05-12-2020, 01:52 AM
You deal with maximum values next in your code. They trigger overflows or memory issues quick. I test those limits by pushing the numbers high. Or perhaps negative values sneak in and break positive only logic. You see how that shifts everything around. Also consider zero as a special point. It divides things oddly in calculations.
But floating point numbers bring their own quirks. Precision errors pop up at boundaries. I watch for rounding problems in your algorithms. Then recursion might hit depth limits suddenly. You need to spot when stacks blow up. Perhaps large data sets slow everything down. Memory gets eaten up before you notice.
Now duplicates in lists cause wrong results often. I handle them by thinking ahead in designs. You might assume unique items but reality differs. Also concurrent changes during runs create chaos. Threads interfere without proper care. Perhaps network delays affect distributed versions. Timeouts hit at wrong moments.
You explore graph edges with isolated nodes. They isolate paths and mess connectivity. I trace those isolated spots carefully. But cycles in data lead to infinite loops. You break them with visited checks. Or empty graphs return nothing as expected. Yet you verify the output matches.
Maximum array sizes push hardware hard. I simulate those to see crashes coming. You adjust your code for such extremes. Perhaps minimum values go below expected ranges. Signs flip and logic fails. Now think about null references in objects. They halt execution without warnings.
You consider time limits in real runs. Algorithms timeout on bad inputs. I optimize for worst scenarios always. But space constraints limit your options too. Memory fills up midway through. Perhaps input formats vary unexpectedly. Strings with special chars confuse parsers.
You watch for boundary crossings in ranges. Numbers hit exact limits and fail. I adjust conditions to cover them. Or repeated operations accumulate errors. Precision drifts over time. Perhaps very long strings exceed buffers. You split them to prevent overflows.
Now uneven distributions in data skew results. I balance tests for fairness. You see averages hide the extremes. But rare cases still matter a lot. They decide if your design holds. Perhaps hardware differences change behaviors. Different machines expose new issues.
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