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Just over a hundred years ago, Henry Ford transformed the car industry with the assembly line. Because of Ford’s innovative approach to car manufacturing, nearly all of us own a car.
Today we live in the Information Age, where software and digital connectivity drive the marketplace. This new era offers different challenges than the Industrial Age, as well as ripe opportunities for innovative solutions, akin to Ford’s assembly line. One such solution exists in the way we manufacture products in this digital landscape: through the software product line.
Software product lines use a collection of software-reliant systems that share a common set of features to manufacture products. Rather than use one set of software per item, engineers can reuse core assets of software product lines to create different products.
A simple way of explaining software product lines is through the lens of a famous fast-food chain. At McDonald’s, a McDouble and a Big Mac are different burgers, but they have a common set of assets: bun, burger, cheese. If an employee knows the proper ingredients and steps of making a McDouble, then she wouldn’t need to be retrained from scratch to make a Big Mac, since a Big Mac is simply a slight variation of a McDouble.
“You have core assets that allow you to manufacture or produce common components in such a way that you have a controlled variation,” says UC Associate Professor Nan Niu, PhD, who researches ways to more effectively build and use software product lines. “You can fine-tune the parameters to obtain these predefined common utilities to serve your specific needs.”
Scale this concept up to the level of a national car manufacturing plant, for instance, and you have Ford Motor Company creating variations of an engine that use the same core assets of an existing engine – its parts, designs, user documents and production processes. Instead of rewriting each of these components every time Ford unveils a new engine, Ford can reuse the assets and adapt minor changes to introduce the new engine to the product line.
“You’re basically shaping the way you conduct your business or engineering to establish and maintain a well-defined infrastructure,” says Niu. “Next time you design a new product, you can write fewer lines of code, because you have that infrastructure serving you.”
Software product lines, however, are not perfect and come with a number of challenges, ranging from investment of time to financial constraints. Additionally, the way engineers determine their assets is not always the most efficient process.
That’s where Niu’s research comes in.
Niu and his PhD advisor, Steve Easterbrook, PhD, recently received the prestigious Most Influential Paper Award at the International Requirements Engineering Conference for their paper, “Extracting and Modeling Product Line Functional Requirements.” The honor, awarded by the Institute of Electrical and Electronics Engineers (IEEE), is given annually to the most influential paper from the conference 10 years earlier.
Niu’s paper, which addresses reusable assets in software product lines, has been monumental to research, and its concepts have been widely applied to the field, its relevance rippling through both academia and industry.
Niu’s paper addresses the extraction method within the software product line. Software developers use three approaches to reuse core assets: proactive, reactive and extractive.
In a proactive model, manufacturers develop nearly all core assets for reuse so that products can be reused at maximum efficiency.
“In this extreme case, you wouldn’t even build a frame of the engine in the first place without thinking about doing a reusable thing first,” says Niu, referring back to the car manufacturing example.
The proactive approach, though most effective, requires a large upfront cost and a transition time that some companies can’t afford. Retrofitting an entire product line to meet a proactive model can be a lengthy process, sometimes shutting down production facilities for months at a time. Its benefits, however, are immediately noticeable: Over time, the cumulative costs for building each product is significantly less than other approaches.
On the other hand, the reactive, or “one-of-a-kind,” approach creates product lines with little regard for reuse. Reusable assets – like designs or user documents – are developed as needed or as they come up in production. Though this method doesn’t require any prior planning – or the costs in time and energy associated with that planning – it can put businesses behind the competition in the long run.
The extractive model, the model Niu addresses in his paper, is a third approach that splits the difference between proactive and reactive models. The extractive approach selectively reuses several existing assets to build a product line asset base.
“The extractive approach strikes a balance,” says Niu. “It may never be as dramatic as the proactive approach, but the key is that you can survive in the market competition.”
Rather than overhaul an entire operation, companies can increase efficiency and stay competitive in the market by selectively choosing several assets to reuse down the road and strategically investing in assets as they can afford to do so.
The extractive approach strikes a balance. It may never be as dramatic as the proactive approach, but the key is that you can survive in the market competition.
Nan Niu UC associate professor
“If I’m a car manufacturer, I may build an engine or two without reusable assets,” says Niu. “After building those two engines, however, I realize I have common themes. While making a third engine, I can afford to invest time in determining reusable assets and shaping that product line infrastructure, so that the third and fourth engine can be produced at a lower cost.”
As a manufacturer develops more products in the line, the number of reusable assets increases and become more advantageous simply because of the financial and time-saving benefits of reuse.
How do manufacturers determine the assets to extract? That is the second part of Niu’s paper.
Niu is working with requirements assets for building reusable assets within software product lines. When people build software systems, for example, they use requirement assets to instruct what each software system should do for a user. Niu found that these assets are typically written in natural language, with a verb-direct object pair.
The paper uses an example of an academic grading and feedback system employed at the University of Toronto. In this system, students can submit papers, follow assignments and view grades online. If a software developer wanted to allow students to view their grades, she would write that into the functional requirements – “student” is the agent, “view” is the verb and “grades” is the direct object that pairs with that verb. When somebody builds the site’s functions, these requirements would provide a convenient framework.
“You use this frame of verb-direct object pairs to allow you to express the concerns or the key functionalities of the software,” says Niu. “In a nutshell, this technique recognizes the verb and direct object pairs that are happening in a natural language context, extracts the pairs and later models them using semantic analysis.”
By employing this approach, a user or developer is left with a set of reusable verb and direct object pairs that expresses the contents of the software product line. Manufacturers can use this set to develop the foundations for their software product lines.
The influence of Niu’s paper is seen in its diverse and far-reaching applications. Though traditional manufacturing is certainly a focus of the research, it’s not the only application. For example, the same concepts of reuse and extraction are being applied to market analysis. So, when you go to the grocery store and repeatedly buy the same items, stores can use that associative and historical data to better determine how to allocate shelf spaces and market products.
Niu’s paper also serves economic purposes. The extractive approach addressed in Niu’s work essentially allows corporations to have their cake and eat it, too. “You can have your product of engineering, and at the same time you can incorporate reuse,” says Niu. “A corporation can be better off without necessarily compromising its ability to build concrete products.”
It has been 10 years since Niu published this paper, which served as the backbone of his dissertation, with Easterbrook. Seeing the paper’s lasting influence on both research and industry has been powerful for Niu.
“Whenever you publish a work, you hope it’s going to have an influence in some way,” he says. “But to be recognized by the conference really gives closure to the work.”
Niu concludes by quoting an ancient Chinese proverb: “It takes 10 years to build a sword.” In other words, should you invest the initial time and energy to craft a masterpiece, its lasting influence will be felt for years. The recent award at the International Requirements Engineering Conference confirmed that Niu crafted his sword right the first time.
Featured image at top: Production line for engines in a car manufacturing facility. Photo/Hamik/Shutterstock.