Software development is evolving, such as with the introduction of object oriented languages that compete with traditionally compiled code. Software development is changing almost as quickly as the hardware on which it runs. Here are eight software development trends to watch out for in 2017 that are certain to impact the industry for years to come.
Early chatbots caused the Lisp programming language to make a comeback because it could handle the lists of textual responses chatbots used when dealing with questions. Newer methods of programming chatbots use the same algorithms Big Data does for search engine optimization, reviewing masses of data on prior interactions between customers and salespeople or technical support to determine the ideal answer for the chatbot to give. Chatbots are cheaper than having people standing by 24/7 online for answering questions or promoting your product, assuming they are equally successful in convincing someone to buy your product or explaining how the checkout error is resolved.
Platform as a Service
Twenty years ago, software resided on the hardware on which it ran unless you were accessing enterprise level software on a server. Software as a service shifted the software programs themselves used by average users to cloud servers, such that you had to access the cloud to run applications like Adobe’s creative suite. Platform as a service is the next level of services, allowing software developers an environment and hardware to run on. Software developers can requisition additional space, processing power and bandwidth as necessary. Google’s App Engine and OpenShift by Red Hat are examples of platform as a service or PaaS.
Infrastructure as a service or IaaS is not as commonly available as a platform as a service, though it is growing. Infrastructure as a service uses cloud storage and networks to allow customers to run virtual data centers; users can deploy virtual servers and control their (virtual) infrastructure. At this point, Platform as a Service is coming to dominate the cloud world while IaaS is used by a few to support PaaS.
The decentralized cloud based model is so prevalent that the term XaaS or anything as a service has come into usage, since one cloud farm may host multiple IaaS or PaaS along with a few SaaS providers and customers may have their data and applications running in several different data centers.
Open source software has been one of the linchpins of the internet thanks to Linux servers with uptimes that are a rounding error away from 100%. Open source software alternatives to games and Microsoft Office have long been inferior substitutes, but they are maturing and rivaling the corporate backed products. Open source software is also expanding into far more niches. MySQL rivals Oracle while Drupal and WordPress support blogging platforms. Open source artificial intelligence, data mining, simulation, data visualization, bioinformatics and risk management tools are in widespread use. Open source tools for human resources management and ERP are available if not as widely used. Check out the latest Opensource ERP Comparison.
Software Escrow Services as Risk Management
Instead of saving your mission critical software to a repository like GitHub where it may inadvertently become open source or corrupted by unauthorized parties adding their alterations, software escrow services allow companies to place their source code in a secure location managed by a third party. When a software escrow account is created, the source code involved is placed in an account the other authorized parties can access.
An increasing number of customers are demanding software escrow services. Holding critical code in escrow ensures that the software application isn’t dead or unsupported if the parent company goes out of business, since licensees retain access to the source code. While around 80% of the intellectual property held in software escrow is code, proprietary databases and data sets are also stored in software escrow.
Software Development as Business Development
Up until recently, software development focused on simplifying, automating and improving pieces of the business’ operations. Quicken and similar software packages were tailored for accountants. Property managers, customer relationship marketing experts and bioinformatics teams all had software options that helped them perform a single job function or set of tasks better. Enterprise resource planning software went a step further, typically integrating purchasing, selling, inventory and payroll functions. Software developers are now taking a step back and trying to collect as much information as possible and use it to help stakeholders make more informed decisions and improve the business as a whole.
The first major implementation of artificial intelligence is likely Google’s search algorithm update to include artificial intelligence smart enough to guess the searcher’s intent based on key search terms and search history. Unlike the application of IBM’s artificial intelligence to try to find treatments for a single patient suffering from an unknown disorder, the AI behind the search engine is interacting with almost everyone on a daily basis and affecting our world on a massive scale.
Teasing out relationships between risk factors and diseases or treatments and improvement for specific subsets of patients is just one way AI is being applied in medicine. Improved marketing to consumers by identifying the most likely prospects or new, previously hidden customer segments is another.
Go by Google
The Go programming language was the most popular programming language in 2016. In contrast to the chunkiness of C and its variants, Go is simple and easy to learn. It has built in support and is very efficient. Go as a programming language is designed to run on distributed systems and highly scalable software, so it is likely to become an industry standard for new applications designed for SaaS and PaaS. Go replaces both Java and C++ in Google’s own software stack. Go won’t replace all other software languages, since it doesn’t let programmers use their own data types.
International Software Development
International software development has been a trend for a number of years, but it is epitomized by Google setting up Indian software development centers to complement its American teams. This wasn’t a case of hiring cheaper Indian programmers to follow the software design instructions of American engineers. The Indian programmers were equal contributors to the Windows 10 operating system and other projects.
Companies are more willing to rely on internationally distributed software development teams to save on labor costs, though software support is often international so that you can afford to offer 24/7 tech support. Distributed software development teams can tap into the same benefits of 24/7 work so that someone in Asia is reviewing and testing code created by an American team when the Americans are done for the day. Companies double the speed of their software development work without demanding staff pull all-nighters.
The cost savings and greater service offered by chatbots are driving their development, while Open Source software’s maturity and a broadening array of services is increasing its adoption. Software as a service is increasingly supplied via the platform as a service model. Software escrow services are starting to be demanded by companies afraid that mission critical software would become unsupported or unavailable if the software developer goes offline.
International software development is increasingly becoming common. Software development is starting to look at products that support the entire business as a whole instead of piecemeal, while Big Data and tools to mine it hope to give knowledge workers the answers they need. AI is growing specifically to do exactly that, all while trying to find cures for disorders and improve search results. Go by Google is the hottest programming language right now because it is designed for cloud based software development and distribution.