The Impact of Automatic Testing on Software Quality

automatic testing in software

Automated testing is on the rise, up 23% over the past year.

It’s usually promoted as a way to lower software development costs and shorten time to market.

However, it also has a serious impact on quality. Software that undergoes automated testing during development needs fewer post-release patches and has higher customer satisfaction rates.

Where does this boost in quality come from? Here’s what automated testing brings to the table:

1. Increased accuracy and reliability

Even the best human testers are inconsistent. They might not complete tests properly on a bad day, or fail to log significant results.

Different engineers have different preferred testing routines, too, so tests can change as staff cycles in and out.

These discrepancies make it hard to compare new tests to previous results.

Automation doesn’t suffer from the same problem.

Scripts don’t skip steps or forget to log activity. Once automated tests are set up, they operate the same way every time.

When a mistake is discovered within the system, developers can track it down through detailed logs.

Scripts are reusable, as well. The same test can be used on successive software.

This means the individual script used has often already proven its worth during previous projects.

If there is an error in the code and automated testing is configured correctly, it will reliably be found.

2. Wider coverage

There are only so many manual tests a company can perform on an application without disrupting the development timeline.

Some developers try to compensate by creating larger teams to enable more types of tests, but that increases both cost and complexity.

Applications tested manually therefore have limited testing coverage.

There’s more opportunity for bugs to slip through or for a previously solid feature to develop issues.

Automation allows for the execution of a wider variety of tests.

Since tests on different features can be run concurrently, adding more doesn’t impact the development schedule in the same way increasing manual testing does.

As a result, more features can be examined before the release date.

3. Earlier fault detection

Because automated testing is faster and less labor-intensive, it can be done more often.

This dovetails nicely with the Agile methodologies favored by top-ranked developers, which encourage testing at every sprint.

Frequent quality checks find faults sooner than would otherwise be possible.

Early detection saves a surprising amount of money.

Errors discovered during final stages can be six times more expensive to correct than those found during early sprints.

If a bug makes it past release, fixing it could cost as much as a hundred times more without considering the opportunity cost associated with any bad publicity.

This is why companies sometimes choose to leave unnoticed bugs in place when they’re found after release.

Doing so affects both quality and security, with the risk of a major public relations fiasco if the error comes to light.

Automation: Powering Rising Software Project Success Rates

Automated testing helps developers stay on schedule and under budget without sacrificing quality.

It has been cited as a primary reason that software project success rates have begun rising again for the first time in five years.

In fact, companies wasted 20% less on failed software development last year than in 2016.

The value of automated testing hasn’t gone unnoticed.

Over the last few years its use has risen 85% across industries, with much of that increase focused on testing web applications.

Expect a smaller but still sizeable increase through 2018 as more companies adopt automation.


Concepta’s experienced development teams incorporate automated testing into every stage of our projects. To find out more or hear about our past successful projects, schedule your no-strings-attached consultation today!

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2018 Technology Predictions for Enterprise

2018 enterprise technology predictions

Staying on top in the tech world means constantly looking ahead.

It’s easier, cheaper, and more effective to integrate new technologies while building applications instead of trying to work them in later.

To that end, here’s a look at where enterprise technology is headed in 2018.

Narrow Artificial Intelligence shows ROI

Scientists have been enthusiastic about artificial intelligence for years, but excitement is spreading to the business community as it demonstrates real world value.

Artificial intelligence can generally be defined as either “general” and “narrow.”

General AI describes machines that can reason and make decisions like a human, without a set domain or task to focus on. It can shift from one task to another as easily as humans.

General AI is the “Holy Grail” for computer scientists, but no one has managed to achieve it yet.

It doesn’t help that every time technology reaches what was once considered general AI scientists realize it’s not comprehensive enough.

That task is then relegated to the narrow AI category.

That doesn’t make them useless, however.

Narrow AI applications are very competent within a single domain or when performing a set task.

That may sound limiting, but in reality it’s the only kind of AI showing ROI.

Every AI currently seeing regular enterprise use is narrow AI:

Computer vision and natural language processing (NLP) are also considered narrow AI in their present forms, though they will likely be folded into general AI eventually.

The use of narrow AI will expand dramatically in 2018.

Major companies are investing in AI, like Ford’s $1 billion Argo AI project aimed at developing self-driving car brains.

Cloud computing will push AI into the mobile realm, too.

79% of tech leaders say increasing AI usage is a priority, and 40% of digital transformation initiatives this year will include AI.

Voice and Visual Search become dominant

Technically these are both forms of narrow AI, but they’ve seen such a surge in interest that they deserve special notice.

Visual search uses an image as the basis for a query instead of text. Users can search for other versions of the same picture, similar pictures, or general information about the image.

As computer vision improves visual search is becoming more viable. While it once only let users find the origin of images, it now offers more options:

  • Find photos of friends across the internet
  • Pull up order pages for items worn by celebrities
  • Get recipes for new favorite dishes
  • Research vacation locations

Visual search is already seeing expanded use by major companies.

Google is fine-tuning its new Google Lens, which lets users take a picture with their cell phone and execute a search based on objects within the frame.

Pinterest has a Lens Your Look feature where pinners can take photos of their clothing to get style suggestions. T

hey’re also upgrading their image search to a Responsive Visual Search, where users have the option to specify what interests them within a photo.

Voice Search allows for search based on spoken commands. In the past voice search was so unreliable it inspired jokes on late night TV, but it’s improved a great deal.

In 2012 the average error rate for voice search was 20%. This year that number fell to 8%.

As the error rate has dropped, people are finding it much easier and more reliable to use. 87% of consumers think voice search is accurate enough to use.

21% of mobile users activate their voice search daily, with half using it at least once a week.

The main draw seems to be the ability to safely use smartphones while driving: 53% of those who use voice search regularly do so behind the wheel.

Because of the rising appeal of these features, expect heavy investment in computer vision and natural language processing throughout 2018.

2018 enterprise technology predictions infographic

Blockchain edges into more common enterprise usage

Blockchain is a secure form of distributed digital ledger consisting of a “chain” of individually encrypted “blocks.”

It’s managed via a Peer to Peer (P2P) Network; everyone has a copy of the chain, which makes altering or forging blocks impossible.

Blockchain is famously used for cryptocurrencies like Bitcoin or Ethereum.

There are more uses for blockchain than tracking cryptocurrencies, though.

Storing information in a blockchain is like storing it in a shared database which is being constantly reconciled.

Records are public and easily verifiable.

Once a transaction is recorded it’s incorporated into the chain, not easily erasable by any stretch of the imagination.

Blockchain also exists on a distributed network, so can’t be censored or altered.

The secure nature of blockchain ledgers has many enterprise applications:

  • Smart contracts: Digital agreements can be structured with blockchain to be fulfilled automatically when specific conditions are met. AIG is testing smart contracts for international insurance policies.
  • Preventing voter fraud: Each vote can be accounted for securely and transparently. This hold enormous appeal for civil rights groups looking for ways to prevent rigged elections.
  • Secure resumes: Create an unalterable CV that lets HR managers trust international hires. Secure resumes are especially helpful for jobs with security concerns.
  • International payment systems: Blockchain provides a method for making payments around the world without worrying about embezzlement or funds being intercepted.
  • Transparent supply chains: Secure tracking eliminates confusion and highlights trouble points in the supply process. It could improve global trade by instituting a level of accountability and trust between trade partners.
  • Secure health records: Hospitals can provide better care and cut down on waste and abuse with an unalterable medical record.

Blockchain technologies are growing in number and sophistication.

More than 2500 new blockchain patents have been filed over the last year.

Analysts predict that blockchain will disrupt the insurance and banking industries in particular.

Augmented Reality continues to mature

Augmented reality involves laying computer-generated or animated assets over a camera image. It’s already seen popular use in entertainment:

  • Pokémon Go
  • Snapchat filters
  • Star Wars Find The Force mobile app

This year, technological advances are pushing augmented reality beyond gaming. AR will find a home in other industries.

  • Retail: RayBan and tattoo shop Inkhunter both have “try on” apps that utilize AR.
  • Education: AR maps constellations over a live camera image of the sky or highlight geological features in real time.
  • Travel: AR gives translation apps a boost by overlaying translations on signs or menus.

Investment in augmented reality is rising.

Spending will double in 2018, going from $9.1 billion to $17.8 billion by the end of 2018.

Commercial use will make up 60% of that spending.

Some analysts suggest that 85% of all AR investments will be commercial (as opposed to games) by 2020.

Google, Apple and others are planning AR glasses, but mobile devices are the priority for 2018.

They offer a wider audience with lower investment costs.

Competition intensifies for technical talent

As companies push digital transformation, the talent gap will be more keenly felt.

There are 3 million more STEM positions than available workers right now.

40% of companies looking for tech talent aren’t in the tech industries, just forward-thinking companies looking for help with digital transformation.

The fields in highest demand are data science, business intelligence, digital security, and cloud computing.

There’s also a call for experienced project managers.

65% of tech leaders say that hiring shortages are holding their digital development back. That’s up from 59% last year.

How are they getting around the skills gap? 60% use third parties to support organizational bandwidth. 55% are outsourcing some or all of their analytics needs.

Expect fierce competition for experienced tech talent in 2018.

Nurturing loyalty in employees with tech skills and offering attractive retention packages will become critical to prevent losing staff to headhunters.

Predictive analytics will drive a “quantifiable” model of business processes as Big Data investments rise

Global enterprise investments in data and analytics will surpass $200 billion a year by 2020.

Companies will be looking for ways to quantify business functions where possible in order to get the best possible ROI from these investments

There is a proven advantage to pushing predictive analytics.

48.4% reported measurable results from Big Data investments.

This year, they want to spread that success throughout their organizations by setting quantifiable goals and enacting data-driven operational programs.

Application security focuses on being resilient, becoming stronger from attacks

Security threats have been a major sore point in 2017.

Ransomware attacks rose sharply. Shadow IT and casual “bring your own device” (BYOD) policies exposed companies to hacking and theft.

There was an overall 164% increase in breached records last year. Not only big corporations get hit: 43% of cyber attacks target small to medium businesses.

To meet evolving threats, security software itself needs to evolve.

The focus is shifting from brute strength protection to intelligent detection and response.

Adaptive security software should continuously monitor and scan for threats and address issues on its own.

Once the problem has been addressed, the software should make changes to fix the weak spots exposed by the attack.

That flexibility is where security companies will focus moving forward.

Security needs to be built into software from the beginning, so 2018 will see increasing collaboration between security personnel and programmers and project managers, as well.

Automation will give businesses a competitive edge in the global marketplace

Between increasing amounts of data, a fast-paced global economy, and a tech skills shortage, companies need strategies to do more with less resources.

Automation meets that need by taking tedious or routine tasks off human hands.

Highly automated companies are six times more likely to experience revenue growth of more than 15%.

Companies are responding to such a clear demonstration of potential: 54% of global companies use automation technologies, and more plan to do so in 2018.

The biggest increase will be IT and data management.

Automation will also shorten software development cycles without decreasing quality (through automated testing)

Where will 2018 take your company? If you’re looking to push digital transformation, Concepta can show you the way! Our developers have the right skills to help you visualize your data and unite your digital operations. Schedule your free consultation today!

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Best Software Development Trends of 2017

software development trends

Developers have been pushing two goals this year: efficiency and customization.

The most popular trends have been those that either streamline the development cycle or offer features tailored to the changing needs of end users.

Mobile technology is beginning to take center stage for developers (you can read about our top mobile trends here) but there are some exciting trends brewing in the general software community, as well.

Here’s a closer look at the ones drawing the most attention:


Consumers have heavy expectations of customer service.

When contacting a company via the in-site messaging service or social media, nearly half expect a response within an hour.

A third want a reply in thirty minutes.

Rather than maintain a twenty-four-hour customer service staff, companies are adopting chatbots and chatbot-enhanced technology to keep customers happy after hours.

Chatbots employ Natural Language Processing (NLP) to let programs understand free form questions and reply in natural speech patterns.

Gartner predicts that by 2020 customers will manage 85% of their brand interactions without speaking to a human.

Macy’s has programmed their On Call feature to provide some more custom services: personalized product recommendations, directions to items within a store, and responses to common shopping questions.

Platform as a Service (PaaS)

PaaS is a cloud-based solution for developing, operating, and managing applications.

PaaS providers supply both hardware and software services to developers, who can log in via a web browser and begin building with a minimum of setup.

Some experts predicted it would fizzle out due to concerns over security risks and lack of developer control, but it’s been enjoying a resurgence in popularity in 2017.

Open Source

Open source databases like MySQL and MongoDB have long been popular because of the lower price point.

Now software built on other open source technologies is increasingly in demand for other reasons: scalability and innovation.

The exploding collection of available plug-ins lets companies create software that meets their exact needs.


With technology changing at such a rapid pace, agile methodologies are more important than ever.

Agile emphasizes responding to change on an ongoing basis, listening to client feedback, and delivering many small portions of a project as they’re finished rather than holding everything until the end.

This year Agile is being praised for one byproduct of iterative development: security.

Bugs which might cause vulnerabilities in the finished software can be fixed after every mini-deliverable instead of waiting for the end.

Doing so keeps the development timeline short while improving the quality of the final product.


Automation has been edging onto the development scene for a while.

Automated actions are often confused for intelligent software, though unlike AI programs automation doesn’t use past experience to refine its algorithms.

It involves maintaining a list of processes which are triggered by specific conditions.

Some common processes are spam filtering, offering to resolve an error message rather than simply alert to the error, sorting new customers, and sending follow-up emails after a comment or complaint.

Though it lacks the responsive nature of a chatbot, automation does give end users an additional suite of partially customizable features.

Artificial Intelligence/Machine Learning

With cloud computing and storage becoming widely affordable, experimenting with artificial intelligence has never been easier.

This year the focus is on using AI to improve the customer experience.

Consumers want personal service around the clock, and AI is a cost-effective way to provide that service regardless of time zone.

Look for AI and ML-powered customer-facing features like online assistants, website design tools, facial recognition, and recommendation engines.

Data science

Data is being created at a faster rate than ever before, and companies are looking for solutions to make sense of their data.

Those solutions may be custom software, embedded analytics, testing procedures, or simple process changes.

Whatever the form, data science is becoming an essential part of software development.

Experts predict the drive for customization will continue through the end of the year and beyond, so we can expect more emphasis on features like chatbots, intelligent programs, and automation in the coming months.

Read about more industry trends from our blog. Here are the best web development trends and best mobile app development trends of 2017.

Can these trends help modernize your digital presence? Drop us a line to ask about your own software development needs.

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