Jungloid mining

Abstract

Reuse of existing code from class libraries and frameworks is often difficult because APIs are complex and the client code required to use the APIs can be hard to write. We observed that a common scenario is that the programmer knows what type of object he needs, but does not know how to write the code to get the object.In order to help programmers write API client code more easily, we developed techniques for synthesizing jungloid code fragments automatically given a simple query that describes that desired code in terms of input and output types. A jungloid is simply a unary expression; jungloids are simple, enabling synthesis, but are also versatile, covering many coding problems, and composable, combining to form more complex code fragments. We synthesize jungloids using both API method signatures and jungloids mined from a corpus of sample client programs.We implemented a tool, PROSPECTOR, based on these techniques. PROSPECTOR is integrated with the Eclipse IDE code assistance feature, and it infers queries from context so there is no need for the programmer to write queries. We tested PROSPECTOR on a set of real programming problems involving APIs; PROSPECTOR found the desired solution for 18 of 20 problems. We also evaluated PROSPECTOR in a user study, finding that programmers solved programming problems more quickly and with more reuse when using PROSPECTOR than without PROSPECTOR.

Analyzing and mining a code search engine usage log

“…Recent research in software engineering has focused on understanding and supporting the search-driven nature of software development, and many such work have produced tools that aid various search needs of developers (Hoffmann et al 2007;Bajracharya et al 2006Bajracharya et al , 2009Lemos et al 2009;Holmes and Murphy 2005;Mandelin et al 2005;Thummalapenta and Xie 2007;Hummel et al 2008;Reiss 2009). On the other hand, there has been considerable commercial effort in the development of Internet-Scale code search engines that have powerful crawlers and large databases providing an index to large quantities of software available on the Web (Web site for Koders 2010; Web site for Krugle 2010; Web site for Google Code Search 2010).…”

Data-driven synthesis for object-oriented frameworks

“…Prospector [9], XSnippet [13], MAPO [20], PARSEWeb [17], and Strathcona [7] mine source code repositories and assist programmers in common tasks: finding call sequences to derive an object of one type from an object of another type, complex initialization patterns, and frequent API usage patterns. They do so by computing relevant code snippets as determined by the static program context and then applying heuristics to rank them.…”

User-friendly functional programming for web mashups

“…Like MashMaker, Marmite will automatically suggest operations to apply to data. Unlike MashMaker, these suggestions are based on the type of the data (similar to Jungloids (Mandelin et al 2005)), rather than based on the behavior of previous users. Anthracite 14 is similar to Marmite, but requires that the user be familiar with complex concepts such as HTML and regular expressions.…”

“…MashMaker's suggestion system is influenced by Jungloids (Mandelin et al 2005) and Google Suggest 16 . Like Jungloids, MashMaker suggests operations that are appropriate to the data one has at hand.…”