In the software development process, there are various types of tasks associated with coding, similar in nature and highly critical, based on which roles are determined. Here, we discuss 5 types of roles that a software developer team would have. However, different types of software development teams assume different structures, and so, the team composition may vary from context to context. Let’s get an insight into these main 5 types of roles associated with core development:
As core team members, software developers work in a cross-functional environment to perform and be a part of a broad range of activities—including designing, developing, building, deploying, and maintaining software.
Software developers drive the software development lifecycle (SDLC), ensuring that the requirements of each stage are fulfilled before the software is advanced to the next stage. They carry the responsibility of translating planning and requirements into a functional software.
A computer programmer uses programming languages like Java, C++, C#, Python, Golang, PHP, etc. to write code, conduct code reviews, and fix bugs. This includes coding and managing visual elements of the software as well as programming for querying databases, operations over databases, routing communication, processing orders, and more. So, in modern software development team structure, programmers are always at the helm of operational efforts, since the efficacy of the application depends upon their efficiency.
Businesses lacking the expertise in software development grapple with a common question – how to set up a software development team. Well, the first obvious thought offering the answer is – to build a team of developers, that’s enough. Many overlook software engineers, taking them as developers.
A software engineer with engineering education and skills applies principles of software engineering to manage and perform tasks associated with software development. Software engineers are problem-solvers. They look into the intricacies of real-world problems and maintain a scientific approach to provide software engineering solutions.
Software engineering is a wholesome job with regard to software development, which is getting increasingly complex and simultaneously intelligent with advancing technologies such as microprocessors, sensors, AI, machine learning, and cloud computing.
Most software development projects these days are machine learning and AI-based. In recent years, thus, people with strong programming, logical, mathematical, and domain skills have become a core part of the team. These are data scientists. So, when building a software development team for your next product, do include a data scientist in your team.
Other way round, the growing demand for data scientists in software development projects demonstrates the increased use of technologies like AI, IoT, and Machine learning in software.
Modern software is capable of harnessing enormous amounts of data and using the learned intelligence to identify patterns, spot anomalies, and make recommendations.
Data science specialists navigate the data pipeline from acquisition to publication, making sure that predictions and recommendations made by the software are accurate.
Key skills required to succeed as data scientists include programming expertise in languages such as Java, Python, R programming, Julia, and Scala. And most importantly, it requires a sound understanding of machine learning, deep learning, natural language processing (NLP), text analytics, regression analysis, data analysis, data manipulation, data cleansing, and cluster analysis.
Software Research professionals in software development possess key skills of basic research, concept formulation, development (preliminary use of programming to bring into light the underlying ideas), and internal enhancement and exploration.
The findings of the research may vary, depending on the goals such as improving ways or selection of alternatives to architectural style, design patterns, frameworks, and operational techniques for development and implementation.
While these professionals are part of the core software development, they are not everything to the software development process. Professionals involved in software development depend on the software project type.
No two software development projects are exactly the same, because the objectives of each would be different. Here are the two most common software development project types based on objectives:
One of the common software development project types is custom software development, which is mainly developed to address specific organizational needs. Custom software has user-centric features and design, which enables a specific category of users in the organization to utilize the benefits of the software.
The users and the organization in itself is a major determinant of who will be involved in the process and the type of software development knowledge and skills one should have. For instance, according to the National Science Foundation, USA, nearly half of the firms in data processing, architectural & engineering, professional scientific, and technical services, automotive, pharmaceutical, mining, and scientific R&D invest in custom software development processes.
Another example of software development is customized off-the-shelf software (COTS). COTS is designed to meet the needs of a large segment of users in the same industry or those who perform the same type of tasks but are in different industries. Google Sheets or Microsoft Office are examples of customized off-the-shelf software products which address the needs of a vast category of users, regardless of their business domains.
Software Company In BangladeshBuilding a software product that caters to a large userbase is complex, not just on the development part, but also in areas such as requirement analysis, UI and UX design, database management, and IT security. A large group of non-developer communities but with working knowledge of software development, such as business analysts, product managers, general researchers, and UI and UX designers are required to complete and manage the software development process.
Although these two are major categories of software development project types, there are several factors that categorize them further such as the use of technologies like AI, coding efforts, computing capabilities, and cloud deployment. These factors add to the complexity of the software development, but at the same time, make it more effective for the users.
Modern software is laced with new technologies to make them more effective for users. These technologies are the highlight of the software, namely:
Artificial Intelligence (AI) is the simulation of human intelligence processes such as reconnecting to past experiences and finding patterns to arrive at a decision or make recommendations. AI based software applications replicate the human intelligence processes to apply knowledge and find solutions autonomously. For example, AI-powered assistants, autonomous vehicles, facial recognition tools, industrial robots, and more.
Artificial Intelligence Software is a combination of tools and techniques such as training machine learning algorithms, image recognition tools, natural language processing, neural networks, and various other specialized hardware and software applications.
These tools and techniques allow the software to process a large amount of data for finding correlations, spotting anomalies, and determining patterns. High quality data and powerful machine learning algorithms allow the AI based applications to use these 3 major cognitive skills:
Learning: This aspect of AI programming focuses on the use of data and algorithms to emulate the human learning process in order to improve the accuracy of their predictions and recommendations.
Learning: This aspect of AI programming focuses on the use of data and algorithms to emulate the human learning process in order to improve the accuracy of their predictions and recommendations.
AI-based software applications are used in various industries to perform detail-oriented, repetitive tasks to reduce the administrative workload, generate insight to improve on decision-making, and predict behavior and patterns to make recommendations.
IoT application development is the process of building software applications that transform data acquired from machines into valuable information. The application processes the data collected through the sensors over cloud to generate insight. This insight helps product owners learn to manage the product more effectively and ensure their optimal utilization.
Connected devices: These devices span over anything from medical devices to agriculture equipment, and automobiles to consumer electronics. Connected devices come with unique identifiers (UIDs), embedded systems such as sensors, processors, and communication hardware along with the ability to transfer data over a network without human interventions.
IoT Gateway: IoT gateway is a hardware or computer program that links connected devices to the Cloud or other data analytics systems. It allows bi-directional data flow between the connected devices and the cloud. The main role of an IoT gateway is to facilitate inter-device communication, device-to-cloud communications, data preprocessing, IoT device security, and Intelligent Edge.
Data System: This aspect of the IoT focuses on collecting, refining, and organizing data to get information out of them. The process begins with storing data to a centralized location and covers policies, practices, and procedures for full cycle data management, ensuring agility, security, and scalability.
IoT application development is about building applications that capture and manage the flow of data, from devices to applications via various types of IoT sensors and vice versa to keep the organizations and product owners informed, and the role of IoT application development companies is to collect that data seamlessly and generate insights that create value.
According to IBM, “Blockchain is a shared, immutable ledger” that enables users to record transactions and track the history of assets and transactions in the business network.
It covers both tangible and intangible assets varying from car, house, and cash to intellectual property rights, patents, copyrights, branding, etc. The fundamental components of blockchain technology are:
Distributed ledger: The access to the ledger is available to everyone in the network. Transactions in the ledger could be recorded only once, thus eliminating the chances of duplicate entries.
