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In computer programming, a characterization test (also known as Golden Master Testing [1]) is a means to describe (characterize) the actual behavior of an existing piece of software, and therefore protect existing behavior of legacy code against unintended changes via automated testing. This term was coined by Michael Feathers.
As a result, legacy systems are typically modernized incrementally. Initially, the system consists completely of legacy code. As each increment is completed, the percentage of legacy code decreases. Eventually, the system is completely modernized. A migration strategy must ensure that the system remains fully functional during the modernization ...
Software archaeology or source code archeology is the study of poorly documented or undocumented legacy software implementations, as part of software maintenance. [1] [2] Software archaeology, named by analogy with archaeology, [3] includes the reverse engineering of software modules, and the application of a variety of tools and processes for extracting and understanding program structure and ...
Legacy code may be written in programming languages, use frameworks and external libraries, or use architecture and patterns that are no longer considered modern, increasing the mental burden and ramp-up time for software engineers who work on the codebase. Legacy code may have zero or insufficient automated tests, making refactoring dangerous ...
Legacy code may not have been designed under a defensive programming initiative, and might therefore be of much lower quality than newly designed source code. Legacy code may have been written and tested under conditions which no longer apply. The old quality assurance tests may have no validity any more. Example 1: legacy code may have been ...
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A field trip for special education students to a Cracker Barrel in Maryland this week has resulted in outcry from teachers and parents.. On Tuesday, a group of 11 students and seven staff members ...
Test-driven development (TDD) is a way of writing code that involves writing an automated unit-level test case that fails, then writing just enough code to make the test pass, then refactoring both the test code and the production code, then repeating with another new test case.