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Open Source Definition: A software for which the original source code is made freely available and may be redistributed and modified according to the requirement of the user. Anyone can manipulate and change a piece of software so that the program or application can work. Programmers who have access to a computer program source code can improve a program by adding features to it or fixing parts that don't always work correctly.
Description: There are two kinds of software. One is open source software and the other is proprietary software or closed source software. As the source code of an open source program can be modified by anyone without any licence to do the same, this is also free to download. Many people prefer open source software because they are interested in more control over these kinds of software.
They can examine the code to make sure it's not doing anything they don't want it to do, and they can only change parts of it they don't like to do. Generic users who aren't programmers also took benefit from open source software, because they can use this kind of software for any purpose without any prior notice to the proprietor as they wish—not merely the way someone else thinks they should.
This is a common misconception about what open source implies. Many open source software programmers find that charging users money for software services and support rather than for the software itself is more profitable. This way, their software remains free of charge and they make money by helping others to install, use and troubleshoot it.
When various subsystems or modules are tightly coupled, debugging becomes harder as any change in one module may cause more bugs to appear in another. Sometimes it takes more time to debug a program than to code it. Description: To debug a program, user has to start with a problem, isolate the source code of the problem, and then fix it. A user of a program must know how to fix the problem as knowledge about problem analysis is expected.
When the bug is fixed, then the software is ready to use. Debugging tools called debuggers are used to identify coding errors at various development stages.
They are used to reproduce the conditions in which error has occurred, then examine the program state at that time and locate the cause.
Functional Testing. Non-Functional Testing. Software Debugging. Object Oriented Testing. Software Testing Tools. Tutorials Library. Debugging : Introduction Debugging is the process of identifying and correcting errors occurred in a software product. Whenever a software fails, we would like to understand the reason behind it for such failures.
After the reason is known, we can attempt to make necessary changes in the source code and try to find the solutions. Those changes can remove the reason for that software failure. Whenever a program generates an unexpected behavior , it is known as failure of program. Some programmers are geniuses and understand everything in little time. If you are like me, you do not understand a lot by just glancing at the code. You might need to run the program a couple of times and experiment with it to discover some properties of its functionality.
Debuggers are an obvious tool for understanding your program. But you can also rely on ad-hoc tools for aiding your understanding. Reading logs or using the poorer variant of printing debugging strings to the console are great tools that complement debuggers. While debuggers give you insight into deep and specific parts of your codebase, logs and console prints can help you build a bird's-eye perspective of your program. This might be useful for validating assumptions that span multiple modules.
Be creative and think outside the box to build more exotic tools than the common ones. RxVision is one example for reactive programming. Build them yourself or search the web for others. Don't shy away from spending time building tools for improving your understanding of the code, and remember that bugs cost billions to the software industry.
Because programming is understanding, preventing bugs is often related to proper architecture which makes it easier to reason about the program's functionality. There is a lot of ongoing discussion on which programming model and architectures are the best, but some practices are widely recommended. One of these ubiquitous practices is to keep different levels of abstraction separated. Here is one simple example in Kotlin:. This getEuroString function checks if the given number is not an integer, returning a price label in euros with two decimal digits, otherwise returning a price label with a whole value.
This function works, but has a problem: the condition in the if is working on a lower abstraction level than the rest of the control flow. This function should only express the logic we mentioned above, yet it goes into details which are irrelevant to its purpose.
The function might be a source of bugs and an obstacle during debugging in the future. The reason for that is: while debugging, it is likely you will look getEuroString through the perspective of one level of abstraction "it checks if the value is a decimal, to use the decimal format, otherwise uses the integer format" and dismiss the lower levels of abstraction, assuming they are correctly doing what you want them to do. And that is where the problem is: letting an assumption slip away unchecked.
Instead, we should refactor the function so that it uses other functions which hide those lower level instructions. In this fashion, you facilitate the assumption validation process when debugging: when inspecting getIntegerEuroString or any other function, it will be straightforward to check whether it only does what it says it does. Each function makes it obvious on which level of abstraction it operates, so you don't need to mentally switch between different levels of abstraction when inspecting the function.
It focuses your mind, pointing you in the right direction for hunting bugs. Overall, programming practices that prevent bugs are empathic to other programmers and to your future self. Code which looks obvious and looks easy to read and change is code which eventually yields less bugs.
Therefore, if you write the code as cleverly as possible, you are, by definition, not smart enough to debug it. To prevent bugs, write code that looks easy in any programmer's eyes. To fix bugs, understand your code. To understand your code with precision, enumerate and validate your assumptions, building debugging tools if necessary.
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