When there are issues with a team’s velocity, the first and easiest solution is to bring more developers on board. But this is just another patch on a broken bag until things go south again because the true problem was never treated. When dealing with legacy code you will often see some sort of spaghetti code.
- Understandability is one of the important characteristics of software quality, because it may influence the maintainability of the software.
- This glimpse, however, can be somewhat limited as Observability tools can only automatically instrument generic code.
- This problem can be extended to the documentation and instructions that the application provides.
- This itself can lead to complexity – especially when the new syntax is less like a human language and more like mathematical symbols or even machine language.
- They are usually provided as error traces or in a tree-like structure to guide through the systems source code or operational behavior.
Communicating this knowledge is made more difficult by the fact that, as hinted above, even programmers cannot always know in advance what is actually possible for software in advance of trying. The root causes of poor reliability are found in a combination of non-compliance with good architectural and coding practices. This non-compliance can be detected by measuring the static quality attributes of an application.
We briefly revisit existing work on notions of causality, counterexample-based causality, certification, and feature-oriented systems. David was going to deal with the metrics for FRG internal and external quality characteristics (according to ISO/IEC , ISO, 2003a, and ISO/IEC , ISO, 2003b), in particular I/O utilization, memory utilization, and response time. Sean restricted himself to quality in use metrics (according to ISO/IEC ; ISO, 2004), namely FRG task efficiency. After negotiation, David agreed not to discuss I/O utilization and memory utilization; whereas Sean agreed to discuss response time instead of task efficiency because this external quality metric was understandable to him. Last but not least, make sure to have the scaffolding in place to deal with complexity when it arises. Write automated tests in the form of both unit-tests and system-tests to ensure that your engineering team can safely refactor that complexity away.
By breaking down quality attributes or even defining additional layers, the complex, abstract quality attributes (such as reliability or maintainability) become more manageable and measurable. Those quality models have been applied in industrial contexts but have not received widespread adoption. One of the challenges in defining quality is that “everyone feels they understand it” and other definitions of software quality could be based on extending the various understandability descriptions of the concept of quality used in business. Often, the most surefire way to improve your team’s Understandability is deploying production-debuggers. This new breed of tools allows engineers to set non-breaking breakpoints in any line of code in any environment, to instantly see the full application state. Unfortunately, when working with a predefined team on an existing application, you don’t have as much flexibility to make your own choices.
In other languages
A common expression is that data is the new oil, but it’s my belief that for businesses, it’s actually oxygen. If you ask a software engineer, debugging and constantly redeploying applications is just a dirty part of the job. It often creates what I like to call “the engineering dilemma,” when an engineer has to choose between moving forward with limited information or spending tons of time writing new code to try to get the data they need. I believe these problems will only get worse if we, as technology-driven leaders, don’t address them now. Engineers can spend hours each day just trying to understand their own code and debugging issues.
And yet, by building your engineers a great sandbox, you’ll definitely enable them to study the application more efficiently. Whether you prefer articles in a shared Wiki or documents stored online, make sure to have something in place for centralizing the knowledge. As always, a picture may be worth a thousand words, so creating architecture diagrams and flow-charts is time well spent. Besides granting everyone access to it, giving the occasional session can go a long way in getting the team up to speed on the way things actually work.
That may mean that email begins to circumvent the bug tracking system, or that four or five bugs get lumped into one bug report, or that testers learn not to report minor annoyances. The difficulty is measuring what we mean to measure, without creating incentives for software programmers and testers to consciously or unconsciously “game” the measurements. The technical activities supporting software quality including build, deployment, change control and reporting are collectively known as Software configuration management.
Complaining about the technical debt you have to cope with and the “unreadable code” your engineers cannot understand is not going to get you very far. Nor will dreaming about long-term refactorings and migrations which will rarely ever come to pass. What all of those IT use cases have in common is that someone, with a basic working knowledge of the system, needs to know exactly how the system behaved in a specific instance so that they can respond to it appropriately. This means we collect data about a predefined set of events, which tends to be about how the system is interacting with the world around it. And so, highly valuable information such as usage patterns, real-world inputs and outputs, and actual performance and availability statistics can become accessible to teams determined to have them. That led to an enormous token, resulting in too many authentication attempts, and finally, that infamous error message.
The potential exists for further development of this model to facilitate optimization of process properties to match organizational needs. The need for a means to objectively determine software reliability comes from the desire to apply the techniques of contemporary engineering fields to the development of software. That desire is a result of the common observation, by both lay-persons and specialists, that computer software does not work the way it ought to.
But in my experience, the technical tools can often become part of the problem. Newer versions of computer languages add new syntax and alternate ways of doing things. This itself can lead to complexity – especially when the new syntax is less like a human language and more like mathematical symbols or even machine language.