Modern programming

Quality requirements
Whatever the approach to the software development may be, the program must finally satisfy some fundamental properties; bearing them in mind while programming reduces the costs in terms of time and/or money due to debugging, further development and user support. Although quality programming can be achieved in a number of ways, following five properties are among the most relevant:
Efficiency: it is referred to the system resource consumption (computer processor, memory, slow devices, networks and to some extent even user interaction) which must be the lowest possible.
Reliability: the results of the program must be correct, which not only implies a correct code implementation but also reduction of error propagation (e.g. resulting from data conversion) and prevention of typical errors (overflow, underflow or zero division).
Robustness: a program must anticipate situations of data type conflict and all other incompatibilities which result in run time errors and stop the program. The focus of this aspect is the interaction with the user and the handling of error messages.
Portability: it should work as it is in any software and hardware environment, or at least without relevant reprogramming.
Readability: the purpose of the main program and of each subroutine must be clearly defined with appropriate comments and self explanatory choice of symbolic names (constants, variables, function names, classes, methods, ...).

Algorithmic Complexity
The academic field and engineering practice of computer programming are largely concerned with discovering and implementing the most efficient algorithms for a given class of problem. For this purpose, algorithms are classified into orders using so-called Big O notation, O(n), which expresses resource use, such as execution time or memory consumption, in terms of the size of an input. Expert programmers are familiar with a variety of well-established algorithms and their respective complexities and use this knowledge to choose algorithms that are best suited to the circumstances.

Methodologies
The first step in most formal software development projects is requirements analysis, followed by modeling, implementation, and failure elimination (debugging). There exist a lot of differing approaches for each of those tasks. One approach popular for requirements analysis is Use Case analysis.
Popular modeling techniques include Object-Oriented Analysis and Design (OOAD) and Model-Driven Architecture (MDA). The Unified Modeling Language (UML) is a notation used for both OOAD and MDA.
A similar technique used for database design is Entity-Relationship Modeling (ER Modeling).
Implementation techniques include imperative languages (object-oriented or procedural), functional languages, and logic languages.
Debugging is most often done with IDEs like Visual Studio, NetBeans, and Eclipse. Separate debuggers like gdb are also used.

Measuring language usage
It is very difficult to determine what are the most popular of modern programming languages. Some languages are very popular for particular kinds of applications (e.g., COBOL is still strong in the corporate data center, often on large mainframes, FORTRAN in engineering applications, and C in embedded applications), while some languages are regularly used to write many different kinds of applications.
Methods of measuring language popularity include: counting the number of job advertisements that mention the language[3], the number of books teaching the language that are sold (this overestimates the importance of newer languages), and estimates of the number of existing lines of code written in the language (this underestimates the number of users of business languages such as COBOL).

Debugging
Debugging is a very important task for every programmer, because an erroneous program is often useless. Languages like C++ and Assembler are very challenging even to expert programmers because of failure modes like buffer overruns, bad pointers or uninitialized memory. A buffer overrun can damage adjacent memory regions and cause a failure in a totally different program line. Because of those memory issues tools like Valgrind, Purify or Boundschecker are virtually a necessity for modern software development in the C++ language. Languages such as Java, C#, PHP and Python protect the programmer from most of these runtime failure modes, but this may come at the price of a dramatically lower execution speed of the resulting program. This is acceptable for applications where execution speed is determined by other considerations such as database access or file I/O. The exact cost will depend upon specific implementation details. Modern Java virtual machines and .NET Common Language Runtime, for example, use a variety of sophisticated optimizations, including runtime conversion of interpreted instructions to native machine code