2. Methodology

The methodology employed in this study is designed to provide a systematic and structured approach to analyzing and improving the code-level architecture of the selected medium-sized software system. This section outlines the steps taken to conduct the analysis and identifies the key sources of information.

To initiate the analysis, we began by selecting a substantial software element within the system, such as a module or a large class, consisting of at least four different functions or sub-elements. This selection process aligns with the principles of code-level architecture analysis, allowing us to delve deeply into a specific, representative portion of the software (Pressman, 2021).

Following the selection of the software element, our analysis drew upon a combination of established code quality metrics and industry best practices. We referenced the works of Martin (2018) and Fowler (2018) to identify code smells, which served as a foundational component of our analysis. These code smells are indicative of structural problems within the codebase, signaling the need for refactoring and improvement.

To assess the software’s documentation and readability, we employed guidelines outlined by Sommerville (2019). Clear and comprehensive documentation is critical for maintaining and understanding software systems over time. We identified areas within the selected software element where documentation was lacking or where code readability was compromised, as poor documentation and readability are known to be architectural deficiencies (Sommerville, 2019).

For the evaluation of standards violations, we referred to both industry-specific standards and language-specific standards. This step involved cross-referencing the codebase with regulatory standards, language specifications, and style guides as discussed in Basili, Briand, and Melo’s work (2018). Instances where the code did not adhere to these standards were noted as architectural deficiencies, as adherence to standards is crucial for ensuring interoperability and compliance (Basili et al., 2018).

Finally, to assess design quality deficiencies, we considered performance, robustness, security, and testability aspects. These design qualities are vital for the long-term viability and adaptability of the software system (Pressman, 2021). Our analysis identified areas within the codebase that may hinder the achievement of these design qualities, thereby serving as architectural deficiencies.

Incorporating these steps in our methodology ensured a comprehensive and structured approach to identifying architectural deficiencies within the selected software element. By drawing from established principles and best practices, we aimed to provide valuable insights into areas of improvement, ultimately contributing to the enhancement of the code-level architecture of the software system.

3. Code Smells Analysis

The analysis of code smells is a fundamental step in identifying structural problems within the codebase, serving as a cornerstone for architectural improvement. Drawing from the works of Fowler (2018) and Martin (2018), we embarked on a comprehensive examination of the selected software element to detect these telltale signs of architectural deficiencies.

One of the most prevalent code smells we encountered was the “Long Method” smell. According to Fowler (2018), this smell manifests when a function or method becomes excessively long, making it challenging to understand and maintain. In our analysis, we identified instances where functions within the selected software element exceeded a reasonable length threshold. This not only hindered readability but also impeded the ease of modification, a crucial aspect of code maintainability (Fowler, 2018).

Another notable code smell we uncovered was the “Duplicated Code” smell. Duplicated code fragments were scattered throughout the software element, violating the DRY (Don’t Repeat Yourself) principle as advocated by Martin (2018). Such redundancy not only increases the risk of inconsistency but also complicates maintenance efforts. Eliminating duplicated code is essential for ensuring codebase integrity and reducing the likelihood of defects (Martin, 2018).

Furthermore, we encountered instances of the “Complex Conditional” smell, where conditional statements within functions became convoluted and difficult to comprehend. As highlighted by Pressman (2021), complex conditional logic can lead to bugs and hinder the testing process. Identifying and simplifying these conditions is imperative for ensuring code reliability and testability (Pressman, 2021).

Additionally, the “Large Class” smell was observed in several instances. According to Fowler (2018), this smell emerges when a class becomes overly complex and encompasses too many responsibilities. Large classes tend to violate the Single Responsibility Principle (SRP), a key tenet of clean architecture (Martin, 2018). Our analysis pinpointed classes within the software element that exhibited this smell, signaling the need for class decomposition and a more balanced distribution of responsibilities.

Lastly, the “Feature Envy” smell was identified in certain functions. This smell, as defined by Martin (2018), occurs when a method exhibits a strong affinity for the data or methods of another class, potentially indicating a design issue. We found instances where functions displayed an excessive interest in the internals of other classes, suggesting a need for a reevaluation of the software’s object-oriented design (Martin, 2018).

Our code smells analysis unveiled a spectrum of architectural deficiencies within the selected software element. These findings serve as a solid foundation for subsequent steps in our quest to enhance the code-level architecture. By addressing these code smells through refactoring and code restructuring, we aim to improve the software’s maintainability and overall quality.

4. Documentation and Readability Concerns

Effective documentation and readability are integral components of code-level architecture, ensuring that software systems remain comprehensible and maintainable over time. Drawing from the insights of Sommerville (2019) and Martin (2018), we scrutinized the selected software element to identify areas of concern related to documentation and code readability.

In our analysis, we found instances where the codebase lacked clear and comprehensive documentation. According to Sommerville (2019), well-documented code provides essential context for developers, facilitating a deeper understanding of the software’s functionality and design decisions. The absence of adequate documentation can hinder collaboration among development teams and make it challenging to maintain the codebase over time (Sommerville, 2019).

Furthermore, we identified sections of code within the software element that exhibited suboptimal readability. Readability, as emphasized by Martin (2018), is a critical aspect of code quality, as code is often read more frequently than it is written. Complex, convoluted code structures can lead to confusion among developers and increase the likelihood of introducing defects during maintenance (Martin, 2018).

The lack of meaningful variable and function names was a recurring issue. Clear and descriptive naming conventions are essential for making the code self-explanatory and reducing the cognitive load on developers (Fowler, 2018). Our analysis revealed instances where variable names were cryptic or lacked context, impeding the understanding of the code’s purpose and functionality.

Additionally, we encountered lengthy and convoluted code blocks that hindered code comprehension. Such blocks often contained multiple nested loops or conditionals, making it challenging to discern the code’s logic and control flow. Simplifying these complex code structures is essential for improving code readability and maintainability (Pressman, 2021).

Another concern was inconsistent formatting and indentation practices within the codebase. Inconsistent code formatting violates the principle of uniformity, making the codebase appear disjointed and unprofessional (Pressman, 2021). It also introduces the risk of introducing errors during code modifications due to inconsistent coding practices.

Our analysis of documentation and readability concerns underscores the significance of these factors in code-level architecture. Addressing these concerns through the establishment of clear documentation practices, adherence to naming conventions, simplification of complex code structures, and consistent code formatting will contribute significantly to enhancing the software’s maintainability and comprehensibility.

5. Standards Violations

Compliance with established standards is a crucial aspect of code-level architecture, ensuring that software systems adhere to industry best practices, language specifications, and regulatory requirements. Our analysis, informed by the works of Basili, Briand, and Melo (2018) and Martin (2018), revealed instances of standards violations within the selected software element.

First and foremost, we assessed the software’s compliance with industry-specific standards and regulations. Regulatory standards, such as FERPA for systems handling student data, or accessibility requirements for user-facing applications, play a pivotal role in software development (Basili et al., 2018). In our analysis, we identified areas where the code fell short of these standards, potentially exposing the system to compliance-related risks (Basili et al., 2018).

Additionally, we scrutinized the software’s adherence to language and syntax standards. Each programming language has its specifications and best practices, and deviating from these can result in code that is difficult to maintain and prone to errors (Martin, 2018). Our analysis revealed instances where the codebase did not fully align with language-specific standards, raising concerns about interoperability and code quality (Martin, 2018).

Furthermore, we considered adherence to specific style guides, such as the Effective Go guide for GoLang (Martin, 2018). Style guides ensure code consistency and readability, making it easier for development teams to collaborate effectively (Martin, 2018). In our analysis, we identified areas where the code did not conform to the prescribed style guide, potentially leading to inconsistencies in coding practices and hindering maintainability (Martin, 2018).

It is important to note that not all software projects are subject to the same set of standards, and in some cases, there may be no specific standards that apply. In such instances, we explicitly documented the absence of applicable standards to provide a clear context for our analysis.

Our analysis of standards violations underscored the importance of aligning software development efforts with established standards, regulations, and best practices. Addressing standards violations within the codebase is crucial for ensuring compliance, reducing risks, and promoting code quality.

6. Design Quality Deficiencies

Design quality is a critical aspect of code-level architecture, encompassing attributes such as performance, robustness, security, and testability. Our analysis, informed by Pressman (2021), revealed potential design quality deficiencies within the selected software element that could hinder the system’s long-term viability and adaptability.

One of the primary design quality concerns we identified was related to performance. High-performance software is essential for ensuring that a system can execute its functions efficiently, even as it scales and handles larger workloads (Pressman, 2021). In our analysis, we found areas where code inefficiencies and bottlenecks could potentially degrade performance, signaling the need for optimization (Pressman, 2021).

Robustness, or the software’s ability to handle unexpected conditions and errors gracefully, was another design quality consideration. We noted instances where the code lacked proper error handling mechanisms, potentially leading to system crashes or data corruption (Pressman, 2021). Ensuring robustness is crucial for delivering a reliable and fault-tolerant software system (Pressman, 2021).

Security emerged as a paramount design quality concern. In an era marked by increasing cyber threats and data breaches, software security is non-negotiable (Pressman, 2021). Our analysis uncovered potential vulnerabilities in the codebase, such as inadequate input validation and insufficient protection against common attack vectors (Pressman, 2021). Addressing these security deficiencies is vital for safeguarding sensitive data and maintaining user trust (Pressman, 2021).

Testability, or the ease with which software can be tested for correctness and reliability, was another design quality consideration. Inadequately designed code can be challenging to test, leading to incomplete test coverage and a higher likelihood of undetected defects (Pressman, 2021). Our analysis identified areas where code complexity and interdependencies hindered effective testing, emphasizing the need for design improvements to enhance testability (Pressman, 2021).

It is worth noting that the specific design quality deficiencies observed may vary depending on the software system’s requirements and objectives. In cases where certain design qualities are not explicitly required, we documented the absence of additional design quality considerations to provide context for our analysis.

Our analysis of design quality deficiencies underscored the significance of factors such as performance, robustness, security, and testability in code-level architecture. Addressing these design quality concerns is pivotal for ensuring the software’s long-term reliability, resilience, and adaptability.

7. Architectural Deficiencies

The culmination of our analysis reveals a spectrum of architectural deficiencies within the selected software element. These deficiencies, as identified in the previous sections, serve as foundational aspects of code-level architecture that require focused attention and remediation. This section consolidates these findings into a succinct list of architectural deficiencies.

One prevalent architectural deficiency is the existence of “Long Methods.” These excessively lengthy functions hinder code comprehension and maintainability, making it arduous to modify and maintain the software (Fowler, 2018). Addressing long methods through refactoring is essential for codebase readability and ease of maintenance (Fowler, 2018).

Another deficiency is the presence of “Duplicated Code.” Duplicated code fragments scattered throughout the codebase introduce redundancy and increase the risk of inconsistency (Martin, 2018). Eliminating duplicated code is imperative for codebase integrity and defect reduction (Martin, 2018).

The “Complex Conditional” architectural deficiency arises from intricate and convoluted conditional logic within functions (Pressman, 2021). Such complexity poses the risk of introducing errors and complicates the testing process (Pressman, 2021). Simplifying complex conditionals is crucial for codebase reliability and testability (Pressman, 2021).

Furthermore, the architectural deficiency of “Large Classes” signifies classes that have become overly complex and encompass too many responsibilities (Martin, 2018). These large classes violate the Single Responsibility Principle (SRP), impeding codebase modularity (Martin, 2018). Decomposing large classes is essential for a more balanced distribution of responsibilities and maintainable code (Martin, 2018).

Lastly, the “Feature Envy” architectural deficiency indicates functions with a strong affinity for the data or methods of another class (Martin, 2018). This suggests potential design issues and a need for reevaluation of the software’s object-oriented design (Martin, 2018).

In addition to these code smells, architectural deficiencies extend to documentation and readability concerns. Insufficient documentation and poor readability hinder code comprehension and collaboration (Sommerville, 2019). Non-compliance with industry, language, and style guide standards introduces non-conformity issues and potential risks (Basili et al., 2018; Martin, 2018). Design quality deficiencies encompass performance bottlenecks, robustness concerns, security vulnerabilities, and testability limitations (Pressman, 2021).

Addressing these architectural deficiencies is essential for enhancing the code-level architecture of the software system. Through a systematic approach to refactoring, code restructuring, improved documentation practices, and adherence to standards, developers can pave the way for a more maintainable, efficient, and resilient software architecture.