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Text retrieval–based feature location techniques (FLTs) use information from the terms present in documents in classes and methods. However, relevant terms originating from certain locations (eg, method names) often comprise only a small part of the entire method lexicon. Feature location techniques should benefit from techniques that make greater use of this information. The primary objective of this study was to investigate how weighting terms from different locations in source code can improve a latent Dirichlet allocation (LDA)‐based FLT. We conducted an empirical study of 4 subject software systems and 372 features. For each subject system, we trained 1024 different LDA models with new weighting schemes applied to leading comments, method names, parameters, body comments, and local variables. We conducted both a quantitative and qualitative analysis to identify the effects of using the weighting …