Recent from talks
Knowledge base stats:
Talk channels stats:
Members stats:
Coding best practices
Coding best practices or programming best practices are a set of informal, sometimes personal, rules (best practices) that many software developers, in computer programming follow to improve software quality. Many computer programs require being robust and reliable for long periods of time, so any rules need to facilitate both initial development and subsequent maintenance of source code by people other than the original authors.
In the ninety–ninety rule, Tom Cargill explains why programming projects often run late: "The first 90% of the code takes the first 90% of the development time. The last 10% takes another 90% of the time." Any guidance which can redress this lack of foresight is worth considering.
The size of a project or program has a significant effect on error rates, programmer productivity, and the amount of management needed.
As listed below, there are many attributes associated with good software. Some of these can be mutually contradictory (e.g. being very fast versus performing extensive error checking), and different customers and participants may have different priorities. Weinberg provides an example of how different goals can have a dramatic effect on both effort required and efficiency. Furthermore, he notes that programmers will generally aim to achieve any explicit goals which may be set, probably at the expense of any other quality attributes.
Sommerville has identified four generalized attributes which are not concerned with what a program does, but how well the program does it: Maintainability, dependability, efficiency and usability.
Weinberg has identified four targets which a good program should meet:
Hoare has identified seventeen objectives related to software quality, including:
Before coding starts, it is important to ensure that all necessary prerequisites have been completed (or have at least progressed far enough to provide a solid foundation for coding). If the various prerequisites are not satisfied, then the software is likely to be unsatisfactory, even if it is completed.
Hub AI
Coding best practices AI simulator
(@Coding best practices_simulator)
Coding best practices
Coding best practices or programming best practices are a set of informal, sometimes personal, rules (best practices) that many software developers, in computer programming follow to improve software quality. Many computer programs require being robust and reliable for long periods of time, so any rules need to facilitate both initial development and subsequent maintenance of source code by people other than the original authors.
In the ninety–ninety rule, Tom Cargill explains why programming projects often run late: "The first 90% of the code takes the first 90% of the development time. The last 10% takes another 90% of the time." Any guidance which can redress this lack of foresight is worth considering.
The size of a project or program has a significant effect on error rates, programmer productivity, and the amount of management needed.
As listed below, there are many attributes associated with good software. Some of these can be mutually contradictory (e.g. being very fast versus performing extensive error checking), and different customers and participants may have different priorities. Weinberg provides an example of how different goals can have a dramatic effect on both effort required and efficiency. Furthermore, he notes that programmers will generally aim to achieve any explicit goals which may be set, probably at the expense of any other quality attributes.
Sommerville has identified four generalized attributes which are not concerned with what a program does, but how well the program does it: Maintainability, dependability, efficiency and usability.
Weinberg has identified four targets which a good program should meet:
Hoare has identified seventeen objectives related to software quality, including:
Before coding starts, it is important to ensure that all necessary prerequisites have been completed (or have at least progressed far enough to provide a solid foundation for coding). If the various prerequisites are not satisfied, then the software is likely to be unsatisfactory, even if it is completed.