A few days ago, while revisiting my notes, I found my scraps of “Code That Fits in Your Head” by Mark Seemann that I read earlier this year. I found the book to be insightful since it takes a step back to explore the broader principles and heuristics of software design.
As an engineer with a few years of experience, I found Seemann’s work to be a reflection of many practices and challenges I’ve encountered in my own career. It’s refreshing and affirming to see these experiences captured in print, lending them structure I hadn’t realized before. What struck me most was how Seemann names and references concepts and processes I was already familiar with but hadn’t previously identified. This not only deepened my understanding but also opened new avenues for further exploration and learning.
In this post, I’ll share a more polished version my insights from Seemann’s book, highlighting how it resonated with me.
My Key Takeaways
Chapter 1: Art of Science?
In the first chapter of “Code That Fits in Your Head,” Mark Seemann challenges conventional metaphors in software design, particularly the notion of software development as a linear, phased process similar to building a house. He critiques this analogy for falsely implying that software development can be segmented into distinct phases and that developers are merely interchangeable workers in this process.
A key insight that stood out to me in this chapter is Seemann’s observation on the inapplicability of linear metaphors in software engineering. Unlike physical construction, where building and rebuilding are costly and time-consuming, software allows for rapid modification and iteration. This fundamental difference highlights the unique flexibility of software development compared to other disciplines. It underscores the need for a more dynamic approach that accommodates constant changes and evolution, much like tending to a garden.
Seemann advocates for viewing software development as a fluid and ongoing process, necessitating continuous cultivation and adaptation by skilled practitioners. This perspective resonates with the reality of software engineering as a field defined by its adaptability and the critical role of experience and context in decision-making.
Furthermore, the introduction of heuristics as a guiding principle in software engineering shifts the focus from searching for absolute ‘right’ or ‘wrong’ ways to understanding the importance of judgment and adaptability. This approach is particularly pertinent given the unpredictable and nuanced nature of software projects.
Chapter 2: Checklists
This chapter dives into the practical utility of checklists in software engineering. Mark Seemann distinguishes two types of checklists: ‘read-do’ and ‘do-confirm.’ The ‘read-do’ checklist involves reading and performing each action step-by-step, while the ‘do-confirm’ checklist is more of a post-action verification tool, ensuring that nothing has been missed.
A particularly impactful concept for me was the ‘Walking Skeleton.’ This idea refers to developing the thinnest possible slice of real functionality that spans the entire system. It’s about creating a bare-bones version of the system that’s operational but minimal. This approach aligns with agile methodologies, emphasizing the importance of getting a rudimentary but functional version up and running early in the development process.
Seemann also touches on the importance of treating warnings as errors, a practice that reinforces the discipline of maintaining high code quality. It’s a reminder that seemingly minor issues, if overlooked, can accumulate and lead to significant problems down the line.
The ‘Boy Scout Rule’ was another key takeaway, encapsulating the ethos of leaving the codebase better than you found it. This principle is a powerful guide for continuous improvement and encourages developers to make small, incremental enhancements, which collectively can have a profound impact on the overall health of the code.
In this chapter, Seemann effectively bridges the gap between theoretical best practices and practical, actionable steps that can be integrated into the daily workflow of software development. These checklists and principles serve as a toolkit for maintaining rigor and quality in a field that is often fast-paced and dynamic.
Chapter 3: Tackling Complexity
In this chapter Mark Seemann addresses the crucial balance in software engineering between focusing on delivering value and maintaining technological robustness. He cautions against leaning too far in either direction—focusing solely on delivering immediate value can lead to neglect of internal quality, while an overemphasis on technology can overlook the practical needs of users.
One of the most compelling ideas in this chapter is the balanced approach to software development. Seemann suggests that sustainable software lies at the intersection of value and technology. This resonates with my own experience, where the most successful projects are those let you bend rules you can have a good balance between robust technology and tangible user benefits.
Seemann also explores a project management approach based on hypothesizing the impact of changes, implementing them, and then measuring their impact. This empirical approach to managing software projects is a practical method for navigating complexity, though he acknowledges its limitations in certain scenarios, like security.
The chapter also delves into the pitfalls of code that is difficult to understand, emphasizing how such code can significantly slow down development. Seemann’s assertion that “every minute invested in making code easier to understand pays itself back tenfold” is a powerful reminder of the importance of clear, maintainable code.
Additionally, the idea that code is not just an asset but also a liability was particularly enlightening. It challenges the common perception of more code as inherently better and highlights the need for thoughtful, efficient coding practices.
Chapter 4: Vertical Slice
The author introduces the concept of a ‘vertical slice,’ a methodological approach that emphasizes the development of minimal yet complete features that extend across the entire software stack.
This idea of the ‘vertical slice’ resonated with me. It advocates for focusing on the smallest segment of functionality that still provides a complete user experience, from the user interface down to the data layer. This approach not only helps in managing complexity but also ensures that each increment delivers real value.
Seemann also delves into the pitfalls of ‘Speculative Generality,’ which is the tendency to add features or code based on the anticipation of future needs rather than actual requirements. This section was a stark reminder of the importance of developing software based on current, concrete needs rather than hypothetical future scenarios, a practice that often leads to unnecessary complexity and maintenance burden.
The chapter further explores ‘Outside-in Test-Driven Development,’ a technique where development begins at the boundaries of the software system and works inward. This aligns with the vertical slice approach and encourages developers to focus on user-facing functionality first, ensuring that the most critical aspects of the application are addressed early in the development cycle.
A lower level concept discussed is the ‘Assertion Roulette,’ a term used to describe the practice of interleaving assertions with arrange and act steps in tests. This can lead to confusion and difficulty in pinpointing the source of test failures, emphasizing the need for clear and well-structured tests.
Seemann’s advocacy for abstraction, encapsulated in the phrase “elimination of the irrelevant and amplification of the essential,” is particularly striking. It serves as a guiding principle for making code more maintainable and focused on its core purpose.
Chapter 5: Encapsulation
Mark Seemann describes encapsulation as not just a best practice, but as a broader principle of creating clear contracts within code. This resonates with the idea that well-encapsulated code delineates clear boundaries and responsibilities, enhancing both maintainability and clarity.
A standout concept for me in this chapter was the ‘Transformation Priority Premise.‘ Seemann explains that code transformations should follow a logical sequence, ensuring that each modification improves the code in a meaningful way. This principle is particularly relevant in refactoring scenarios, where the goal is to enhance code without altering its external behavior.
Seemann also discusses the significance of tests acting as a form of double-entry bookkeeping. This analogy struck a chord with me, for the past few years, even when I’m not practicing TDD, I must go through at least part of the Red-Green-Refactor cycle—in a way to ensure the test I’m adding covers what I intended to.
The chapter makes a compelling argument against trading compile-time errors for run-time exceptions, a practice often seen as a shortcut but can lead to less reliable and more error-prone code. Seemann’s emphasis on the importance of catching issues early in the development cycle is a crucial takeaway.
An interesting reference is made to Bertrand Meyer and the Eiffel language, which Seemann suggests looking into for a deeper understanding of encapsulation principles.
Additionally, the chapter touches on Postel’s Law: “Be conservative in what you send. Be liberal in what you accept.” This principle, originally from the field of network communications, is applied to software design, advocating for robustness and flexibility in handling inputs and outputs.
Chapter 6: Triangulation
Here, the author highlights the importance of creating manageable ‘chunks’ of code that align with human cognitive capabilities. This concept is particularly significant given that software complexity often exceeds the limits of individual understanding.
A key insight from this chapter is the idea of ‘Triangulation’ in test-driven development. Seemann uses this term to describe the process of incrementally building tests to validate software requirements accurately. This resonates with the practice of refining and adjusting your approach based on feedback.
Seemann also discusses the ‘Devil’s Advocate’ technique for determining the sufficiency of test cases. This involves intentionally writing an incomplete implementation to ensure that tests are robust enough to catch deficiencies. I found this to be a clever strategy for enhancing test reliability and coverage.
The low-level concept of ‘Number-Line Order’ was another intriguing takeaway. It’s a coding style where comparisons involving a variable and two numbers should be written in a logical sequence (e.g., low < value < high). I can’t count how many times I had to re-order, or try another workaround while trying to understand code that was organized in a logical sequence.
Chapter 7: Decomposition
The problem that Seemann addresses in this chapter is the gradual deterioration of code quality, a phenomenon often faced in software development. He provides insights into how to combat this ‘code rot’ through effective decomposition strategies.
One of the most striking ideas in this chapter is the notion that no one intentionally sets out to write legacy code; it’s a process that happens slowly over time. This resonates with my own observations, where seemingly minor compromises in code quality can accumulate, leading to a codebase that becomes increasingly difficult to maintain.
Seemann introduces the concept of the ‘Hex flower’ as a pattern for managing code complexity. This pattern emphasizes that only a limited number of things should be happening in a single piece of code at any one time.
The discussion on cohesion within classes was particularly enlightening. Seemann elaborates on the degrees of cohesion, from maximum, where all methods use all fields, to minimum, where each method operates on a disjoint set of fields. This helped me better understand the importance of structuring classes in a way that promotes clarity and reduces interdependencies.
Another important takeaway was the concept of ‘Feature Envy,’ a code smell where a function is overly reliant on the internals of another class or module. This chapter reinforced the importance of keeping functions and classes focused and avoiding unnecessary dependencies.
Seemann also touches on the challenges of ‘Lost in Translation’ issues when converting between different object types. He contrasts Domain Models with Data Transfer Objects (DTOs), highlighting how they serve different purposes and interact with the chaotic outside world differently.
Chapter 8: API Design
In this chapter, the author provides valuable insights into creating APIs that are not only functional but also intuitive and difficult to misuse.
A particularly resonant idea in this chapter is the concept of designing APIs with built-in quality, essentially making them ‘poka-yoke’ or foolproof. Seemann suggests that APIs should be designed in such a way that it becomes difficult for other developers to use them incorrectly. This proactive approach to API design greatly reduces the potential for errors in software development.
Seemann’s discussion on making illegal states unrepresentable was another eye-opening takeaway. It emphasizes the importance of designing systems where incorrect use cases are naturally prevented, enhancing the robustness of the software. This approach is especially effective in strongly typed languages, where the type system can be leveraged to enforce correct usage. This discussion reminded me a lot of how Haskell forces you to design your code.
The chapter also delves into the principle of Command Query Separation, advocating for a clear distinction between methods that change state (commands) and those that retrieve data (queries). This separation not only makes APIs clearer and more predictable but also simplifies debugging and maintenance.
Seemann’s advice on method naming and documentation was particularly valuable. He advises against over-relying on comments and encourages the use of expressive method names and types to convey intent. This aligns with the principle of self-documenting code, which enhances readability and maintainability.
Chapter 9: Teamwork
A central theme of this chapter is the significance of understanding and respecting the rationale behind code. Seemann notes that one of the major challenges in software development is grasping the reasoning behind certain coding decisions. This resonates with my experience, where clear communication and documentation of intent can greatly ease the process of working in a team environment.
Seemann advocates for the practice of continuous integration, stressing the importance of frequently merging code changes to avoid the pitfalls of long-lived branches. This aligns with the agile methodology and highlights the efficiency gains from regular, small integrations over sporadic, large updates.
The discussion on the ‘Bus Factor’ (or ‘Lottery Factor’) provided an interesting perspective on knowledge distribution within a team. Ensuring that multiple team members are familiar with different parts of the codebase not only mitigates risks but also promotes a more collaborative and versatile team environment.
Pair programming and mob programming are presented as effective strategies for knowledge transfer and avoiding knowledge silos within a team. Seemann suggests regularly rotating pairs and mob groups to maximize learning and exposure to different parts of the code.
The chapter also touches on the effectiveness of code reviews, a practice that has documented positive impacts on software quality. Seemann provides practical tips for conducting code reviews, such as keeping change sets small and focusing on one issue per pull request, to enhance their effectiveness.
Seemann concludes the chapter by addressing the challenges of meeting deadlines and the counterproductive nature of ‘crunch mode.’ He emphasizes the importance of manageable, iterative changes and the avoidance of large, unwieldy modifications.
Chapter 10: Augmenting Code
In this chapter, Mark Seemann categorizes these changes into three buckets: introducing new functionality, enhancing existing features, and bug fixing. This chapter provides a clear framework for understanding the various types of code changes and their implications.
The author highlights the challenges of integrating large changes and the benefits of smaller, more frequent updates. An approach that uses Continuous Integration not only streamlines the development process but also reduces the risks associated with integrating large chunks of code.
Seemann discusses the ‘Strangler Pattern’ in the context of software evolution. This pattern involves gradually replacing parts of an existing system with new implementations, allowing for a smoother transition and minimizing disruption. This concept resonated with me, as it provides a practical approach to evolving and modernizing legacy systems without the need for a complete overhaul.
Another important aspect discussed is the ‘maintenance tax’ associated with adding more code. Seemann reminds us that every new line of code adds to the overall maintenance burden of the system. This perspective encourages a more thoughtful approach to coding, where the long-term implications of additional code are carefully considered.
The chapter also emphasizes the importance of not just adding features but also refining and deepening the understanding of the existing codebase. Seemann suggests that refactoring for deeper insight is a crucial part of software development, enabling developers to improve the system’s design and functionality over time.
Chapter 11: Editing Unit Tests
A key takeaway for me was the emphasis on the strength of post-conditions in tests. Seemann argues that adding new assertions can actually strengthen these post-conditions, thereby enhancing the test’s effectiveness. This perspective shifts the focus from a rigid rule of one assertion per test to a more flexible approach that prioritizes the comprehensiveness and reliability of the tests.
The chapter also revisits the Liskov Substitution Principle in the context of testing. According to this principle, subtypes should weaken pre-conditions and strengthen post-conditions. Seemann’s discussion on this topic deepened my understanding of how inheritance and polymorphism can be effectively utilized in test design.
Another important aspect of this chapter is the idea that deleting tests or assertions can weaken the guarantees of the system. This underscores the significance of carefully considering the impact of any changes made to the test suite, as tests play a vital role in ensuring the stability and reliability of the software.
Seemann advises that whenever tests need to be refactored, it’s best to do so without touching the production code. This separation ensures that changes in tests don’t inadvertently introduce new bugs or alter the behavior of the existing code.
The chapter also touches on the importance of making sure tests fail in expected ways when changes are made. I also find this crucial for verifying that the tests are indeed testing what they are supposed to and that they remain sensitive to potential issues in the code.
Chapter 12: Troubleshooting
In this chapter, Seemann delves into the systematic approach to solving problems in software development. This chapter stands out for its emphasis on applying a scientific method to troubleshooting.
One of the most impactful ideas for me was the concept of formulating a hypothesis before attempting to solve a problem. Seemann encourages developers to make predictions about what might be causing an issue, and then to test these hypotheses through experiments. This methodical approach not only streamlines the troubleshooting process but also fosters a more thorough understanding of the system. As many other insights from the book, this is very close to how I work, but it’s interesting to see the process described in a throughout way.
Seemann advises keeping solutions simple, echoing the well-known principle of Occam’s Razor. This reinforces the idea that the simplest solution is often the most effective, especially in complex systems where adding more complexity can exacerbate issues.
The chapter also highlights the importance of time-boxing in the problem-solving process. Setting a limit on how long to spend on a particular issue can prevent developers from getting too entrenched in a single problem, which can be counterproductive.
An interesting point Seemann makes is about the potential pitfalls of rolling back transactions during tests. While this practice can be convenient, it can also mask issues related to transaction management, emphasizing the need for comprehensive testing that includes transactional behavior. He suggests recreating the database for each test case. Honestly, I tried it but failed to make the test suite run in a reasonable amout of time.
Seemann discusses the concept of ‘Bisection’ as a troubleshooting technique, where the codebase is systematically reduced to isolate the source of a problem. This approach, while sometimes challenging to apply in practice, can be effective in pinpointing issues in complex systems.
The idea of creating a ‘minimal working example’ to isolate and clarify problems is highlighted as a particularly effective troubleshooting technique. This approach involves stripping down the system to the bare essentials where the problem manifests, making it easier to identify the cause.
Chapter 13: Separation of Concerns
This chapter emphasizes the importance of organizing code in a way that separates different aspects or concerns, enhancing maintainability and scalability.
A key insight that resonated with me is the notion that elements of a software system that change at the same rate should be grouped together, while those that change at different rates should be kept apart. This approach facilitates easier updates and maintenance, as changes are more likely to affect only specific, isolated parts of the system.
Seemann discusses different meanings of the term ‘component’ in software engineering, ranging from classes and modules to libraries. This variability underscores the importance of context when considering the separation of concerns, as the optimal level of separation can differ based on the scale and complexity of the system.
The chapter introduces the ‘Composite’ pattern as a way to manage side effects in software systems. This design pattern helps in organizing code that has side effects, making it more manageable and testable.
Seemann also revisits the concept of pure functions in this context. He advocates for keeping non-deterministic operations and side effects at the edge of the system, while central logic should be composed of pure, deterministic functions. This ‘functional core, imperative shell’ approach is particularly appealing as it combines the clarity and testability of functional programming with the practicality of imperative programming.
The discussion on logging and the need for repeatability in log data is another valuable point. Seemann suggests that sufficient information should be logged to allow for the replication of issues, which is crucial for effective troubleshooting.
Chapter 14: Rhythm
This chapter explores the importance of finding a balance between focused work and necessary breaks, a concept that resonates deeply with the reality of the software development process.
A significant insight from this chapter is the idea that being ‘in the zone’ might feel productive, but it’s the alternation between focus and breaks that truly enhances productivity. Seemann suggests that sustained concentration, followed by periods of rest, can lead to more effective work habits, aligning with contemporary research on productivity and cognitive function.
The chapter also addresses the scalability of meetings versus documentation in software projects. Seemann argues that while meetings can be useful for immediate communication, they don’t scale well with project size and complexity. On the other hand, well-maintained documentation can be a more effective tool for communication in larger projects, offering a scalable and persistent reference.
Another interesting aspect of this chapter is the discussion of Conway’s Law, which states that an organization’s structure will inevitably influence the design of its systems. This law highlights the importance of considering organizational dynamics when designing software systems, as the communication patterns within a team or company can significantly impact the software’s architecture.
Seemann also touches on different methodologies such as Scrum, XP, PRINCE2, and the challenges of navigating daily chaos in software development environments. This variety illustrates the need for teams to find a rhythm that works best for their specific context and project requirements.
Chapter 15: The Usual Suspects
One of the key points that stood out to me in this chapter is the caution against over-prioritizing performance. Seemann suggests that while performance is important, it should not overshadow other critical factors like maintainability, functionality, and security.
Seemann also touches on the analogy of software security to insurance. This comparison highlights the often-grudging attitude towards investing in security measures, while also underscoring its essential nature. Just like insurance, neglecting security can lead to severe consequences, making it a crucial consideration for any software project.
The chapter discusses the STRIDE model for security auditing, which provides a structured approach to identifying and mitigating security risks. This model is particularly relevant in the context of programming languages like C and C++ that are vulnerable to specific types of security issues such as buffer overflows.
Chapter 16: Tour
A notable point in this final chapter is Seemann’s discussion on file organization. He challenges the traditional hierarchy-based organization of files, suggesting instead that modern IDEs make it feasible to keep files in a flat structure. This perspective encourages a shift in focus from file structure to other features like searchability and navigation within the IDE, which can enhance developer efficiency.
The emphasis on favoring composition over inheritance is another key insight. Seemann points out that while inheritance might seem like an intuitive way to organize code, it can often lead to rigid and less maintainable structures. Composition, on the other hand, offers greater flexibility and encourages more modular and reusable code.
Seemann also explores different architectural models like layered architecture, monolithic applications, ports and adapters, and microservices. Each of these models has its strengths and trade-offs, and Seemann’s tour through these concepts provides a broad overview of the options available to software engineers.
The chapter further delves into the ‘functional core, imperative shell’ model, which is a recurring theme in the book. This model advocates for separating the functional, stateless part of the system from the imperative, stateful part, thereby combining the benefits of both functional and imperative programming paradigms.
Finally, Seemann touches upon the concept of ‘listening to your tests,’ a practice where the feedback from test suites guides the development and design of the software. This approach underscores the importance of tests not just as a verification tool but also as a driver for design decisions.
Reflections
“Code That Fits in Your Head” by Mark Seemann has been an enlightening journey through the complex world of software engineering. Reading this book, I found myself nodding in agreement repeatedly, recognizing challenges and practices I’ve encountered in my own career. Seemann’s ability to name and define concepts that I’ve experienced but never formally identified was particularly gratifying.
Seemann’s critique of traditional metaphors in software design, especially the comparison of software development to building construction. His argument that software engineering should be more fluid, resembling gardening more than construction, resonated with me. It reflects the adaptability and ongoing maintenance required in software development, aspects that I’ve come to appreciate more deeply through practical experience.
However, keep in mind this book favors breadth intead of depath. My impression is that this was done by design, and Seemann’s solves this by offering numerous references, offering readers the opportunity to delve deeper into specific subjects on their own.
In chapters discussing topics like API design and the ‘functional core, imperative shell’ model, Seemann offers a wealth of knowledge that is both practical and insightful.
Overall, “Code That Fits in Your Head” strikes a fine balance between offering guidance and acknowledging the artful nature of software development. It’s a book that resonates with experienced developers through its recognition of the less tangible aspects of our craft—the intuition, judgment, and accumulated wisdom that shape our approach to code.