Source code changes can have ripple-effects that result in unchanged source code elements producing different results than they would have produced before the changes. This paper proposes a taxonomy of the types of impacts that can result from source code changes in both procedural and object-oriented code. The taxonomy is extensible by creating additional sub-types of the types proposed. The proposed taxonomy is based on an analysis of existing change impact analysis algorithms and provides a basis for classifying change impact analysis algorithms by the types of impacts they identify.

This study is a quasi experiment comparing the software defect rates and implementation costs of two methods of software defect reduction: code inspection and test-driven development. We divided participants, consisting of junior and senior computer science students at a large Southwestern university, into four groups using a two-by-two, between-subjects, factorial design and asked them to complete the same programming assignment using either test-driven development, code inspection, both, or neither. We compared resulting defect counts and implementation costs across groups. We found that code inspection is more effective than test-driven development at reducing defects, but that code inspection is also more expensive. We also found that test-driven development was no more effective at reducing defects than traditional programming methods.