You look
at marketing: everything that's happening in marketing is digitized. Everything
that's happening in finance is digitized. So pretty much every industry, every
function in every industry, has a huge element that's driven by Information
Technology. It's no longer discrete”. Satya Nadella, Chairman, Microsoft
In the last 10
years, IT has taken long strides and has become a force multiplier for any
organization. Judicious #integration of IT with fast emerging #telecommunication
facilities like #5G and devices is providing the cutting edge in a global
business scenario. As such, software companies have to move faster in adopting
new software development/testing tools to stay ahead and get their major shares
in the #global IT market.
Today’s
customers are becoming more IT savvy, knowledgeable, demanding and they insist
that Software Development Agency (SDA) uses #futuristic technologies. This
is to enhance their productivity, increase product life cycle and facilitate
global business alliances. These customers also demand faster delivery for an
early launch of their product/service and retain their winning edge among
business competitors. To meet these expectations, there has been a lot of progress
in #Object-Oriented Technologies (OOT), Software Tools for System Analysis and Design (SAD), Software Project
Management (SPM) and Software Quality Assurance (SQA). Software Development Processes, #Security and
Privacy. Customer preferences are the key indicators of future #Digital #Economies.
Some of the emerging trends in the IT industry which continue to impact
the customers and implementers of newer technologies are briefly given in
succeeding sections.
· Data
Handling. Indeed, data is power and the country
which can handle its data efficiently and converts data into actionable
intelligence will lead the way. A serious cyber-attack happened during
USA, 2016 elections, where an adversary country could very effectively
impact the public minds by manipulating data and spreading false information.
Google Cloud services have reported that every day, over 2.5 quintillion bytes
of data is being generated around the world. It is expected that
other cloud service providers like Amazon, IBM, Microsoft, Oracle,
Adobe, Rackspace, Red Hat, and Verizon will have similar large data to
handle. Such a large volume of data requires large and very fast
computing power, special software tools and techniques for fast processing and
extracting relevant intelligence.
· Data Types and Format. Unlike
in the past, today data is not just numbers and text in a structured form.
New data includes #unstructured data as text, tables, pictures,
sound, videos, multi-media messages, feedback coming from organized/unorganized
sectors, public and social media. This data is continuously flowing across
geographical boundaries at a very fast speed and round the clock. This Big
Data is characterized by 3Vs - Variety, Velocity, and Volume. This
has greatly impacted the techniques required for data
collecting, organizing, processing and interpreting for decision
making in various business applications.
· Information. As we know that Data when captured, organized, analyzed
and processed for decision making is referred to as
information
· Knowledge. When information is shared, integrated, and stored
for reuse, it is knowledge.
· Natural
Language Processing (NLP). #NLP can #translate from
one language to another language. This helps the users to select a
convenient language for communication on the web. This also enables the
computing machine or algorithm to interpret and communicate results
in “Plain English” or any other local language that the system
can support. Some NLP tools only do translation and mapping of
words as per computer held dictionaries.
· # Cognitive
Computing. (CC) It relates to systems and processes which
attempt to understand and #emulate human #behaviour. It also provides an
intuitive interface between a person and a machine. #Cognitive computing
employs many techniques including NLP and advanced Machine Learning (ML)
algorithms. CC makes machines (software systems) more accessible and intuitive.
Infect, CC is the key to increasing the adoption of automated systems and
analytic solutions.
Need for
new Programming Languages. In the past,
programming languages like COBOL, Structured Cobol, C, ADA,
Visual C, Modula and Pascal were #procedural programming languages. These
programming languages restricted the developer to focus on
computing resources and not on problem-solving. Indeed, these
procedural languages offer ease of coding and #transparency for simple
applications. However, these are not capable of handling multi-formatted,
multi-media and complex data sets. This has necessitated the evolution of new
programming languages which are more users friendly and can handle a variety of
data, integrate many devices and sensors and ensure higher productivity and
efficiency. Although we have been using (OOPs) Languages
like C#, C++, Java, XML for over 15 years yet software developers
were finding it hard to meet the emerging demand of unstructured,
multi-formatted, multimedia data, Big Data and cloud computing. Hence the
search started for a new programming language to meet new computing and
communication challenges.
Object-Oriented Programing,
(OOP). In earlier programming languages, we
were using subroutines, functions and passing parameters during run-time. In
the #OOP environment, we use “Class|”, which is more powerful than the
subroutine, as it contains both data as well as program/instructions. The #Class
can be coded, tested and validated indivisibly and reused by many other users
in the project team or even in the whole organization. The real potential
of flexible programming lies in the adaptability of classes. OOP allows
developers to break down big and complicated projects into smaller classes.
This makes writing software code less linear, more flexible, easier to #reuse,
ensure better quality and more efficiency. This feature of “Class”
helps in creating reusable software components. Reuse of software
components promotes higher #productivity, #efficiency, #quality, #interoperability
and facilitate business alliances. Modern, high-level languages
like C#, C++, Java, Python, Scala, Kotlin, GO and Ruby are good examples of
OOP. Some of the benefits of OOP are listed below:
· Design. Ease of designing software
applications
· Productivity. Higher
productivity due to easy reusability of objects and classes.
· Reusability. The classes are reusable
and can be distributed to other projects within and outside the
premises.
· inheritance. Another feature “#Inheritance”
of OOP provides better data analysis, requires less development time and ensures
more accurate coding.
· Data Hiding. Data hiding and
abstraction makes data safe and secure, with fewer chances of data
corruption.
· Testing. Ease of testing, traceability,
debugging, and maintenance of software applications.
· #Continuous
Deployment Environment (CDE). Most customers want frequent
delivery and participate alongside the implementer. This close interface
facilitates the timely incorporation of any additional requirement so that
users get software product/service which fully delights them.
Job
Oriented Programming Languages.
In today’s fast-changing
global market environment, new technologies like AI, ML, Robotics, #Drones, IoT, VR/AR,
5G- Mobile Communication, Big Data, Cloud Computing, # Blockchain
all are impacting our workplaces, business practices, travel,
inter-communication, homes. lifestyle and even relationships. For the
implementation and effective use of these technologies, one important common
component is software programming. Old procedural programming
languages like Cobol, Fortran, Modula, C, Visual C, ASP.NET, JSPL, Jrun, PHP
are outdated and not relevant to the new emerging high-tech environment.
However, C++, C# and Java are still in use. Today, to get a lucrative job in an
emerging technology-oriented environment, one needs to have good competency in
new programming languages. Education policies and curriculum in education
institutes are changing fast to meet emerging
requirements. Education policymakers and training institutions should
consider what computer programing language /coding skills College/university
students and the developers of tomorrow should learn to get a good
job in a highly competitive market scenario. Indeed, your choice is
based on market –demand, time and effort required to learn and attain
competency. Leading Computer Software /IT industries like #IBM, #Microsoft, #Google,
#Cisco, have not lagged behind and they continue to evolve new software
programming languages. More than 12 new programming languages have
been developed not only in the USA but also in Japan, the UK,
Sweden. Some of the most popular and job oriented programming languages, used
by software developers are briefly explained in succeeding paragraphs.
· # Python. Python continues to be the topmost programming language commonly
used by most software developers. Python is liked by many since it is
like C++ or java with added features to handle Big data applications. Python is
easy to learn, implement and best suited for coding Algorithms. Current
trends in programming languages show Python’s usability for Machine Learning
(ML), Data Science, IoT and VR/AR applications. Python is an OOP language with
a very comprehensive library. Python is a very efficient programming
language for applications like -Web development; Desktop apps development; ML;
Neuroscience; Medicine; Pharmacology Astronomy, gaming and social media
applications. Python has a few advantages like- Simple to learn
since it has plain syntax; a wide range of libraries; #Open-source nature
which facilitates integration. It can also be used for scripting. However, it
has a few limitations like -- Moderate execution speed;
Extensive memory consumption; not being very suitable for mobile communication
development.
· Kotlin. Kotlin is the fastest
emerging programming language. According to the latest
survey by experts on programing languages, Kotlin is the preferred
language for Android development. This trend is going to grow even more popular
in 2022-2025. Kotlin is well suited for Android software development but can
also be used for applications like - Building IoT applications, Web
Development, Data Analytics, Data Science and Gaming development. The main
advantages of #Kotlin are- good Java interoperability, compact coding and;
ease of maintenance. Like other programming languages, Koilin also has a few
limitations - Comparatively slow compilation, restricted
library resources.
· JavaScript
(JS) JavaScript is popularly used for Web development, Game development.
Mobile apps, Building web servers. According to the latest survey, JavaScript
is the most commonly used scripting language in the world (69.7%), followed by
HTML/CSS (62.4%), SQL (56.9%), Python (41.6%) and Java (38.4%). JavaScript is used to manage web pages and mobile app development; Web games;
client-side of web applications; the server-side of web apps. It has a few
advantages like- It is easy to learn and you can practice and play.
It is the key programming language for building the front-end of websites. It
reduces demand on servers; Interoperability with other programming languages.
JS has a few limitations like- lack of static typing; each browser interprets
JavaScript code differently, lack of client-side security.
· Scala. #Scala is a
relatively new programming language, but it is in high demand by Scala
developers. Scala can be used for multiple purposes like
- customized projects dealing with big data and distributed
applications. Scala is used by LinkedIn and Twitter. It has a
few advantages like-- Compatibility with Java; Functional and concise
coding, Scala is an efficient web programming language. Scala also has a few
limitations like - Scala’s syntax is more complicated as
compared to Java; Limited developer pool
· GO. It has been developed by Google, in 2007, and has got
great success. #GO is very efficient for applications like- System
programming; Network programming, Audio/video editing and Big
Data. GO is
now in the top five programming languages and it is capable of
executing several processes concurrently. GO is efficient for the
applications related to Cloud services; Media platforms; Google products;
On-demand services. It has a few advantages owing to a small number of complex
functions and simple syntax, GO is easy to learn, has a good library and
advanced tools for statistical analysis. Like other programming languages, GO also
has a few limitations-- The small number of packages: Insufficient error
handling and a limited number of frameworks.
· Rust. Rust is a new OOP language designed to cater to emerging requirements. #Rust
focuses on thread safety and performance. However, Rust is considered complex
and with a steep learning curve. The motivation to create Rust was to
create a language that would make system-level programming more secure and have
concurrency to simultaneously execute several calculations, instructions, and
commands. Amazon and Microsoft are supporting Rust for its further
enhancement.
· Ruby. #Ruby is a dynamic, interpreted, reflective, object-oriented,
general-purpose programming language. It was designed and developed in the
mid-1990s by Yukihiro "Matz" Matsumoto in Japan. It is very
powerful in handling Big Data More details
are given in Chapter 10,
· R Studio. It is a powerful OOP
language, particularly designed to handle statistical data and
carry out predictions as per trends. Data Scientists use R for statistical modelling
and forecasting.
· Matlab. It is a very user-friendly programming
language and very good graphical interface. Matlab is suited for
telecommunication applications like 5 G. It is easy to learn and
apply in many engineering applications.
Software Project
Management (SPM) Trends.
In today’s
emerging business scenario and fast-moving technology revolution, SPM has
become a very challenging task. This challenge is due to rapidly changing
Software Products, Services, Software Tools, a variety of Computing Platforms,
many Operating Systems, Browsers, Mobile Input /Output Devices. This is further
compounded since most Customer Requirements (CR) keep growing in terms of
scope, quality and security issues. Infect, as the project progresses, the
customer’s expectations become more important than the original CR. The
customers often ask for earlier delivery to beat their competitors. Some
customers like continuous delivery and progressive integration of modules to ensure
the early success of their projects.
In the recent
past, Waterfall Model, V-Model, Spiral Model, Incremental Model and Iterative
model were used for executing various software projects. In these
models, Software Development Cycle (SDC) was often a lengthy and tedious
process, resulting in delays, many bugs and costly rework. Hence
there was an urgent need for SDA to adopt continuous development, continuous delivery and continuous deployment of executable software
modules. As a result, there has been a major shift in the Software
Development Environment (SDE), which is briefly given below:
· #Agile computing. It invites close participation of the customer and
developer during all stages of SDC. The availability of SCRUM has
brought in more transparency and early participation of customers with
continuous development and continuous delivery/deployment. In this
approach, software packages (small but fully functional modules)
are quickly and frequently delivered for download, testing and use by
the customer. Another new feature of Agile is that CR is not a written down document to be
submitted once and frozen before the start of the project. Instead, CR is
expressed in the form of storytelling, where the customer/representative tells
the requirement in the form of a story to the implantation team. Together, they
comprehend and break it down into smaller modules, to be implemented and
delivered frequently.
· # Cloud Computing. It provides
unlimited hardware and software resources on the concept of “Pay as you Use”,
The data is distributed over many servers of the cloud. Data can
be of very large size and variety and it is processed at great
speed. This helps all small to large customers by not
investing their large amount on one-time buying of hardware and software but to
have scalable resources with flexibility to reduce/ expand at
will. IT team has to be open to newer software tools to get the best
out of cloud computing. More details are given in Chapter 09.
· # Big Data. With the rapid expansion of
social media and smart data input/output devices, very large data in
multi-formats is flowing at great speed across the world on a 24x7x365 basis.
This requires a newer concept for data management and using newer software
tools like Hadoop, MapReduce, Pig, and Hive, More details of Big
Data are given in Chapter 9
· Non-SQL Databases. RDBMS is not effective/
efficient in handling unstructured multi-formatted data. Hence, the need to go
for Non-SQL databases like Mysql, Mongo Db.
· Outsourcing. Due to ever-growing global
competition and more complex business processes, there is an urgent need to
ascertain in-house competency and make the best use of own capabilities. The
rest of the project could be outsourced and keep the focus on quality and
efficient integration. It cuts in time, cost and effort to provide higher
overall productivity. It also helps in delivering good quality products in a
shorter time.
· Software Apps. The emerging trend is
to do less coding and develop smart software
applications (Apps), which can be like small to medium
size websites, capable of running on multi-platforms. This trend
is to integrate Apps and get desired functionality in a shorter time with
minimum effort. This approach saves in development time, testing time,
validation effort and overall product cost.
· Software updates and new releases. With
the availability of OOPs languages, like C++, C#, Java, Python, Ruby, Continuous
Delivery and Continuous Deployment have become popular trends in modern
software development. In this approach, without customers waiting
for new features, SDA works continuously to improve the functionality and
efficiency of their products/services. As such, the SDA themselves release new
fixes/ patches for their operational software to delight the
users.
· Non-SQL Data Bases. Earlier
RDBMS like Oracle, Sybase, MS- SQL, IBM- DB1, Real-Time Distributed
RDBMS were very popular. These RDBMS were suitable both for
standalone small users as well as enterprise versions of RDBMS for bigger
industrial houses. The current trend is in favour of using Non-SQL
DB like MySQL or Mongo.
· # Data Science. Data Science is
becoming as popular as computer science. Python,
R and Data Science focus is towards statistical
modelling and handling large data. It supports Machine Learning,
Forecasting, Innovation and Statistical Modeling.
· #
Embedded Software. Most
organizations are depending on AI/ML, Robotics and Drones to transform their
processes and business practices. AI and Robotics applications are linked to
the efficiency of microprocessors, embedded software, algorithms and sensors This
requires experts in embedded software for operating sensors, aerial
photography, scanning and inter-communication among various devices.
· Software for Blockchain. # Blockchain
is one of the latest technologies in the Digital world. Bitcoin
Technology (BT) which is based on the Blockchain concept of distributed ledger had brought crypto-currency with
a bang and has already validated the Blockchain technique of handling financial
transactions. Blockchain-based apps known as distributed apps (DApps) are
becoming popular options for developers who are working to create
decentralized and secure open-source solutions. Distributed e-ledger is
efficiently processed with programming languages like Python and Ruby. More
about Blockchain is covered in chapter 15.
· Cross-Platform Development Tools. In
the recent past, most software Developments required a single platform like IOS
or Android. After developing the initial Apps for one platform, SDA
could create another version for other platforms. Obviously, it
needed extra time, effort and cost. For universal use of Apps across all
platforms, SDAs are now using new software tools like Microsoft’s Xamarin or Google’s
Flutter. These software tools help software developers to
quickly develop apps, which can efficiently run on all desktops/ Laptops,
Tablets and Smart Phones.
· Software for #IoT. Since 2017, IoT has become
a very popular technology, where many vehicles,
machines and assemblies in the production line, household equipment and devices
need to communicate with each other; All these “Things” have embedded sensors
and software to interact with each other in real-time and without human
intervention,. As new mobile communication technologies like 5G is now
available, more devices will interact and take action in autonomous
mode. More is covered in chapter 6.
· Progressive Web Apps. Leading
software companies like Google, Microsoft and Adobe are
already developing Progressive Web Apps which will be easy to integrate
and offer easy accessibility from anywhere, anytime by anyone using any
browser or device. This environment will provide more job
opportunities for IT professionals.
· Low-Code Development. Traditional, software
development required a lot of customization and at times, rework due to
ever-changing Customer Requirement (CR). Consequently, it needed a dedicated
team of system analysts and designers and coders to implement an assigned
software project. This was costly in terms of resources and lacked
reusability of software assets, Emerging trend is to cut the software
development cost and ensure early delivery to delight the customer, the
SDA trend is to go for low-code software
development resources, making it easy to code applications through
Graphical User Interfaces ( GUI) .
Summary. The use of emerging
technologies and best business practices will evolve cost-efficient, economical
and enduring business solutions. However, advances in emerging technologies and
IT are taking place so fast that new developments in business processes find it
hard to keep pace with it. In most cases, before current processes stabilize, new processes come up quickly to replace the current
ones. This is impacting organization structures and the sustainability of
global alliances. Luckily, Low-code development platforms with
drag-and-drop features are gaining popularity. #Low-code development enhances the productivity of software products and services without extra time, effort
and cost. Low-Code makes it easier for an average coder to quickly and
easily interface /integrate various modules.
In the last 10 years,
microchip technology has advanced very rapidly. This has provided a
much-awaited boost to embedded software for micro-processers and other
communication devices. It must be known that programming for Robotics, Drones,
Gaming, Animation, Block-Chain, ML and AI applications is not simple programming
but requires sound knowledge of advanced programming and hands-on experience of
working on live projects. To stay in demand during the technology wave,
IT professionals need to quickly pick up newer software skills and
gain good competency say in Python, or Scala, Ruby, # Hadoop, MapReduce, Data Science and Embedded software.
There is ever increasing
demand for software experts in these areas and a continued shortage of good
software professionals. Fortunately, a number of leading universities and
engineering colleges have already restructured their curriculum of Computer
Science and Information Technology at UG and PG levels to cater for market
requirements. The onslaught of Covid-19 since Jan 2020 has put a lot of
pressure for online learning and working from remote locations /
Homes. Employers of software companies and organisations adopting
new technologies are ready to pay the most lucrative pay package. As such, many
professionals from other than the IT/ Computer Science discipline are acquiring
required programming skills and moving into the high demand IT
field. This will soon mitigate the shortage of high-end
software professionals
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