ݺߣshows by User: eranyahav / http://www.slideshare.net/images/logo.gif ݺߣshows by User: eranyahav / Wed, 27 Nov 2013 04:50:21 GMT ݺߣShare feed for ݺߣshows by User: eranyahav PRIME OOPSLA12 paper /slideshow/prime-oopsla12-paper/28669060 oopsla12-131127045021-phpapp01
We present a novel code search approach for answering queries focused on API-usage with code showing how the API should be used. To construct a search index, we develop new techniques for statically mining and consolidating temporal API specifications from code snippets. In contrast to existing semantic-based techniques, our approach handles partial programs in the form of code snippets. Handling snippets allows us to consume code from various sources such as parts of open source projects, educational resources (e.g. tutorials), and expert code sites. To handle code snippets, our approach (i) extracts a possibly \emph{partial} temporal specification from each snippet using a relatively precise static analysis tracking a generalized notion of typestate, and (ii) consolidates the partial temporal specifications, combining consistent partial information to yield consolidated temporal specifications, each of which captures a full(er) usage scenario. To answer a search query, we define a notion of relaxed inclusion matching a query against temporal specifications and their corresponding code snippets. We have implemented our approach in a tool called PRIME and applied it to search for API usage of several challenging APIs. PRIME was able to analyze and consolidate thousands of snippets per tested API, and our results indicate that the combination of a relatively precise analysis and consolidation allowed PRIME to answer challenging queries effectively. ]]>
We present a novel code search approach for answering queries focused on API-usage with code showing how the API should be used. To construct a search index, we develop new techniques for statically mining and consolidating temporal API specifications from code snippets. In contrast to existing semantic-based techniques, our approach handles partial programs in the form of code snippets. Handling snippets allows us to consume code from various sources such as parts of open source projects, educational resources (e.g. tutorials), and expert code sites. To handle code snippets, our approach (i) extracts a possibly \emph{partial} temporal specification from each snippet using a relatively precise static analysis tracking a generalized notion of typestate, and (ii) consolidates the partial temporal specifications, combining consistent partial information to yield consolidated temporal specifications, each of which captures a full(er) usage scenario. To answer a search query, we define a notion of relaxed inclusion matching a query against temporal specifications and their corresponding code snippets. We have implemented our approach in a tool called PRIME and applied it to search for API usage of several challenging APIs. PRIME was able to analyze and consolidate thousands of snippets per tested API, and our results indicate that the combination of a relatively precise analysis and consolidation allowed PRIME to answer challenging queries effectively. ]]> Wed, 27 Nov 2013 04:50:21 GMT /slideshow/prime-oopsla12-paper/28669060 eranyahav@slideshare.net(eranyahav) PRIME OOPSLA12 paper eranyahav We present a novel code search approach for answering queries focused on API-usage with code showing how the API should be used. To construct a search index, we develop new techniques for statically mining and consolidating temporal API specifications from code snippets. In contrast to existing semantic-based techniques, our approach handles partial programs in the form of code snippets. Handling snippets allows us to consume code from various sources such as parts of open source projects, educational resources (e.g. tutorials), and expert code sites. To handle code snippets, our approach (i) extracts a possibly \emph{partial} temporal specification from each snippet using a relatively precise static analysis tracking a generalized notion of typestate, and (ii) consolidates the partial temporal specifications, combining consistent partial information to yield consolidated temporal specifications, each of which captures a full(er) usage scenario. To answer a search query, we define a notion of relaxed inclusion matching a query against temporal specifications and their corresponding code snippets. We have implemented our approach in a tool called PRIME and applied it to search for API usage of several challenging APIs. PRIME was able to analyze and consolidate thousands of snippets per tested API, and our results indicate that the combination of a relatively precise analysis and consolidation allowed PRIME to answer challenging queries effectively. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/oopsla12-131127045021-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> We present a novel code search approach for answering queries focused on API-usage with code showing how the API should be used. To construct a search index, we develop new techniques for statically mining and consolidating temporal API specifications from code snippets. In contrast to existing semantic-based techniques, our approach handles partial programs in the form of code snippets. Handling snippets allows us to consume code from various sources such as parts of open source projects, educational resources (e.g. tutorials), and expert code sites. To handle code snippets, our approach (i) extracts a possibly \emph{partial} temporal specification from each snippet using a relatively precise static analysis tracking a generalized notion of typestate, and (ii) consolidates the partial temporal specifications, combining consistent partial information to yield consolidated temporal specifications, each of which captures a full(er) usage scenario. To answer a search query, we define a notion of relaxed inclusion matching a query against temporal specifications and their corresponding code snippets. We have implemented our approach in a tool called PRIME and applied it to search for API usage of several challenging APIs. PRIME was able to analyze and consolidate thousands of snippets per tested API, and our results indicate that the combination of a relatively precise analysis and consolidation allowed PRIME to answer challenging queries effectively.
PRIME OOPSLA12 paper from Eran Yahav
]]> 1072 4 https://cdn.slidesharecdn.com/ss_thumbnails/oopsla12-131127045021-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds document Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 Programming with Millions of Examples (HRL) /slideshow/programming-with-millions-of-examples-hrl/28665648 prime-hrl-131127024803-phpapp01
In a world where programming is largely based on using APIs, semantic code search emerges as a way to effectively learn how such APIs should be used. Towards this end, we present a formal framework for static specification mining that is able to handle code snippets and incomplete programs. Our framework analyzes code snippets and extracts partial temporal specifications. Technically, partial temporal specifications are represented as symbolic automata – automata where transitions may be labeled by variables, and a variable can be substituted by a letter, a word, or a regular language. With the help of symbolic automata, the use of the API is extracted from each snippet of code, and the many separate examples are consolidated to create a full(er) usage scenario database that can be queried. We have implemented our approach in a tool called PRIME and applied it to analyze and consolidate thousands of snippets per tested API. This talk is based on work with Alon Mishne, Sharon Shoham, Eran Yahav, and Hongseok Yang. ]]>
In a world where programming is largely based on using APIs, semantic code search emerges as a way to effectively learn how such APIs should be used. Towards this end, we present a formal framework for static specification mining that is able to handle code snippets and incomplete programs. Our framework analyzes code snippets and extracts partial temporal specifications. Technically, partial temporal specifications are represented as symbolic automata – automata where transitions may be labeled by variables, and a variable can be substituted by a letter, a word, or a regular language. With the help of symbolic automata, the use of the API is extracted from each snippet of code, and the many separate examples are consolidated to create a full(er) usage scenario database that can be queried. We have implemented our approach in a tool called PRIME and applied it to analyze and consolidate thousands of snippets per tested API. This talk is based on work with Alon Mishne, Sharon Shoham, Eran Yahav, and Hongseok Yang. ]]> Wed, 27 Nov 2013 02:48:03 GMT /slideshow/programming-with-millions-of-examples-hrl/28665648 eranyahav@slideshare.net(eranyahav) Programming with Millions of Examples (HRL) eranyahav In a world where programming is largely based on using APIs, semantic code search emerges as a way to effectively learn how such APIs should be used. Towards this end, we present a formal framework for static specification mining that is able to handle code snippets and incomplete programs. Our framework analyzes code snippets and extracts partial temporal specifications. Technically, partial temporal specifications are represented as symbolic automata – automata where transitions may be labeled by variables, and a variable can be substituted by a letter, a word, or a regular language. With the help of symbolic automata, the use of the API is extracted from each snippet of code, and the many separate examples are consolidated to create a full(er) usage scenario database that can be queried. We have implemented our approach in a tool called PRIME and applied it to analyze and consolidate thousands of snippets per tested API. This talk is based on work with Alon Mishne, Sharon Shoham, Eran Yahav, and Hongseok Yang. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/prime-hrl-131127024803-phpapp01-thumbnail.jpg?width=120&amp;height=120&amp;fit=bounds" /><br> In a world where programming is largely based on using APIs, semantic code search emerges as a way to effectively learn how such APIs should be used. Towards this end, we present a formal framework for static specification mining that is able to handle code snippets and incomplete programs. Our framework analyzes code snippets and extracts partial temporal specifications. Technically, partial temporal specifications are represented as symbolic automata – automata where transitions may be labeled by variables, and a variable can be substituted by a letter, a word, or a regular language. With the help of symbolic automata, the use of the API is extracted from each snippet of code, and the many separate examples are consolidated to create a full(er) usage scenario database that can be queried. We have implemented our approach in a tool called PRIME and applied it to analyze and consolidate thousands of snippets per tested API. This talk is based on work with Alon Mishne, Sharon Shoham, Eran Yahav, and Hongseok Yang.
Programming with Millions of Examples (HRL) from Eran Yahav
]]> 425 2 https://cdn.slidesharecdn.com/ss_thumbnails/prime-hrl-131127024803-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post http://activitystrea.ms/schema/1.0/posted 0 https://cdn.slidesharecdn.com/profile-photo-eranyahav-48x48.jpg?cb=1527655079 https://cdn.slidesharecdn.com/ss_thumbnails/oopsla12-131127045021-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/prime-oopsla12-paper/28669060 PRIME OOPSLA12 paper https://cdn.slidesharecdn.com/ss_thumbnails/prime-hrl-131127024803-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/programming-with-millions-of-examples-hrl/28665648 Programming with Milli...