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Information retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections (usually stored on computers).

• ‘Documents’ in 101project
     • wiki text (pages or sections) and
     • source-code units with
          • program identifiers and
          • comments

IR scenario

• Objective: find source-code units that implement a
                         specific feature, e.g., ‘Total’.

• Method: search source code for characteristic
                      terms, e.g., ‘total’.
• Challenges:
       • Distinguish feature implementation and testing.
       • Dealing with variation in natural language usage.

Performance and correctness measures in IR

Precision is the fraction of the documents retrieved that are relevant to the user's information need.

                     |{relevant docs} "geschnitten" {retried docs}|
precision =
                                          |{retrieved docs}|


Recall is the fraction of the documents that are relevant to the query that are successfully retrieved.


                     |{relevant docs} "geschnitten" {retrieved docs}|
recall =
                                          |{relevant docs}|