science/Engineering or equivalent work experience.
Experience: At least 2 years of relevant work experience preferred. A strong desire to continuously
improve skills and knowledge in hardware and software integration, with an openness to feedback and
new ideas. Key is openminded person willing to learn fast in great team.
Communication Skills: Effective oral and written Eng

Others:

• Full time job (employment)
• Onsite work during onboarding period, then it can be 3 days onsite, 2 days home office
Offered salary: from 2000 Euro (depends on seniority and skills level)
Variety of financial benefits
Place of work: Bratislava

Segron logo - The Next Generation of Active Testing
Segron logo black blue

Senior Python Developer

Technical Skills :

  • A solid, experienced SW developer with at least 10 years of experience in active SW development in different programming paradigms
  • Minimum 5 years of professional Python development experience
  • Master or college degree from Computer Science, Mathematics or STEM domain
  • Well educated in design and programming patterns that increase software’s efficiency and readability.
  • Very good analytical and problem solving skills.
  • At least three skills out of the following 4 skills are requested:
    • Microservices based architectures (Docker containers)
    • Linux
    • Ansible
    • Robot  Framework
  • Comfortable with sysadmin and DevOps skills (Ansible, YML files, Network Programming, IP protocols, designing and developing proxy servers for different protocols – example: streaming, integrating and compiling third party libraries on Linux (Debian))
  • Proficient with Atlassian Tools (BitBucket, Jira, Confluence) thorough understanding of Git and version control best practices
  • Familiar with cloud patterns and best practices
  • Familiar with web performance best practices

Non-technical skills:

  • Ability to work under pressure
  • Ability to abstract and explain your work
  • Strong understanding of Agile development process and experience working in an agile team
  • Strong communication skills with both technical and non-technical stakeholders
Location :
  • Bratislava, Slovakia (with hybrid flexibility)
  • Rate: from 35 EUR/hour (possible higher rate, but depends on experience)
Segron logo - The Next Generation of Active Testing