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A strategic approach to modernizing code At e-Core, we often partner with organizations whose software technically “works” in production, but just barely. Over time, shifting teams, competing priorities, and tight deadlines lead to codebases that are fragile, expensive to maintain, and risky to enhance. In this context, software refactoring becomes more than a technical task. It’s a business strategy that preserves continuity while unlocking future growth. Defining refactoring: Evolution without disruption Software refactoring is the disciplined restructuring of existing code, improving readability, modularity, and performance, without altering its external behavior. Unlike a full rewrite, refactoring delivers incremental value by: Accelerating feature delivery through cleaner, more modular code. Reducing operational risk by eliminating brittleness and regressions. Lowering total cost of ownership by making enhancements less labor-intensive. Why refactoring matters for business  Healthy codebases have a direct business impact: Faster Time-to-Market: Modular components support parallel development and faster releases. Greater resilience: Decoupled services isolate failures and simplify maintenance. Easier onboarding: Clear architecture and design patterns help new developers ramp up quickly. Sustainable cost savings: Less firefighting, fewer regressions, and lower maintenance overhead. What may look like a simple “cleanup” is often the first step toward digital reinvention. Refactoring techniques In enterprise environments built on Java, C#, or Python, we apply proven object-oriented refactoring techniques to increase cohesion and extensibility: Class decoupling: Split monolithic classes into focused, single-responsibility components. SOLID principles: Apply interface segregation and dependency inversion to stabilize architecture. Composition over inheritance: Build flexible, interchangeable structures. Testability enhancements : Isolate side effects and inject dependencies for better test coverage. These techniques form the foundation of our incremental software refactoring roadmaps. Beyond OO: Choosing the right tools for each paradigm Modern languages blend programming paradigms. We help clients apply the right tools to the right problems: Functional patterns in Python to create concise, side-effect-free data pipelines. Kotlin/Scala hybrids that combine OO structure with expressive functional constructs. C# LINQ and Async for declarative data queries and scalable concurrency. This multi-paradigm approach ensures that systems remain robust, flexible, and expressive. A refactoring story: From debt to differentiation Case Study: Regional logistics provider

In recent years, artificial intelligence has shifted from a futuristic promise to an essential ally in the day-to-day work of development teams. AI for developers, such as code assistants, automated bug analysis, and intelligent test generation, are transforming the way we write software. Reducing repetitive tasks, accelerating delivery, and freeing developers to focus on what really matters, using technology to solve business problems. According to the report The Economic Potential of Generative AI by McKinsey (2023) by McKinsey (2023) , the use of generative AI in software development can reduce time spent on activities like coding, reviewing, and debugging by up to 45%. That’s a significant productivity leap, especially in roles like software engineering, where those tasks take up a large part of the daily routine.  PwC (PricewaterhouseCoopers) also highlights a notable trend: industries with higher AI exposure have seen productivity growth nearly five times greater.

In daily software development, tests are an essential part of the process. By ensuring code coverage, we can mitigate issues, ultimately improving the quality of our code . In this scenario, Testcontainers presents itself as a valuable framework for integration testing, helping developers manage dependencies and create more reliable, reproducible test environments. In this article, we’ll explore how testcontainers can be applied to real-world scenarios to improve the effectiveness of integration tests. 

Test-Driven Development (TDD) is one of the most well-known modern philosophies for achieving a high level of excellence in software development . Like any solid philosophy, however, TDD is sometimes misunderstood and misapplied, making it challenging to implement in certain environments. The discussion about the importance of testing in systems development is nearly as old as programming itself. In the second chapter of The Mythical Man-Month, Frederick P. Brooks Jr. suggested, back in 1975, that half of the time spent on a task should be dedicated to testing. When the testing phase isn’t planned, developers often spend even more time on it unintentionally. In the late 1990s, Kent Beck and others created the concept shown below: 

In today’s fast-paced tech world, companies that fail to adopt effective DevOps practices risk falling behind their competitors and missing out on critical business opportunities. Robust continuous integration and deployment solutions are essential for business continuity and growth. Here are some essential rules to embrace DevOps effectively and stay ahead in the competitive market. Embracing Agile Project Management Why do some companies release new features every few weeks, while others take years? The reason is agile project management. Agile project management is an iterative approach that helps software teams enhance their development speed, increase collaboration, and respond well to current market trends. Tools like Jira Software can help your teams segregate the work into smaller, more manageable tasks for faster deployment. By integrating with Bitbucket or GitHub, your application is already well-documented, with each pull request corresponding to a business object (Story, Task). Encourage teams to add the Jira ticket to the pull request for better tracking and collaboration. Code Review One crucial practice is ensuring that at least two people look at the code before it ships . As a developer, you create a pull request, and another developer reviews the code and makes comments. This step is vital in high-security environments and helps to spread knowledge, allowing each developer to grow and learn from each other. No single person owns that part; the knowledge is on the team. Implement security practices in the application development Security is a shared responsibility. There is not much a security team can do if your application puts vulnerable code out there (this is called a Zero-day vulnerability). DevSecOps can put tools and processes in place to try to detect vulnerabilities early in your code pipeline. You can use Bitbucket and AWS CodePipeline to provide a single dashboard integrated with your code repository and deployment tools. These tools give complete visibility of all the changes, pull requests, deployment warnings, and test coverage. Implementing Continuous Integration/ Continuous Delivery (CI/CD) In continuous integration or CI, developers commit new codes to a shared repository several times. Continuous Delivery or CD automates the software delivery process . You can use many tools to build this. The critical focus should be on incorporating all necessary testing, such as code review, unit testing, security scans, and so on, to ensure all rules are followed. Observability There are many complexities of cloud and microservice architecture. Therefore, implementing observability is a must-have DevOps best practice . OpenSearch, NewRelic, Splunk, Datadog, and Sentry are examples of many tools that can help you monitor and manage your systems effectively. Choose the right tools for your specific workload to ensure optimal performance and issue resolution. Releases and deployments with feature flags and canary releases Deployment is the process of sending the software to its final destination – your clients. You will disrupt everything if you do not have the proper deployment process, especially in SaaS companies. Feature flags The feature flags are very useful, especially in mobile applications that deploy the software with the new feature turned off. This method enables you to deploy the same code versions in different environments. Implement feature flags as conditional statements within the source code that require external validation to turn features on or off. Some tools also allow you to enable features for a small percentage of users , for example, 10% of the user base, scaling up if everything is stable. Canary deployments Canary releases are a DevOps practice that tests the impact of a new feature release on a small user segment before a full rollout. This approach helps you gauge the changes made to the code without affecting the entire user base. If successful, you can scale up the deployment; if not, you can roll back the changes. Canary deployments can be managed using load balancers, AWS, Kubernetes, and other tools. Conclusion Adopting DevOps best practices is essential for companies to remain competitive in today’s tech market. Companies that have not yet implemented DevOps risk falling behind, facing challenges such as longer delivery times, failures, and poor team collaboration. Evolving your DevOps maturity level enhances development speed and security from the start, and promotes continuous and reliable delivery. Practices such as agile project management, code review, CI/CD, observability, feature flags, and canary deployments are crucial for success. If you want to implement DevOps best practices or evolve your maturity level, schedule an assessment with the specialists from e-Core .

Have you heard about Docker, Kubernetes, and container orchestration? Find out how they are impacting application deployment. Surely, you’ve heard of containers before. They’re among the most talked-about technologies today. Terms like “Docker,” “Kubernetes,” and “container orchestration” frequently appear in IT discussions. But what exactly are containers? Today, we aim to explain how application deployment has been revolutionized by this incredible and (mostly) simple-to-use technology. Here is some useful information about it. What are containers? A container, simply put, is a collection of software packages needed to run a process. This might sound a bit confusing, so let’s break it down, starting with the image below.

Technical debt is a concept familiar to many in software development. It generally occurs when there is a rush to finish something, leading to a messy outcome. In software development, it is the accumulation of shortcuts and quick fixes over time, complicating future work. Understanding technical debt is crucial for tech managers because it directly influences various aspects of software development and maintenance. By recognizing technical debt, managers can allocate resources efficiently to address it, thereby reducing the risk of future disruptions. This supports strategic decisions that balance short-term gains with long-term consequences. Technical debt: Definition Technical debt is the baggage you accumulate from sub-optimal or expedient solutions in software development that can slow future progress and increase costs. Being aware of technical debt is highly recommended because it allows managers to enhance team productivity. This is achieved by minimizing rework and focusing on delivering new features effectively. Clear communication about technical debt with stakeholders ensures alignment of expectations and fosters trust in the development process. Overall, a comprehensive understanding of technical debt empowers tech managers to drive successful technology initiatives and ensure the sustainability of their organization’s software systems. Common causes Technical debt generally happens when deadlines are tight, resources are scarce, planning falls short, requirements keep changing, or bad technical decisions are made to expedite the solution. Technical debt manifests in various forms within software development. It can arise from bad implementations that prove difficult to maintain, as well as from inadequate documentation that obscures how systems operate. Unresolved bugs, particularly those not addressed at their root cause, contribute to accumulating technical debt. Persisting with outdated libraries, despite community recommendations against them, also adds to this burden. Overlooking security vulnerabilities in external libraries further compounds the issue, underscoring the importance of proactive debt management strategies. Real-life examples of technical debt risks to business Technical debt isn’t just a developer problem; it affects the whole business. It can increase maintenance costs, slow progress, hurt product quality, and even drive customers away. Real-life examples vividly illustrate the destructive consequences of neglecting technical debt. One such instance occurred with the Boeing 737 MAX aircraft, which faced severe technical debt issues in its MCAS software. The system, meant to address stability concerns, suffered from insufficient testing and documentation, leading to two fatal crashes and the global grounding of the plane. Boeing’s reputation suffered greatly, and 346 lives were tragically lost. Similarly, Adobe Flash encountered challenges as it succumbed to security vulnerabilities and performance issues. With the advent of HTML5 and modern web standards, Flash lost relevance, prompting Adobe to announce its end-of-life by the end of 2020. Financial firm Knight Capital Group experienced a catastrophic loss of approximately $440 million in less than an hour due to a software issue stemming from unresolved technical debt in a high-frequency trading algorithm. Outdated software led to thousands of unauthorized trades and significant financial losses. Equifax, one of the largest credit reporting agencies, fell victim to a massive data breach in 2017, exposing the personal information of 147 million individuals. Investigation revealed that the breach occurred due to technical debt, specifically the failure to apply security patches to a vulnerable web server. This oversight allowed hackers to exploit a known vulnerability and access Equifax’s systems, resulting in profound consequences. These examples underscore the critical importance of addressing technical debt promptly and comprehensively. So, what practical steps can we take collectively to mitigate the risks associated with technical debt? Here are some insights: Checklist: 8 techniques to prevent technical debt Preventing technical debt means being proactive and sticking to best practices. By following these 8 steps, you can lay a solid foundation to safeguard the security and stability of your company. Here’s a checklist: Code reviews: Good code reviews help identify potential issues before they become a problem, promoting code quality and consistency. Following the Maslow Piramide for code review might be a good way to do it well. Automated testing: Implementing automated testing ensures that changes and updates do not introduce regressions or defects. Keep libraries upgraded: Staying current with technology stacks, frameworks, and libraries minimizes compatibility issues and security vulnerabilities associated with outdated components. Security vulnerabilities tracking: Utilizing tools and processes to monitor and address security vulnerabilities proactively safeguards the software against potential breaches and exploits. Refactoring: Continuously refactoring code improves its maintainability, readability, and extensibility, reducing the probability of technical debt accumulation. Firefighter role for bugs: Allocating people to address critical bugs promptly prevents them from snowballing into significant technical debt. Product understanding: It is crucial to educate stakeholders, including product managers and executives, about technical debt. They must understand its implications for product development, sustainability, and long-term success. Inclusion in product roadmaps: Integrating technical debt management into product roadmaps ensures that it receives the right attention and people working alongside feature development.  How to reduce existing technical debt issues Addressing existing technical debt demands a concerted effort and careful prioritization. In essence, we have two main pieces of advice: Maintain it as a priority: Recognize technical debt as a critical concern and designate dedicated time and resources to tackle it effectively. Allocate 10% effort in each sprint: Integrate debt reduction tasks into regular development cycles by allocating a portion of each sprint’s capacity to gradually address outstanding issues. In conclusion, managing technical debt is not merely a technical concern but a business imperative. By understanding its nature, identifying its causes, and implementing preventive measures, organizations can mitigate its adverse effects on product development and ensure long-term success. Furthermore, by prioritizing the reduction of existing debt and integrating debt management into ongoing processes, businesses can foster a culture of continuous improvement and innovation. It is important to highlight that technical debt can never be eliminated and that it is a natural part of the software development cycle. The objective is to manage it effectively to minimize its negative impact on projects and the business as a whole. References Adobe Flash Termination Disrupts Archived 9/11 Coverage Equifax Data Breach Settlement Software Testing Lessons Learned from Knight Capital Fiasco Technical Debt: How to Manage It and Minimize the Risks

As professionals, we always seek to thoroughly understand our customers’ challenges and offer the best possible solution. With Atende Simples it was no different. The company offered an enterprise solution based on a monolithic application model, which did not prove to be efficient in the long run. The application was poorly scalable and flexible, which hindered its growth.