7 Ways to Future-Proof Your Software Development Process

Statistics claim there are 8,945 programming languages, yet we bet neither developers nor businesses need all of them to get market traction. As we enter Q1 of 2025, the programming world hasn't changed much; almost every programming languages rating is still shaped by a mix of established languages and modernized classics like Java and Python. However, it has shifted to include innovative tools like AI, blockchain, data science, and IoT. 

To cut through the clutter, we've analyzed the latest trends and compiled a list of the top 10 programming languages for 2025, an overview of different rankings, and the best ideas on choosing a programming language for a project. Read on for success.

Programming Languages Ratings

As of early 2025, some programming language rankings are still based on 2024 data. However, developers, businesses, and educators can leverage PYPL, TIOBE, and GitHub insights to guide learning efforts, hiring strategies, and project development. 

Read all the ranking lists and find the most desired programming language in 2025.

PYPL Ranking 2025

The PopularitY of Programming Language (PYPL) index is a Google-powered snapshot of programming language popularity. It tracks tutorial searches, giving a clear view of which skills are in demand—a crucial tool for tech trend analysis.

As per the PYPL report, 5 five most popular programming languages are: 

The TIOBE Ranking 2025

The TIOBE Index provides a monthly snapshot of programming language popularity. It ranks languages by global developer presence, educational material availability, and industry adoption based on search trends from platforms like Google, YouTube, and Wikipedia. Amazon and Baidu.

According to TIOBE, the five most popular programming languages are:

The GitHub Ranking 2025

GitHub is a global code hub shaped by Fortune 50 companies. While GitHub doesn't provide rankings, tools like GitRanking organize repositories, and DevRank measures developer influence. Here are the dynamics of popularity from the latest GitHub report:

IEEE Spectrum Ranking 2025

From GitHub commits to Stack Overflow threads, this annual roundup analysis cuts through the noise of top programming languages with three crystal-clear metrics: established giants, breakthrough performers, and market demand. Here is the latest technical ranking IEEE report:

RedMonk Ranking 2025

RedMonk ranks programming languages twice a year, blending GitHub code usage with Stack Overflow engagement. They track adoption trends and developer preferences by combining code usage with developer discussions. Over 45% of software companies use these quarterly rankings to guide their technology decisions.

Here are the latest insights from their programming language RedMonk rankings:

Stack Overflow Developer Survey 2025

The Stack Overflow Developer Survey collects data from over 30,000 developers to explore their opinions and habits. It highlights trends in technology usage and preferences, illustrating how new tools and frameworks rise in popularity each year while others fade away.

According to this survey, the five most popular programming languages here are:

What Affects Programming Language Rankings?

Language rankings depend on GitHub stats, Stack Overflow activity, and job demand. Tech giants can elevate a language overnight. Community support ensures good documentation, while technical strengths drive relevance in AI, cloud, and mobile. Overall, enterprise adoption hinges on commercial investment in tools and frameworks.

Why Do Developers Switch Languages?

Market demand and salary potential often trigger language switches. New projects at work may require learning unfamiliar stacks. Some developers migrate when they hit technical walls with their current language. Others switch purely out of curiosity to explore fresh programming concepts. Better developer experience—from cleaner syntax to powerful debugging tools—can seal the deal.

How Do Trends Impact Programming Language Rating?

Tech trends reshape the programming landscape constantly. Cloud computing favors languages that handle concurrency well. Mobile development boosts cross-platform-friendly languages. AI and ML create demand for specialized numerical computing capabilities. Modern software architecture—like microservices and serverless—influences language choice based on performance needs. Open source momentum can make or break a language's trajectory. Universities follow these shifts, molding new developers' skills accordingly.

Why Do Some Languages Rise or Fall in Popularity?

Languages surge when they solve pressing problems—like Rust addressing memory safety. Corporate champions (Google with Go, Microsoft with TypeScript) accelerate adoption through resources and integration. Growing ecosystems create network effects, attracting more developers and tools. Languages decline when they stagnate or lose their edge to newer alternatives. Yet some persist through enterprise inertia, particularly in legacy systems. Success hinges on balancing innovation with stability while nurturing a vibrant developer community.

Top 10 Most Popular Programming Languages in 2025 

From crunching data and financial management apps to renewable energy systems, optimizing solar panel efficiency, and reducing carbon footprints—programming spans different fields of humankind. 

But here's the million-dollar question: with so many programming languages out there, which ones are worth learning? We turn to the database of the most desired and loved programming languages from Stack Over Flow. Here is the list of the top 10 below:

1. Python

With clean syntax and broad applications, Python is a go-to language for web development, AI, and data science. Supports procedural, object-oriented, and functional programming, consistently placing it at the top of programming language rankings.

Pros:

• Easy to Learn: Simple syntax makes it beginner-friendly.
• Extensive Libraries: Large collection of standards and toolkits available.
• Integration: Works well with languages like C and C++.
• High Demand: Especially among startups.

‍Cons:

• Slower Speed: Slower compared to compiled languages.
• Limited Concurrency: Global Interpreter Lock (GIL) limits true parallelism.
• High Memory Use: Consumes more memory than some alternatives.
• Complex Debugging: Dynamic typing can complicate the debugging process.
• Poor for Certain Applications: Less suitable for mobile, embedded, and real-time systems due to efficiency concerns.

Common Use Cases of Python:

Thanks to TensorFlow, Python excels in data science and web development, particularly in AI and ML. From Instagram to Dropbox, it powers a wide range of applications. We bet that in years ahead, we'll still see Python as the number №1 solution, ranked in most ratings.

2. JavaScript

Among all the most popular programming languages, JavaScript remains the "default" one for web developers. Born for the browser, JavaScript now dominates both frontend and backend, thanks to Node.js and a massive npm ecosystem. In 2025, it will continue to dominate as a leader on GitHub in terms of code volume.

Pros:

• Versatile & Rich Ecosystem: Works for front-end, back-end (Node.js), and mobile, with a vast array of frameworks and libraries (React, Angular, Vue).
• Client-Side Responsiveness: Executes directly in the browser, reducing server load and improving user experience.
• Interactive Web Pages: Enables dynamic features, animations, and real-time updates.
• Large, Active, and Supportive Community: Ensures ample resources and solutions.

Cons:

• Security Vulnerabilities: Client-side code is visible and susceptible to attacks (XSS).
• Inconsistent Browser Behavior: Code may render differently across browsers.
• Performance Limitations: Heavy client-side JavaScript can impact loading times.
• Debugging Complexity: Client-side debugging can be challenging.
• Single-Threaded Constraints: Limits performance for complex, concurrent operations.

Common Use Cases of JavaScript:

JavaScript powers web development with React, Angular, and Vue.js for interactive interfaces and single-page apps. Node.js extends its reach to server-side development, real-time apps, and microservices.

3. TypeScript

TypeScript is a Microsoft-backed superset of JavaScript that adds static typing and class-based object-oriented programming. It compiles to JavaScript and runs anywhere JavaScript does. Strong type safety and advanced tooling make it a top choice for large-scale development. In 2025, it will remain in the first position of top programming languages.

Pros:

• Type Safety: Static typing helps catch errors during development rather than runtime.
• Enhanced IDE Support: Better code completion, refactoring, and error detection in development tools.
• JavaScript Compatibility: Can use all JavaScript libraries while adding type safety.
• Enterprise-Ready: Perfect for large codebases and team collaboration.
• Improved Code Quality: By catching errors early, TypeScript reduces the likelihood of bugs in production.
• Better Collaboration: Type annotations make code more self-documenting, making it easier for teams to understand and work on the same codebase.
• Scalability: TypeScript is particularly well-suited for large and complex applications.

Cons:

• Type Definition Files: Some libraries may lack or have outdated type definitions.
• Complexity: Initial installation and setup might be a bit tricky.
• Development Time: Writing types can slow down initial development speed.
• Compilation Step: TypeScript code needs to be compiled into JavaScript before it can be executed.
• Increased Code Size: Type annotations can increase the size of your code.
• Runtime vs Compile time: while Typescript catches many errors at compile time, it does not guarantee that there will be no errors at runtime.

Common Use Cases of TypeScript:

It's the default for Angular and powers tools like Visual Studio Code and Slack. Its compatibility with Node.js makes it a top choice for full-stack development, prioritizing type safety.

4. Rust 

Rust, developed by Mozilla Research, delivers memory safety, high speed, and a growing ecosystem. Its ownership model eliminates memory vulnerabilities without a garbage collector. Adopted by startups and major tech firms, Rust is a rising star that won't stop raising its popularity for performance-critical development.

Pros:

• Memory Safety: Catches errors before runtime, not during production crashes.
• Performance: Matches C/C++ speeds with higher-level abstractions.
• Cargo: A modern package manager that just works. 
• Cross-Platform: Write once, deploy anywhere approach.
• WebAssembly Ready: First-class support for the web's low-level powerhouse.

Cons:

• Learning Cliff: Ownership and lifetimes concepts demand serious study.
• Unforgiving Compiler: The "fighting the borrow checker" experience is real.
• Build Times: Complex codebases can test your patience during compilation.
• Young Ecosystem: Some specialized tools are missing in the standard of mature languages.

‍Common Use Cases of Rust:

Rust shines in critical infrastructure: Firefox's core engine, Discord's real-time systems, and cutting-edge blockchain platforms. It's the go-to choice for projects where failure isn't an option—embedded systems, operating system kernels, and game engines pushing performance boundaries.

5. Go (Golang)

Go, developed by Google, is a high-performance language known for simplicity, efficiency, and scalability. In 2025, Go continues to rise with native scaling and a lightweight yet productive design, often chosen over Java or C# for backend and DevOps. While Rust challenges C++, Go is a streamlined alternative for modern software teams. Consequently, in recent years, it frequently tops each rating of programming languages.

Pros: 

• Simplicity: Clean and straightforward syntax, easy to learn. 
• Concurrency: Excellent built-in support for goroutines and channels. 
• Performance: Fast compilation and execution speeds, comparable to C++. 
• Garbage Collection: Automatic memory management, reducing the risk of memory leaks. 
• Static Typing: Catches type-related errors at compile time. 
• Standard Library: Comprehensive and well-documented standard library. 
• Cross-Compilation: Easy to compile for different platforms. 

Cons: 

• Lack of Generics: Limited code reuse for different data types (now addressed but still evolving). 
• Verbose Error Handling: Requires explicit error checking, which can lead to verbose code. 
• Limited Expressiveness: Some developers find the language less expressive than others. Dependency Management: Older dependency management was considered cumbersome (now improved with modules). 
• Smaller Ecosystem: While growing, the ecosystem is smaller than more established languages.

‍Common Use Cases of Go:

Go is widely used in cloud-native development, web development (server-side), and network programming. It's popular for building microservices, distributed systems, and command-line tools. Companies like Google, Docker, and Kubernetes utilize Go for their infrastructure and tooling.

6. C#

C# is a modern, object-oriented coding language developed by Microsoft as part of the .NET platform. It blends the robustness of C++ with the simplicity of Visual Basic, featuring strong type safety, versioning, and scalability support. In 2025, C# will remain the strongest language in the Microsoft ecosystem and seems not to lose its popularity.

Pros:

• Type Safety: A strong static typing system prevents common runtime errors and improves code reliability.
• Rich Ecosystem: Extensive standard library and NuGet package ecosystem for nearly any functionality.
• Cross-Platform: .NET Core/.NET 5+ enables true cross-platform development and deployment.
• Performance: High-performance capabilities, especially with recent memory management and compilation improvements.
• Modern Features: Pattern matching, nullable reference types, LINQ, and continuous language evolution.

Cons:

• Platform Dependencies: While cross-platform, some libraries still have Windows dependencies.
• Resource Usage: Higher memory footprint compared to lower-level languages.
• Compilation Required: Must be compiled before execution, adding a build step.
• Learning Curve: Complex features and patterns can be challenging for beginners.
• Verbose Syntax: More ceremonial code compared to dynamic languages.

Common Use Cases of C#:

C# is widely used in enterprise software development, particularly in the Microsoft ecosystem. It powers everything from ASP.NET web applications to Unity game development, Windows desktop applications, and cloud services on Azure. 

7. C/C++

C and C++ pioneers of modern computing remain unmatched in hardware control. C provides procedural efficiency while C++ adds object-oriented features; both deliver raw performance critical for systems development.  In 2025, it remains first among the 10 top programming languages.

Pros:

• Zero-Overhead Abstraction: Efficient execution with direct hardware access.
• Precise Memory Control: Fine-grained resource management without a garbage collector.
• Cross-Platform Compatibility: Runs on diverse architectures and operating systems.
• Extensive Legacy Codebase: Decades of existing libraries and software.
• Deep System Integration: Ideal for OS development, embedded systems, and performance-critical applications.

Cons:

• Manual Memory Management: Prone to leaks and undefined behavior.
• Complex Syntax: Challenging constructs like C++ templates.
• Slow Compilation: Long build times for large projects.
• Security Risks: More exposure to vulnerabilities like buffer overflows.
• Steep Learning Curve: Requires deep understanding of low-level concepts.

Common Use Cases of C/C++:

These languages drive OS development, game engines, embedded systems, real-time applications, and high-performance computing, including Chrome's V8 and major databases.

8. R

R is an open-source language for predictive analytics and data visualization, built with C, C++, Fortran, and R. It features S3 and S4 frameworks for flexible data modeling and method dispatching, which allows for flexible data modeling and method dispatching.

Pros:

• Statistical Analysis: Built-in capabilities.
• Visualizations: Publication-ready.
• Packages: Extensive scientific libraries.
• Math Operations: Advanced support.
• Community Support: Favorite among researchers.

Cons:

• Big Data Performance: Struggles with big data performance.
• Memory Usage: Can spiral quickly.
• Syntax Complexity: Unique syntax challenges newcomers.
• Package Quality Variance: Package quality varies wildly.
• Limited Use Cases: Beyond data analysis.

Common Use Cases of R: 

R dominates biotech labs and research institutions. Companies like Pfizer and Merck crunch clinical trial data while hedge funds model risk. Academia relies heavily on R for peer-reviewed research and statistical validation.

9. Java

Java is a high-level, object-oriented language known for its platform independence. With ongoing improvements, including syntactic enhancements and advancements in GraalVM and WebAssembly, Java is expanding beyond traditional backend development to stay competitive.

In 2025, Java will steadily retain its leadership in the top 10 programming languages as a workhorse for enterprises and large high-load systems. If you plan to work with large corporations, the banking sector, or any system that requires stability, Java is an excellent choice.

Pros:

• Platform Independence: Code runs anywhere via the JVM.
• Rich Ecosystem: Extensive libraries and frameworks like Spring and Hibernate.
• Concurrency Support: Built-in multithreading enhances performance.
• Security Features: Strong protections make it ideal for web and enterprise applications.
• Community Support: A large user base ensures abundant resources and tools.

‍Cons:

• Verbose Syntax: Requires more code compared to modern languages like Python.
• Performance Overhead: Slower than lower-level languages due to JVM interpretation.
• Memory Intensive: Consumes more memory than C or C++.

Common Use Cases of Java: 

Java is everywhere—from Google's backend to Fortune 500 banks. It's vital for Android, Spring, and high-load systems, and with cloud innovations, it continues shaping enterprise tech, big data, and finance.

10. PHP

Once a simple scripting language, PHP now drives much of the web, including WordPress and Facebook. Modern frameworks like Laravel have refined it, making PHP more efficient and scalable than ever.

‍Pros:

• Web Integration: Excellent integration with HTML and web servers.
• Easy Deployment: Simple setup and hosting requirements.
• Large Community: Extensive documentation and community support.
• Framework Ecosystem: Modern frameworks like Laravel provide robust development tools.
• Cost-Effective: Wide availability of hosting and developers.

Cons:

• Inconsistent Design: Historical inconsistencies in function naming and parameter ordering.
• Security Concerns: Easier to write insecure code if not following best practices.
• Type System: Weak typing can lead to subtle bugs (though improving with recent versions).
• Performance: Not as performant as compiled languages for complex applications.
• Legacy Code: Many older codebases use outdated practices.

Common Use Cases of PHP: 

PHP continues to dominate CMS, e-commerce, and traditional web development. Ideal for small to mid-sized projects, it remains the backbone of WordPress, Wikipedia, and countless content-driven platforms.

How to Choose a Programming Language for a Project?

While language wars rage on Twitter, programming languages ratings "hustle-and-bustle with numbers," successful tech leads know it's not about which language is "best" – it's about which one serves your specific mission. Let's delve into tips on how to figure out what programming language suits your business best.

Project Type

• Identify the target platform (e.g., web, mobile, desktop, or multi-platform).
• Define the application's purpose and user environment.

Language Features

• Evaluate performance, functionality, and built-in capabilities.
• Assess support for modern coding paradigms (e.g., functional, object-oriented).

Ecosystem

• Explore the availability of tools, plugins, and development environments.
• Investigate the breadth of open-source contributions and ecosystem maturity.

Scalability

• Analyze how well the language supports large-scale applications.
• Consider its ability to handle increased user loads or data growth efficiently.

Learning Curve

• Determine how intuitive the language is for new developers.
• Assess the time required to become proficient compared to alternatives.

Compatibility

• Verify how seamlessly it integrates with existing systems and APIs.
• Check for cross-platform support and interoperability with other technologies.

Industry Demand

• Research hiring trends and industries actively using the language.
• Examine its prevalence in job postings and developer surveys.

Support

• Review the quality and availability of official documentation.
• Look into active communities, forums, and professional support channels.

Future Trends

• Monitor the language's adoption of cutting-edge technologies (e.g., AI, blockchain).
• Analyze its trajectory in developer rankings and long-term viability.

Here is a detailed overview of the area domain and programming language features and connections:

Don't Fall Behind With the Wrong Programming Language

In most cases, when it comes to real development projects—it's not just about code but performance, scalability, and future growth. Checking the most popular programming language ratings ensures a wise, future-proof decision. Choose a language that fits your needs, leverages your team's expertise, and keeps you ahead of the curve. With Darly Solutions, you're always one step ahead.

Backed by deep industry knowledge and hands-on experience, we help businesses navigate the ever-changing tech landscape. Whether launching a startup or scaling an enterprise, don't let the wrong decisions hold you back—let's build for the future together.

These days, Fintech is becoming one of the world's fastest-growing industries. Every year, the number of new Fintech startups increases. In 2024, more than 13,000 such enterprises were recorded in the Americas.

Financial technologies include online banking applications, lending platforms, trading platforms, and robo-advisor apps for investing and budget planning. All these innovations demand top-notch Fintech solutions to serve customers, so aspiring Fintech startups need to find a talented team that can build an advanced product.

Key considerations when hiring

Before hiring a FinTech development company, it’s crucial to ensure the specialists have all the essential hard and soft skills. This way, the Fintech application project will have more chances to succeed. So, to hire reliable developers for your project, you need to understand the essential compliance requirements, which you will need to check. 

What are the must-have competencies of web development companies for Fintech?

• Technical knowledge. The company's developers must be well-versed in all the necessary coding languages, frameworks, technologies, and security norms. 
• Background in your niche. Check if a company has a portfolio of projects related to the financial field. 
• Familiarity with applicable finance legislation. The company must know industry norms such as PCI DSS and GDPR.
• Social skills. Seek a team that is able to ensure transparent communication, flexibility, well-organized teamwork, and attention to detail.

Experience in FinTech

Familiarity with the industry is obligatory for financial services development because the specialists must comprehend the main finance principles. A deep understanding of monetary standards and risk management allows developers to craft solutions that meet the niche requirements. Look for a company that has worked on apps or websites for mobile banking, budget management, cryptocurrency wallets, or other products related to Fintech app development. 

Technical Expertise

First of all, make sure the tech specialists know the necessary programming languages. For instance, frontend development for Fintech may require knowledge of JavaScript, libraries and frameworks such as React.js, adaptive and cross-browser layouts, as well as principles of responsive web design and great user experience. At the same time, Python paired with Node.js may be useful for backend development for Fintech.

Secondly, developers must ensure the product's security. To achieve this, they must understand finance APIs and data encryption protocols. Similarly, implementing secure coding methods and following best practices are critical to providing data security. Additionally, expertise in cloud and blockchain technologies can be vital for the safe and reliable launch and scaling of Fintech products.

In many cases, especially for lending platforms, a key functionality is digital credit scoring—the ability to assess a user’s creditworthiness based on real-time data automatically. Implementing such systems requires backend development expertise and experience working with financial scoring models, third-party data providers, and data compliance protocols. A development partner with proven experience building custom scoring logic can help you avoid regulatory risks and launch a more competitive product.

Security and Compliance Knowledge 

Fintech solutions must meet the latest regulations and standards for user data security. Since Fintech startups and online banks carry sensitive customer data, they are often victims of cyber attacks. That’s why there are legal regulations aimed at the safety of clients and ensuring secure accounting transactions. So, to get secure Fintech development services, check if a company has relevant experience and understanding of the best practices in data protection along with industry norms such as PCI DSS and GDPR.

Communication and Collaboration

Effective communication is crucial for successful Fintech website development. A simple and streamlined interaction provides quick response, the ability to adjust tasks quickly, and full transparency of their implementation. Also, the tech team members must evolve their problem-solving skills, be adaptable, and demonstrate excellent collaborative skills. The last thing can be reached only by an experienced provider, so you should assess the management style in a company.

Research Potential Partners 

Before hiring a Fintech development company, conduct research on your own. A company must have a website providing all the information about its expertise, portfolio, and contact details. Besides, don’t forget to check customers’ testimonials to determine the quality of the services provided. Likewise, case studies of Fintech projects will best demonstrate a company’s expertise and outcomes achieved. 

Develop a Request for Proposal

When you already have a candidate for possible cooperation, the next step is to write a project proposal. Initially, you need to define the project's goals, target audience, desired functionality, and budget. This process will help your possible contractor fully understand your business demands and provide you with a personalized offer.

Conduct Interviews

While conducting a technical interview, ask detailed questions about the development process to check your possible contractor’s skills. Secondly, the organization's leadership style and structure should be analyzed. Inquire about any cross-functional initiatives the company has worked on.

It’s also important to find out who is on the team. In addition to the usual members of a tech team, such as a technical lead, developers, and QA testers, there should also be an expert who works on UI/UX design for Fintech. And, of course, don’t forget to ask about their previous experience in the niche and evaluate their grasp of your business needs and vision of the product.

Portfolio Review

When selecting a software development company, experience is a key consideration. And the easiest way to assess it is by checking the portfolio. Companies that have been on the market for a while usually have numerous projects. However, you need to pay the strongest attention to those connected to the Fintech industry. Check for mobile banking apps, home loan calculators, or trading tools technologies to make sure their design, usability, and the achieved results are close to your goals and needs. 

Conclusion

Developing a Fintech product is not an easy task. Besides the fact you need to retain customers by providing an outstanding service, you also have to worry about things like regulations and data security. That’s why it’s essential to learn how to recruit decent Fintech development specialists. By following the clues given above, you will be able to find suitable candidates.

Interesting fact: there are approximately 8,462 project management methodologies to choose from. Every project manager understands that selecting the right methodology is crucial to getting the job right.

So, how to understand which one is right for your project?

There are many various ways to deliver projects. Generally speaking, these ways are our project management models—applying different principles, themes, frameworks, processes and standards to help provide structure to the way we deliver projects.

Agile is one of the more recognizable project management methodologies. This methodology is best suited for projects that are iterative and incremental. It’s a type of process where demands and solutions evolve through the collaborative effort of self-organizing and cross-functional teams and their customers.

Agile is a methodology that has methodologies within itself, such as Scrum and Kanban. Scrum methodology is one of the most popular and simple frameworks to put the principles of Agile into practice.

Let’s talk about the Scrum and how it works

Scrum is a subset of Agile. It is a framework for agile development that helps teams work together with the customers. Much like a sports team training for the big game, Scrum encourages teams to learn through experiences, self-organize while working on a problem, and reflect on their wins and losses to continuously improve. Its goal is to develop, deliver, and sustain complex products through collaboration, accountability, and iterative progress. According to this, it is not surprising that Scrum is the most widely-used one among the teams.

Scrum team roles

• Product owner: The product owner represents stakeholders, which are typically customers.
• Development team: Group of professionals that consists of three to nine individuals who have the business, design, analytical and development skills to carry out the actual work, solve problems and produce deliverable products.
• Project manager: Manager who ensures the understanding and execution of Scrum is followed. The manager’s responsibilities include coaching and motivating the team, removing impediments during the development, and ensuring that the team has the best possible conditions to meet its goals and produce deliverable products.

Phases of Scrum Model

Now, let’s take a look at the main steps of the development process that Scrum consists of.

Step 1. Product Backlog Creation

A product backlog is a list that contains features to be implemented during the development process. It’s ordered by priority and every item is called a User story. A user story is an informal, general explanation of a software feature written from the perspective of the end user or customer. It helps development teams capture simplified, high-level descriptions of a user’s requirements written from that end user’s perspective. The examples below show how these stories can look like:

• As an internet banking customer, I want to see a rolling balance for my everyday accounts, so that I can keep track of my spending after each transaction is applied

• As a manager, I want to be able to understand my colleagues’ progress, so I can better report our success and failures.
• As a customer, I want to receive an SMS when the item arrives, so that I can go pick it up right away.
• As Max, I want to organize my work, so I can feel more in control.

This structure is not required, but it is helpful for defining done.“Why can’t we just write features or tasks instead?”

Step 2. Sprint Planning and Sprint Backlog Creation

The sprint duration is very important so that the user stories are as small as possible. The typical average sprint duration lasts about 2 weeks. If the sprint duration is small, then the advantage is that more customer feedback can be received and most of the errors and bugs can be addressed earlier. If the sprint duration is long, then it allows the developer to work thoroughly.

The next stage is to do the sprint backlog creation. It consists of user stories that will be completed during the current sprint. The scrum team must select the important user stories and make them into smaller tasks. They need to plan on how to get the task completed. The Scrum team should be capable of finishing all these stories on time. Also, one important thing is to prioritize the necessary tasks.

For example, the goal for Sprint: “A website visitor can order a product”. We discuss with the team and product owner how to implement this. Roughly, customers have to go through three steps to order something: 1) select a product, 2) enter address and billing information, 3) perform the payment. We discover several exception paths. After the discussion about what technology we will use for this goal and how the team will implement this functionality, we start creating the Sprint Backlog.

Below are some of the items that can end up on the Sprint Backlog:

• When an order is placed, send an email to the sales department;
• Allow customers to pay for their order by credit card;
• Encrypt user information in order (e.g. email, address);

Step 3: Working On Sprint and Scrum Meetings

The actual user stories are moved as small tasks in the sprint backlog, where the actual work starts. This is where the implementation of a software application, such as website development, begins.

To begin with, a task board is made with a lot of cards is used. The cards specify the details about the tasks such as assignee, work details, due date or the time duration, etc. The cards can be arranged according to their importance. When work on a task has been started, the corresponding sticker is moved from the “To do” field to the “In progress” one. When work is completed, the sticker can be moved to the “Testing” field, and after the task is successfully tested, the sticker goes to the “Done” field.

For this activity, we use specialized software JIRA and Trello for this task.

In this step the scrum meetings are important as it is done to track the progress status and who is doing what status. The burndown chart is the output of this meeting, as it provides the details about how many tasks are completed and if there are any issues or problems in completing the tasks in the “Work In Progress” columns.

It is also important to notice one more Scrum feature is Daily Scrum meetings. These meetings’ main purpose is to get full information about the current project status and make sure that all team members are on the same stage. During Scrum meetings, every single team member should tell what he has done for the day, which tasks will be the next, and what problems team members faced during the work.

Day by day Scrum meetings help increase the flexibility of the development process. They also allow understanding of what changes should be made.

Step 4. Testing, Product Increment and Sprint Review

The result of every sprint in Scrum is a potentially shippable product increment that can be presented to the customer. After each iteration, the development team creates a new version of a software product and adds new features with increased value. In the end part of every sprint, there is Sprint Review where the overall results can be demonstrated and analyzed. According to this info, the stakeholders can make a decision about further project changes and plan the next sprint.

Step 5. Retrospective and Next Sprint Planning

Retrospective’s main goal is to consider the results and the ways how to improve the development process on the next step. The team should talk about the lessons learned and the pitfalls that were during the development part. An important feature is to improve the work of the Scrum team as a whole. The team should conclude what went well during the working process and what can be done better during future iteration. When the ways of improvement are defined, the team can start and concentrate on the next sprint planning.

Project Closure

The project closure phase represents the final phase of the project management. Around this time, the final product is ready for delivery. Here, the main focus of the project manager and the team should be on product release and product delivery. In this stage, all the activities related to the project are wrapped up.

Once the product is handed to the customers, the documentation is finalized and the project is closed.

Conclusion

The main differential features of Scrum are flexibility and constant progress. It’s provided mostly by regular communication and close cooperation between the stakeholders at each step.

When the sprint is done, the customer can assess the working product functionality at the current iteration and make decisions about how the project should evolve during the next sprints.

Use Case: Web Development

Problem Statement: Important changes need to be implemented on an existing company website.

Scrum team roles:

1. Product Owner: Team Lead
2. Development Team: Developers
3. Scrum Master: Project Manager

Basic Flow of Events:

1. The website needs to be updated.

Using Scrum:

1. Product Owner creates a backlog, i.e. the prioritized changes to make.
2. The development team and the QA team is created.
3. Sprint of 7 days is decided.
4. Project manager is assigned to set up the meetings and help with issues.
5. Tasks are assigned to the team
6. A daily 15-minute Scrum is set up for holding team meetings
7. The website is updated each day with the work done
8. QA notifies issues on the same day
9. Each week, the Sprint Review meeting is held with the CEO for an update on progress

Scrum is best suited for projects that consist of teams of less than seven people who need a flexible approach to deliver a product or service.