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What Is Software Testing?

Higginbotham, Stacey

Software glitches have always caused major damage. And recently, the biggest failures haven’t been in aerospace or defense, but have increasingly affected the average consumer. Often, we hear that the software testing wasn’t done properly. But what does this mean exactly?

 Photo: iStockphoto Photo: iStockphoto

Every now and then, really spectacular software breakdowns occur. The opening of Heathrow Terminal 5 became a public embarrassment because the baggage system failed to function. More than 17 million customer accounts at RBS and its subsidiaries NatWest and Ulster Bank could be accessed for some or all of the day because the installation of customer management software corrupted the entire system. One of the biggest Austrian banks paid out €21 million to appease its customers with vouchers because the new online banking software didn’t work for days on end.

Errors like these are not only damaging to a company’s brand, but can also be very costly. The goal of software testing is to avoid such incidents and the consequences. On the following pages, we explore the topic of software testing and address these main questions:

Hans Hartmann, test director at Objentis since 2007. (Photo: Private)

We can assume that in the cases previously mentioned, the software in question was definitely tested: Banks and insurance companies know the risks of using software that has not been tested. So how can such malfunctions continue to occur? Some, but certainly not all, software glitches can be caused by storms and natural disasters. Still, this provides no explanation for the increase in software errors of late. Testing has always been done and it used to work well. And natural disasters are a known, if unpredictable, factor. So why should the tried-and-true formulas suddenly fail?

The reason is simple: Programs have become more complex. And to address this complexity, more testing is required. How much more? Take the years 2000 and 2010. In this time, the volume of data being moved around increased by a factor of 50,000. If a program was tested for two weeks in 2000, it would have to be tested for 100,000 weeks in 2010 – in other words, around two thousand years.

More interactions, not more data, increases complexity

Working and calculating this way is clearly not an option. After all, software is now more efficient, development tools allow many errors to be detected before the program is first created, and modern object-oriented software design enables developers to code neatly and in a less error-prone way. But even if testing is only increased by a factor of 50, it would still have to be tested for 100 weeks – or two years. That simply isn’t feasible.

Comparing the difference in size and quantity alone doesn’t necessarily mean that the software has become more complex. In fact, one of the main arguments for using a computer is that it doesn’t matter whether it has to perform a calculation five times or 5,000 times. It should simply be reliable. It is not the increase in the quantity of data that causes complexity, but rather the increase in possible connections and systems.

Look at the development of mobile telephony: In Germany, Radio Telephone Network C came along first in cumbersome cases, followed by the much more manageable digital cellular network D-Netz. In comparison, today’s smartphones have the processing power of mainframe computers from 20 years ago. Apart from the pure advancement of technical data, think about all the things that can now be done with a smartphone. Above all, think about the number of other systems that can be tapped into – at the same time, even. It is the number of possible connections that causes the corresponding increase in complexity.

The main difference between today and yesterday is not the advancement in programming languages – even though developers may no longer code in Assembler or COBOL, these languages can still be used to write good programs today – but rather the number of possible solutions there are for a certain problem.

Take this analogy of trying to cross a river that is 30 feet wide without using a boat and without getting wet. In the past, there was one solution: system analysts would look for places where big rocks could be used jump across the river to the other side. Today, there are 10 different bridges crossing the river, that is, 10 different ways to solve the problem.

The software architect, then, has to choose a particular solution based on whether it meets various quality requirements. Let’s say there is a highway bridge crossing the river as well as a wooden walkway. To use the highway, you need to build feeder roads. Even if the simple wooden walkway is sufficient and building feeder roads requires more effort, the software architect may still choose to use the highway with the reasoning that other people want to cross the river, too.

It’s impossible to test every combination

Here is another example: Forty years ago, when passengers would buy a train ticket from a ticket machine, they would have to answer a series of questions, one after the other. From where do you wish to depart? To where do you wish to travel? How old are you? Are you entitled to a reduced fare? In which class do you wish to travel? And so on. If they discovered while answering the questions that they didn’t have enough money, they would have to cancel the transaction and start again from the beginning.

At today’s ticket machines, passengers will find the questions slightly more hidden in different fields. Instead of entering their age, they select standard fare, half price, or other offers. Rather than typing the destination in full, they type the first few letters, and only the possible destinations are then displayed. While the layout of the input fields suggests that the information can be entered in any order, that is still not possible. For example, if users have entered a discount ticket, they cannot subsequently upgrade to first class. However, instead of getting an error message that says, “First class must be entered before you select a discount,” users will see a message like, “You must purchase your first class ticket on the train.”

In this case, it is clear that developers made some small mistakes in the process of transferring an originally linear, simple input sequence to a graphical input system. Let’s say the machine needs to process five different inputs and they can be in any order. This means there are 120 different combinations of how entries can be made. So, it is understandable that not all input options were tested before the software was implemented.

In the past, it was possible to test each individual function and then test the complete process. Now it is necessary to test the interactions between individual functions. The number of these interactions depends directly on the number of possible sequence combinations, which can easily be a seven-digit sum. If you take a smartphone, for example, the number of possible combinations surpasses the example of the ticket machines by several orders of magnitude.

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Why 3D Printed Food Just Transformed Your Supply Chain

Hans Thalbauer

Numerous sectors are experimenting with 3D printing, which has the potential to disrupt many markets. One that’s already making progress is the food industry.

The U.S. Army hopes to use 3D printers to customize food for each soldier. NASA is exploring 3D printing of food in space. The technology could eventually even end hunger around the world.

What does that have to do with your supply chain? Quite a bit — because 3D printing does more than just revolutionize the production process. It also requires a complete realignment of the supply chain.

And the way 3D printing transforms the supply chain holds lessons for how organizations must reinvent themselves in the new era of the extended supply chain.

Supply chain spaghetti junction

The extended supply chain replaces the old linear chain with not just a network, but a network of networks. The need for this network of networks is being driven by four key factors: individualized products, the sharing economy, resource scarcity, and customer-centricity.

To understand these forces, imagine you operate a large restaurant chain, and you’re struggling to differentiate yourself against tough competition. You’ve decided you can stand out by delivering customized entrees. In fact, you’re going to leverage 3D printing to offer personalized pasta.

With 3D printing technology, you can make one-off pasta dishes on the fly. You can give customers a choice of ingredients (gluten-free!), flavors (salted caramel!), and shapes (Leaning Towers of Pisa!). You can offer the personalized pasta in your restaurants, in supermarkets, and on your ecommerce website.

You may think this initiative simply requires you to transform production. But that’s just the beginning. You also need to re-architect research and development, demand signals, asset management, logistics, partner management, and more.

First, you need to develop the matrix of ingredients, flavors, and shapes you’ll offer. As part of that effort, you’ll have to consider health and safety regulations.

Then, you need to shift some of your manufacturing directly into your kitchens. That will also affect packaging requirements. Logistics will change as well, because instead of full truckloads, you’ll be delivering more frequently, with more variety, and in smaller quantities.

Next, you need to perfect demand signals to anticipate which pasta variations in which quantities will come through which channels. You need to manage supply signals source more kinds of raw materials in closer to real time.

Last, the source of your signals will change. Some will continue to come from point of sale. But others, such as supplies replenishment and asset maintenance, can come direct from your 3D printers.

Four key ingredients of the extended supply chain

As with our pasta scenario, the drivers of the extended supply chain require transformation across business models and business processes. First, growing demand for individualized products calls for the same shifts in R&D, asset management, logistics, and more that 3D printed pasta requires.

Second, as with the personalized entrees, the sharing economy integrates a network of partners, from suppliers to equipment makers to outsourced manufacturing, all electronically and transparently interconnected, in real time and all the time.

Third, resource scarcity involves pressures not just on raw materials but also on full-time and contingent labor, with the necessary skills and flexibility to support new business models and processes.

And finally, for personalized pasta sellers and for your own business, it all comes down to customer-centricity. To compete in today’s business environment and to meet current and future customer expectations, all your operations must increasingly revolve around rapidly comprehending and responding to customer demand.

Want to learn more? Check out my recent video on digitalizing the extended supply chain.

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Hans Thalbauer

About Hans Thalbauer

Hans Thalbauer is the Senior Vice President, Extended Supply Chain, at SAP. He is responsible for the strategic direction and the Go-To-Market of solutions for Supply Chain, Logistics, Engineering/R&D, Manufacturing, Asset Management and Sustainability at SAP.

How to Design a Flexible, Connected Workspace 

John Hack, Sam Yen, and Elana Varon

SAP_Digital_Workplace_BRIEF_image2400x1600_2The process of designing a new product starts with a question: what problem is the product supposed to solve? To get the right answer, designers prototype more than one solution and refine their ideas based on feedback.

Similarly, the spaces where people work and the tools they use are shaped by the tasks they have to accomplish to execute the business strategy. But when the business strategy and employees’ jobs change, the traditional workspace, with fixed walls and furniture, isn’t so easy to adapt. Companies today, under pressure to innovate quickly and create digital business models, need to develop a more flexible work environment, one in which office employees have the ability to choose how they work.

SAP_Digital_Emotion_BRIEF_image175pxWithin an office building, flexibility may constitute a variety of public and private spaces, geared for collaboration or concentration, explains Amanda Schneider, a consultant and workplace trends blogger. Or, she adds, companies may opt for customizable spaces, with moveable furniture, walls, and lighting that can be adjusted to suit the person using an unassigned desk for the day.

Flexibility may also encompass the amount of physical space the company maintains. Business leaders want to be able to set up operations quickly in new markets or in places where they can attract top talent, without investing heavily in real estate, says Sande Golgart, senior vice president of corporate accounts with Regus.

Thinking about the workspace like a designer elevates decisions about the office environment to a strategic level, Golgart says. “Real estate is beginning to be an integral part of the strategy, whether that strategy is for collaborating and innovating, driving efficiencies, attracting talent, maintaining higher levels of productivity, or just giving people more amenities to create a better, cohesive workplace,” he says. “You will see companies start to distance themselves from their competition because they figured out the role that real estate needs to play within the business strategy.”

The SAP Center for Business Insight program supports the discovery and development of  new research-­based thinking to address the challenges of business and technology executives.

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Sam Yen

About Sam Yen

Sam Yen is the Chief Design Officer for SAP and the Managing Director of SAP Labs Silicon Valley. He is focused on driving a renewed commitment to design and user experience at SAP. Under his leadership, SAP further strengthens its mission of listening to customers´ needs leading to tangible results, including SAP Fiori, SAP Screen Personas and SAP´s UX design services.

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Planning For High-Tech In The Digital Age: The Customer Wants It All On Short Notice

Andrew Boyle

Of course it’s happened again.

Supervisor with digital tablet at production line in circuit board manufacturing plant --- Image by © Adrian Brockwell/Juice Images/CorbisYour new “next big thing” is ready to launch, and the supply chain planning team spent inordinate amounts of time over the past few months refining a forecast and collaborating with suppliers and contract manufacturers. All components were purchased, and most were even delivered at the assembly houses when they were supposed to be.

But now your most important customer needs twice as much product this week than they had previously forecast. No apologies – only demands. How do you reallocate components and finished goods inventory to your new high-priority order without missing dates you’ve already promised to other customers?  Is it even possible?  What components might you need to resolve the shortage?

We have seen such issues with just about any successful product launch in recent history, from smartphones and tablets to gaming systems and even integrated circuits or components. End-to-end planning and order promising in high-tech is all about facing these kinds of dynamic situations. With the proliferation of the digital economy, the good news is that you have more data points than ever to help you plan and respond. The challenge is that you need to find a way to manage all that data and put it in a meaningful business context. Therefore, it cannot be done in a silo; these new plans and customer allocations must be integrated into your core operations to be effective.

This is where a digital supply chain and modern tools enable a different way of integrated execution.

Plans can now consider production constraints and supplier commitments. This enables, for example, the modelling of assembly house capacity from production line to complete packaging of finished goods.

When you consider the entire value chain and the entire planning horizon, the magnitude of data that needs to be processed increases exponentially. Planning systems need to work through these massive amounts of data quickly to support a data model that includes demand, supply, and financial factors. To be effective, these plans must be supported by strong collaboration between both internal stakeholders and external business partners. And of course, these tools need to be easy to use. No matter how powerful, a system that is not user-friendly will be passed over in favor of spreadsheets and guesswork.

How can a modern high-tech organization use these new tools to meet their goals of lower inventory levels and reduced time to market? Sales and operations planning can now consider demand, supply, and financial factors and simultaneously optimize inventory carrying costs. The limitations identified in strategic planning can now be used to drive customer inventory allocations, considering priorities that you set. Order promising can be more than a simple check against stock on hand; it can now include what-if scenarios to solve problems, like that new large customer order. Collaboration with suppliers and contract manufacturers is made easier with business networks rather than traditional EDI and supplier portal onboarding. All of this can now be monitored by a central control tower, which oversees the entire value chain and alerts planners when things need fixing.

So what about your favorite customer with that big order—how do we resolve the shortage? With effective internal and external collaboration, planning across demand, supply, and financial factors, and fast what-if response scenarios, we will be able to quickly identify gating parts, adjust plans and component orders, and meet the new customer deadline without impacting existing customer commitments.

This blog is the first in a series. Upcoming blogs will provide a more in-depth look at OEMs and how they can use digitalization to help plan and determine when to send clear-to-build signals. We will also look at semiconductor organizations and how they can plan, for example, wafer starts and optimize diebank stocks.

For more on how digital transformation is impacting all aspects of high-tech business, please visit here.

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High Tech Blazes The Digital Transformation Trail

Dirk Wenzel

Digital transformation is not just a new technology trend; it is fundamentally changing how business is done across all industries. From product innovation to customer engagement and enterprise productivity, technologies such as the Internet of Things (IoT) and real-time, Big Data analytics as well as social, mobile, and cloud computing, are changing every aspect of business.

The high-tech industry is playing a unique role, not just as an enabler of digital transformation, but also as a potential disrupter of all industries. 70% of all high-tech revenue will be directly related to other industries adopting the digital economy by 2020. Companies in every industry use technology to reimagine their core business processes. This makes it harder to see where high tech ends and other industries begin. New products and business models rely on technology to deliver benefits. Those benefits help them to leapfrog the competition as customers choose to buy outcomes rather than products.

Connected things enable new business models

According to IDC, the IoT will reshape almost every aspect of business. This change includes product design, marketing strategies, executive decisions, customer engagement, and after-sales service. In this projected model, every company will need to become the focal point of a broad ecosystem. This business network will enable close collaboration among all participants using mobile, analytics, and the cloud in a secure environment.

Examples of outcome-based business models already exist across both consumer and B2B companies. Lexmark, for example, recognized that customers want prints, not printers. It sells its products as a service and billing is based on usage, not the hardware that was used to create the print. But the company took it further. With the acquisition of smaller software companies, it is now able to manage the entire document flow, from paper to digital documents that are fully integrated into the back-end business processes.

Research in the Harvard Business Review shows that nearly 60 percent of the buying process happens before initial contact with a sales rep. “First Mile” technology helps companies connect with potential customers during the time before they engage with the company.

The same technology helps to onboard customers, admit patients, process claims, or simplify any other process that requires integration between systems. The result is closer relationships with customers and a much deeper understanding of the customer’s needs and interests.

It might appear that Lexmark’s business is selling printers. Yet the real backbone of the First Mile offering is software, not hardware. In this case, the hardware is acting as an intermediary by collecting information. It then passes the information to other systems.

A connected value chain

The “connected home” is one of the earliest examples of how companies are using high tech to reimagine their business processes.

Google’s Nest connected thermostats keep consumer’s home comfortable. They also connect consumers and energy companies to find the best balance between comfort and economy.

Emerson ComfortGuard services use sensor-equipped HVAC equipment to track performance. When the sensor detects it’s time for service, it notifies the consumer using email. It understands whether the equipment needs a simple filter change or a part replacement. Using predictive analytics, the service can even go a step further. It can autonomously schedule a maintenance appointment before the equipment even malfunctions and it connects to an approved technician list.

These simple examples illustrate how technology is changing basic processes, and this is only the beginning. Connected cars, connected cities, connected machines, and wearables – smart devices have become so powerful and so small that they will be everywhere, enabling a complete new world of tracking, measurements, and monitoring of situation- and environment-specific parameters. Reported in real time, combined with powerful analytics and integrated into core business processes, will enable fact-based, situation-specific decision-making in the moment.

These success stories show that winners in every industry are early adopters of high-technology enhancements to traditional products offerings that enable digital transformation to meet customer needs. In many cases, these new products fulfill needs that customers may not have recognized until they saw the product.

Regardless of the industry, high technology in the form of mobile access, connected devices, sophisticated analytics, and software is blazing the trail to digital transformations and reimagined products and services.

In upcoming blogs we will take a deeper look into digital transformation and how it impacts business models, supply chain networks, customer engagement, as well as talent that is needed to make it all happen.

For more information on how digital transformation is impacting all aspects of high-tech business, please visit here.

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Dirk Wenzel

About Dirk Wenzel

Dirk Wenzel is the Head of Global High Tech Solution Marketing at SAP. He has over twenty years’ experience in software, management, consulting and the high tech industry, with deep expertise in business development, operations and marketing with a focus on business transformation and technology.