AP Computer Science
Principles – Fall Review
2026 | Study Guide,
Practice Questions,
Answers, Rationales &
Exam Review | Complete
Ethics Study Guide
Updated 2026 Questions and Answers
100% Verified Exam Prep and Comprehensive
Rationales
Included
, Overflow error that results when the number of bits is not enough to hold the number, like a
car's odometer "rolling over"
Round-off error that results when the number of bits is not enough to represent the actual
number, like 3 digits to represent π as 3.14
Lossy Compressing data in a way that throws some data away and makes it almost
impossible to recover the original, great compression, like JPEG images
Lossless Compressing data in a way that preserves all data away and allows full recovery of
the original, good compression -- usually not as good as lossy, like PNG images
Metadata data about data, like a camera storing the location, aperture, shutter speed, etc. for
a digital photo
Sequencing code flows line by line, one after another, like a recipe
Selection a boolean condition to determine which of two algorithmic paths are taken, aka if-
then
Iteration using a looping control structure, like while, for, foreach, repeat, repeat-until, etc.
Reasonable time polynomial in the number of steps an algorithm takes in the worst case based on
the input size
Not reasonable time Usually exponential in the number of steps, like doubling every time your input
grows by one
Heuristic using a "rule" to guide an algorithm, like always walking toward the north star if you
were stuck in a forest
Undecidable A problem that is so difficult, we can't ever create an algorithm that would be able to
answer yes or no for all inputs, like determining if a user's program run on some
input would always stop and not run forever
Principles – Fall Review
2026 | Study Guide,
Practice Questions,
Answers, Rationales &
Exam Review | Complete
Ethics Study Guide
Updated 2026 Questions and Answers
100% Verified Exam Prep and Comprehensive
Rationales
Included
, Overflow error that results when the number of bits is not enough to hold the number, like a
car's odometer "rolling over"
Round-off error that results when the number of bits is not enough to represent the actual
number, like 3 digits to represent π as 3.14
Lossy Compressing data in a way that throws some data away and makes it almost
impossible to recover the original, great compression, like JPEG images
Lossless Compressing data in a way that preserves all data away and allows full recovery of
the original, good compression -- usually not as good as lossy, like PNG images
Metadata data about data, like a camera storing the location, aperture, shutter speed, etc. for
a digital photo
Sequencing code flows line by line, one after another, like a recipe
Selection a boolean condition to determine which of two algorithmic paths are taken, aka if-
then
Iteration using a looping control structure, like while, for, foreach, repeat, repeat-until, etc.
Reasonable time polynomial in the number of steps an algorithm takes in the worst case based on
the input size
Not reasonable time Usually exponential in the number of steps, like doubling every time your input
grows by one
Heuristic using a "rule" to guide an algorithm, like always walking toward the north star if you
were stuck in a forest
Undecidable A problem that is so difficult, we can't ever create an algorithm that would be able to
answer yes or no for all inputs, like determining if a user's program run on some
input would always stop and not run forever
