style (colors, patterns, etc.). Because all of the elements of the vector image are defined by mathematical formulae and not by a grid of dots as in a raster image, sharpness is maintained regardless of

style (colors, patterns, etc.). Because all of the elements of the vector image are defined by mathematical formulae and not by a grid of dots as in a raster image, sharpness is maintained regardless of

style (colors, patterns, etc.). Because all of the elements of the vector image are defined by mathematical formulae and not by a grid of dots as in a raster image, sharpness is maintained regardless of

style (colors, patterns, etc.). Because all of the elements of the vector image are defined by mathematical for- mulae and not by a grid of dots as in a raster image, sharpness is maintained regardless

style (colors, patterns, etc.). Because all of the elements of the vector image are defined by mathematical for- mulae and not by a grid of dots as in a raster image, sharpness is maintained regardless

style (colors, patterns, etc.). Because all of the elements of the vector image are defined by mathematical for- mulae and not by a grid of dots as in a raster image, sharpness is maintained regardless

login, …), usually it’s mentioned in the javadoc by giving data-obj (cf next chapter) used with notation like xxxxx.yyyy with xxxx the test-case and yyyy data- obj. 6.1.5. Look Test Log In the main

indiqué dans la javadoc qui précise le data-obj (cf paragraphe suivant) qui est utilisé (avec une notation de type xxxxx.yyyy xxxx étant le test-case et yyyy le data-obj). 5.1.5. voir le log du test Dans