Abstract
Software engineers must contend with situations in which they are exposed to an excess of information, cannot readily express the kinds of information they need, or must make decisions where computation of the unequivocally correct answer is infeasible. Recommendation systems have the potential to assist in such cases. This paper overviews some recent developments in recommendation systems for software engineering, and points out their similarities to and differences from more typical, commercial applications of recommendation systems. The paper focuses in particular on the problem of software reuse, and speculates why the recently cancelled Google Code Search project was doomed to failure as a general purpose tool.
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Walker, R.J. (2013). Recent Advances in Recommendation Systems for Software Engineering. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_38
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DOI: https://doi.org/10.1007/978-3-642-38577-3_38
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