Java Programming Project Sample

A Discussion of How You Approached the Project

To tackle the project, I began by thoroughly examining the provided requirements and the skeleton program. I soon understood that my primary task was to enhance the current program, enabling it to parse and exhibit a variety of image types as dictated by an advanced grammar.

Initially, adjustments were made to the Lexer class to efficiently handle string tokens. To complement this, the relevant tokens were incorporated into the Tokens enumerated type.

As I progressed, my attention pivoted to the Parser class, which needed significant modifications to be compatible with the extended grammar. This involved refreshing the existing grammar rules and devising new production rules. These new rules were crucial for the inclusion of diverse image forms, such as parallelograms, regular polygons, isosceles triangles, and text representations. A pivotal aspect of this phase was ensuring the parsing mechanism aptly recognized and instigated the creation of the image objects in line with the interpreted tokens.

Subsequent to these foundational changes, the next step was the actual implementation of the classes for every new image type. Classes like Text, SolidPolygon, IsoscelesTriangle, Parallelogram, and RegularPolygon were crafted during this phase. A conscious effort was made to ensure that these new classes were derivatives of the overarching Image class. Moreover, they were tailored to accommodate the stipulated constructors and draw methods, as set out in the project guidelines. During this phase, allocating necessary data structures like arrays became essential, along with the computation of the coordinates to facilitate accurate image rendering.

In the concluding stages, rigorous testing was undertaken. I utilized sample scene definition files as the basis for these tests, aiming to validate the program’s ability to parse and illustrate the images impeccably. Post-testing, a few adjustments and bug resolutions were carried out to guarantee the program’s optimal performance.

A Test Plan and Test Cases

Case	Input	ExpectedOutput	ActualOutput	Pass/Fail
1.	Load input file contains: Scene Polygons (500, 500);RightTriangle Color (255, 0, 0) at (50, 30) Height 100 Width 300;End.	A 500×500 pixel window with a hollow red triangle.	A 500×500 pixel window with a hollow red triangle.	Pass
2.	Load input file contains: Scene Polygons (700, 300);Rectangle Color (0, 128, 255) at (100, 100) Height 200 Width 100;End.	A 700×300 pixel window with a hollow blue rectangle.	A 700×300 pixel window with a hollow blue rectangle.	Pass
3.	Load input file contains: Scene Polygons (500, 500);Isosceles Color (255, 0, 0) at (120, 120) Height 100 Width 200;End.	A 500×500 pixel window with a solid red isosceles triangle.	A 500×500 pixel window with a solid red isosceles triangle.	Pass
4.	Load input file contains: Scene Polygons (500, 500)Parallelogram Color (0, 0, 255) at (40, 150) (440, 120) Offset 30;End.	A 500×500 pixel window with a solid blue parallelogram.	A 500×500 pixel window with a solid blue parallelogram.	Pass
5.	Load input file contains: Scene Polygons (500, 500)RegularPolygon Color(255, 0, 255) at (300, 300) Sides 6 Radius 80;End.	A 500×500 pixel window with a solid pink octagon.	A 500×500 pixel window with a solid pink octagon.	Pass
6.	Load input file contains: Scene Polygons (300, 500)Text Color(0, 0, 0) at (200, 100) “Test Message”;End.	A 300×500 pixel window with black text “Test Message”.	A 300×500 pixel window with black text “Test Message”.	Pass

A Discussion of Lessons Learned From the Project and Any Improvements That Could Be Made

During this project, I enriched my skills by extending a provided program skeleton and seamlessly integrating new functionalities to match given criteria. This endeavor allowed me to delve deep into the intricacies of grammar parsing, the nuances of tokenization, and the management of diverse image objects in a defined scene.

A pivotal takeaway from this experience was understanding the utmost importance of a meticulous analysis of both requirements and grammar rules. Such an analysis guarantees a pinpoint implementation. It’s paramount to grasp the interplay between different classes, predict the behavior of each image type accurately, and execute the proper management of tokens and lexemes.

Furthermore, this project underscored the significance of penning down modular and cleanly structured code. By architecting distinct classes for each image type, the coding landscape became neater and more streamlined. This approach ensured that each class exclusively concentrated on the functionalities of a particular image type, paving the way for a more intuitive understanding and any potential future augmentations.

Looking forward, there are multiple avenues for enhancing this project. Top on the list would be the introduction of robust error handling mechanisms. Such mechanisms, paired with articulate error messaging, would simplify the identification and rectification of parsing or visualization glitches.

On the feature front, contemplating the addition of advanced functionalities like image rotation, scaling, and layering could radically transform the program’s offerings. Such inclusions would empower users to craft and showcase scenes that are both multifaceted and dynamic.

To wrap up the enhancement suggestions, integrating a graphical user interface (GUI) could be game-changing. Such an interface would usher in an interactive platform for users, enabling them to craft, modify, and visualize an assortment of images in a scene with unparalleled ease.

Code Sample