Data-driven programming

EN Texte en anglais Pas encore d'article dans ta langue : extrait en anglais.

In computer programming, data-driven programming is a programming paradigm in which the program statements describe the data to be matched and the processing required rather than defining a sequence of steps to be taken. Standard examples of data-driven languages are the text-processing languages sed and AWK, and the document transformation language XSLT, where the data is a sequence of lines in an input stream – these are thus also known as line-oriented languages – and pattern matching is primarily done via regular expressions or line numbers. Data-driven programming is similar to event-driven programming, in that both are structured as pattern matching and resulting processing, and are usually implemented by a main loop, though they are typically applied to different domains. The condition/action model is also similar to aspect-oriented programming, where when a join point (condition) is reached, a pointcut (action) is executed. A similar paradigm is used in some tracing frameworks such as DTrace, where one lists probes (instrumentation points) and associated actions, which execute when the condition is satisfied. Adapting abstract data type design methods to object-oriented programming results in a data-driven design. This type of design is sometimes used in object-oriented programming to define classes during the conception of a piece of software. Data-driven programming is typically applied to streams of structured data, for filtering, transforming, aggregating (such as computing statistics), or calling other programs. Typical streams include log files, delimiter-separated values, or email messages, notably for email filtering. For example, an AWK program may take as input a stream of log statements, and for example send all to the console, write ones starting with WARNING to a "WARNING" file, and send an email to a sysadmin in case any line starts with "ERROR".