Graph theory questions are about extracting structure from a network. Once you identify vertices, edges, degrees and paths clearly, the question usually becomes a sequence of short observations.
Graph theory rewards precise vocabulary. Once you identify the vertices, edges, degrees, adjacency, and path lengths clearly, many questions reduce to a sequence of small decisions. That is why graph theory often feels easier after you translate the picture into language first. The drawing matters, but the real mathematical work comes from describing what the drawing is telling you in exact terms.
A strong revision habit is to redraw a graph more cleanly before solving the problem. Reorganising the layout does not change adjacency, but it often makes routes and degree patterns easier to see. That is especially helpful on crowded shortest-path questions.
It is also worth checking whether the question is about the shape of the network or about weights on the network. A path can use fewer edges but still have a larger total weight. Keeping that distinction clear helps you decide whether you should count connections, compare distances, or analyse a property of the graph as a whole.
These topics reward careful structure more than fast calculation. In complex numbers, discrete mathematics, graph theory, and number theory, the key objects carry meaning that should stay visible all the way through the working. Real and imaginary parts, matrix entries, graph properties, and modular statements all behave best when they are written clearly and interpreted consistently.
A reliable way to revise is to explain each line of working in words as you go. If you can say what a power of i is doing, what a matrix row represents, what a graph property implies, or what a congruence statement means, then the notation is working for you rather than against you. That level of clarity usually prevents the small symbolic errors that turn easy marks into lost marks.