Abstract: Various technologies pertaining to extracting data encoded in a tree-structured document and generating a table based upon the extracted data are described herein. In a first embodiment, the table is generated without requiring input from a data cleaner. In a second embodiment, the table is generated based upon examples set forth by a data cleaner.

Abstract: Systems and techniques for structured query language (SQL) query formatting by examples are described herein. In an example, a SQL query formatter is adapted to receive a SQL statement, such that the SQL statement is formed using SQL tokens. The SQL query formatter may be further adapted to use a SQL formatter model to format the SQL statement, which results in a formatted SQL statement. The SQL formatter model may be trained using at least one previously executed SQL statement. The SQL formatter model may include format definitions for SQL tokens. The SQL query formatter may be further adapted to output the formatted SQL statement.

Abstract: Described herein are various technologies pertaining to identifying boundaries of a substring in a log file, wherein the substring is to be extracted from the log file and used to construct a table. An indication is received that a user has selected a beginning boundary of the substring, and the ending boundary of the substring is automatically identified.

Abstract: Described herein are various technologies pertaining to identifying boundaries of a substring in a log file, wherein the substring is to be extracted from the log file and used to construct a table. An indication is received that a user has selected a beginning boundary of the substring, and the ending boundary of the substring is automatically identified.

Abstract: Described herein are various technologies pertaining to identifying boundaries of a substring in a log file, wherein the substring is to be extracted from the log file and used to construct a table. An indication is received that a user has selected a beginning boundary of the substring, and the ending boundary of the substring is automatically identified.

Abstract: Described herein are various technologies pertaining to processing a log file, such that the processed log file is well-suited for analysis by a programming by example (PBE) system. When processing the log file, header lines and comment lines in the log file can be automatically identified and filtered from the log file, such that the PBE system does not contemplate the header lines and comment lines. Further, when processing the log file, boundaries of records in the log file can be identified without requiring user input. The PBE system constructs a table based upon the identified boundaries of the records in the log file, wherein the table includes rows that correspond to the records, and further wherein the table fails to include rows that correspond to header lines and comment lines.

Abstract: Various technologies pertaining to extracting data encoded in a tree-structured document and generating a table based upon the extracted data are described herein. In a first embodiment, the table is generated without requiring input from a data cleaner. In a second embodiment, the table is generated based upon examples set forth by a data cleaner.

Abstract: Systems and methods for increasing user confidence in results that are produced by one or more programs that are generated by an underlying Programming-By-Example (PBE) system based on user input examples. A plurality of generated programs that have been generated using one or more user input examples that are indicative of an output that should be achieved to comply with a user determined result are received. The generated programs are narrowed based on one or more sub-expressions of the programs that are likely to cause the resultant program to comply with the user determined result. The one or more sub-expressions are exposed. Input that selects at least one of the one or more exposed sub-expressions to thereby identify the one of the generated programs that will result in the user determined result is received.

Abstract: Various technologies described herein pertain to controlling automated programming for extracting data from an input document. Examples indicative of the data to extract from the input document can be received. The examples can include highlighted regions on the input document. Moreover, the input document can be a semi-structured document (e.g. a text file, a log file, a word processor document, a semi-structured spreadsheet, a webpage, a fixed-layout document, an image file, etc.). Further, an extraction program for extracting the data from the input document can be synthesized based on the examples. The extraction program can be synthesized in a domain specific language (DSL) for a type of the input document. Moreover, the extraction program can be executed on the input document to extract an instance of an output data schema.

Abstract: Systems and methods for increasing user confidence in results that are produced by one or more programs that are generated by an underlying Programming-By-Example (PBE) system based on user input examples. A plurality of generated programs that have been generated using one or more user input examples that are indicative of an output that should be achieved to comply with a user determined result are received. The generated programs are narrowed based on one or more sub-expressions of the programs that are likely to cause the resultant program to comply with the user determined result. The one or more sub-expressions are exposed. Input that selects at least one of the one or more exposed sub-expressions to thereby identify the one of the generated programs that will result in the user determined result is received.

Abstract: Various technologies described herein pertain to controlling automated programming for extracting data from an input document. Examples indicative of the data to extract from the input document can be received. The examples can include highlighted regions on the input document. Moreover, the input document can be a semi-structured document (e.g. a text file, a log file, a word processor document, a semi-structured spreadsheet, a webpage, a fixed-layout document, an image file, etc.). Further, an extraction program for extracting the data from the input document can be synthesized based on the examples. The extraction program can be synthesized in a domain specific language (DSL) for a type of the input document. Moreover, the extraction program can be executed on the input document to extract an instance of an output data schema.

Abstract: A program development framework (PDF) is described herein which allows a user to produce a program in piecemeal fashion by successively specifying program fragments. The PDF creates a new program fragment by receiving keyword information from the user that describes a new program fragment, and then identifies context information that pertains to a programmatic context in which the new program fragment appears within the overall program being created. The PDF then generates a set of candidate program fragments that satisfy the keyword information and the context information, and ranks those candidate program fragments based on ranking information. At least part of the ranking information may be based on statistical information that is produced by analyzing a corpus of previous programs produced by one or more users. The PDF then provides the ranked program fragments to the user using various user-friendly presentation strategies.

Abstract: Various technologies described herein pertain to controlling programming for manipulating an input document based on example(s) and/or natural language input(s). A data manipulation system includes an interface component configured to receive an input document, which is semi-structured or unstructured. The data manipulation system further includes an extraction component configured to synthesize, based on a first input, a first program for parsing data of the input document. The extraction component is configured to execute the first program on the input document to form structured data. The data manipulation system also includes an operation component configured to synthesize, based on a second input, a second program for performing an operation on the structured data. The operation component is configured to execute the second program on the structured data to generate a result of the operation, which is output by the data manipulation system.

Abstract: Various technologies described herein pertain to controlling automated programming for extracting data from an input document. Examples indicative of the data to extract from the input document can be received. The examples can include highlighted regions on the input document. Moreover, the input document can be a semi-structured document (e.g. a text file, a log file, a word processor document, a semi-structured spreadsheet, a webpage, a fixed-layout document, an image file, etc.). Further, an extraction program for extracting the data from the input document can be synthesized based on the examples. The extraction program can be synthesized in a domain specific language (DSL) for a type of the input document. Moreover, the extraction program can be executed on the input document to extract an instance of an output data schema.

Abstract: A program development framework (PDF) is described herein which allows a user to produce a program in piecemeal fashion by successively specifying program fragments. The PDF creates a new program fragment by receiving keyword information from the user that describes a new program fragment, and then identifies context information that pertains to a programmatic context in which the new program fragment appears within the overall program being created. The PDF then generates a set of candidate program fragments that satisfy the keyword information and the context information, and ranks those candidate program fragments based on ranking information. At least part of the ranking information may be based on statistical information that is produced by analyzing a corpus of previous programs produced by one or more users. The PDF then provides the ranked program fragments to the user using various user-friendly presentation strategies.

Abstract: An assessments framework includes a framework batch processor and a partner batch processor. The framework batch processor performs static assessments based on information obtained from a task definition database and a policy database. The partner batch processor outputs dynamic task definitions and dynamic policy information, to be input to the framework batch processor for executing an assessment when a triggering event occurs. The triggering event may be a schedule-based trigger or an event-based trigger.