Table 2.

Ranking approaches for source code.

Tool/ Approach	Strength	Weakness
Google Code Search and Ohloh [41,42]	Results are ranked based on textual similarity.	Uses only one feature which is textual similarity.
Sourcerer [29]	Uses the basic notation of CodeRank, which only extracts structural information.	Only focus on structural information of source code.
PARSEWeb [4]	Uses the frequency and length of MIS (method-invocation sequences) to rank the final result.	Uses MIS feature during the ranking phase.
Exemplar [43]	Uses three ranking schemes WOS (word occurrences schema), DCS (dataflow connection schema), and RAS (relevant API calls schema) to rank the application.	This tool ranks the applications, not the source code snippets.
Semantic Code Search [44]	The comparable code snippets that follow the call sequences extrapolated from code snippets determine the ranking.	Uses a call sequence, which is the only feature used for the ranking code snippets.
Pattern-based Approach [45]	This approach considers popularity to rank the working code examples.	Popularity is the only feature that contributed to the final ranking.
QualBoa [37]	This tool incorporates functional and quality attributes	Ranking components based on the functional score