Abstract: A method, computer system, and a computer program product for generating instructions to highlight software change may be provided. In one embodiment, the technique comprises obtaining information about a requested modification to an original code of a software program and classifying it based on the type of change requested by the modification. The unit tests available are then identified. At least one of the identified unit tests are selected and customized based on classification of the type of code modification requested. Using the at least one selected and customized unit test, the differences between the original and modified code may be identified. One or more test execution stories are then generated related to the modification of the code, to highlight the changes. Test execution stories are further analyzed to provide any additional missing information.

Abstract: A question database storing questions and a conditional probability of one question to be asked given that a previous question was asked is searched to predict a future question based on the conditional probability stored in the question database given an input question as the previous question. The future question is suggested to a user. Responsive to receiving an acceptance of the future question, the question database is updated to strengthen the conditional probability associated with the future question occurring given the input question. An answer to the future question can be provided and searching, predicting, suggesting and updating may be repeated, with the future question as the input question, until the future question is declined.

Abstract: Approaches presented herein enable asset identification for collaborative projects in software development. More specifically, a plurality of assets is identified. Content provided by at least one asset of the plurality of assets is determined. A project that is associated with the content provided by the at least one asset is determined. A repository associated with the project to include the at least one asset is updated.

Abstract: A method of repairing crashed applications includes detecting a crash in an application operating in a host computing device. The application is migrated to a remote computer server. The remote computer server provisions computing resources to the application, while the application is resident in the remote computer server. Resumed operation of the application is executed, using the provisioned computing resources, in the remote computer server. Execution results are generated from the application, in the remote computer server. The generated execution results are migrated from the application back to the host computing device.

Abstract: A method of data transformation for acceleration of context migration includes monitoring user actions in a source code development environment using fragment-based source code documents are monitored. A content of each fragment of the source code document is determined. A sequence of execution of the fragments is determined. A status of a project captured by the source code development environment is determined. A fidelity of the data to be transformed to a new execution environment is determined. Upon determining that a new execution environment is warranted based on the determined fidelity, the new execution environment is determined. The one or more fragments are then executed in the new execution environment.

Abstract: A method and system of generating a documentation includes monitoring user actions regarding a model development, wherein the user actions are captured in a source code development environment. Semantic meaning is provided for each user action captured in the source code development environment. A degree of impact of each user action is determined in connection with the model. Actions having a degree of impact in the development of the model that is above a predetermined threshold are identified as impactful actions. An interactive knowledge graph is identified based on the user actions, semantic meaning of each action, and the determined degree of impact of each user action. The interactive knowledge graph is provided to be displayed in a navigable way.

Abstract: A metadata-based scientific data characterization method, system, and computer program product include requesting a user input for a task to specify a rule for the task to determine a quality and a relationship of a data file in a data file database based on metadata associated with the data file, processing a user feedback of results using the rule run on the data file database and tracking the user feedback on the results in order to learn from the user feedback, and based on the learning, creating a modified rule to determine a quality and a relationship of a second data file.

Abstract: A collection of code fragments loaded in an interactive development platform for running on a first processor can be received. A candidate fragment in the collection of code fragments can be determined for migration to a second processor based on characterizing the collection of code fragments. Based on a location of the candidate fragment in the collection of code fragments, a spot can be identified in the collection of code fragments to inject a code for saving program context. The code for saving program context can be injected in the identified spot. Responsive to the code for saving program context having run on the first processor and based on a criterion, the program context can be migrated to the second processor.

Abstract: Approaches presented herein enable asset identification for collaborative projects in software development. More specifically, a plurality of assets is identified. Content provided by at least one asset of the plurality of assets is determined. A project that is associated with the content provided by the at least one asset is determined. A repository associated with the project to include the at least one asset is updated.

Abstract: Techniques for automatically recreating data removed from storage are disclosed. A request to access data at a first storage location is received. It is determined, based on a catalog and using a computer processor, that the data has been removed from the first storage location. In response the data at the first storage location is automatically recreated using the computer processor. The recreating includes identifying a second storage location for the data, based on the catalog, retrieving the data from the second storage location, and storing the data at the first storage location. The catalog is updated to reflect recreating the data at the first storage location.

Abstract: Techniques for automatically recreating data removed from storage are disclosed. A request to access data at a first storage location is received. It is determined, based on a catalog and using a computer processor, that the data has been removed from the first storage location. In response the data at the first storage location is automatically recreated using the computer processor. The recreating includes identifying a second storage location for the data, based on the catalog, retrieving the data from the second storage location, and storing the data at the first storage location. The catalog is updated to reflect recreating the data at the first storage location.

Abstract: A metadata-based scientific data characterization method, system, and computer program product include requesting a user input for a task to specify a rule for the task to determine a quality and a relationship of a data file in a data file database based on metadata associated with the data file, processing a user feedback of results using the rule run on the data file database and tracking the user feedback on the results in order to learn from the user feedback, and based on the learning, creating a modified rule to determine a quality and a relationship of a second data

Abstract: A question database storing questions and a conditional probability of one question to be asked given that a previous question was asked is searched to predict a future question based on the conditional probability stored in the question database given an input question as the previous question. The future question is suggested to a user. Responsive to receiving an acceptance of the future question, the question database is updated to strengthen the conditional probability associated with the future question occurring given the input question. An answer to the future question is provided and searching, predicting, suggesting and updating may be repeated, with the future question as the input question, until the future question is declined.

Abstract: A method for answering a natural-language user query includes receiving a query from a user by a central agent, parsing the query, and determining if an answer is known to the central agent as being within a local database. If the answer is known, the query is answered with a known natural-language answer using the local database. If not, artificial conversational entity (ACE) invocation is performed. The ACE invocation includes determining a topical field for the query, determining an ACE, of a plurality of ACEs, to send the query to, based on the topical field, and sending the query to the ACE. If the ACE is capable of answering, a natural-language answer is received from the ACE and presented to the user. If not, a natural-language answer is created using social knowledge and presented to the user. Social knowledge includes data crawled from subscriber-provided content of social media services.

Abstract: A question database storing questions and a conditional probability of one question to be asked given that a previous question was asked is searched to predict a future question based on the conditional probability stored in the question database given an input question as the previous question. The future question is suggested to a user. Responsive to receiving an acceptance of the future question, the question database is updated to strengthen the conditional probability associated with the future question occurring given the input question. An answer to the future question can be provided and searching, predicting, suggesting and updating may be repeated, with the future question as the input question, until the future question is declined.

Abstract: A method for answering a natural-language user query includes receiving a query from a user by a central agent, parsing the query, and determining if an answer is known to the central agent as being within a local database. If the answer is known, the query is answered with a known natural-language answer using the local database. If not, artificial conversational entity (ACE) invocation is performed. The ACE invocation includes determining a topical field for the query, determining an ACE, of a plurality of ACEs, to send the query to, based on the topical field, and sending the query to the ACE. If the ACE is capable of answering, a natural-language answer is received from the ACE and presented to the user. If not, a natural-language answer is created using social knowledge and presented to the user. Social knowledge includes data crawled from subscriber-provided content of social media services.

Abstract: A system for coordinating multiple chatbots in a group conversation using natural dialog systems, including a creation unit that enables a user to create a group chat with chatbots; a response unit that allows the user to reply to any utterance extracted from a message received from a member of the group chat; a transmission unit that sends messages to every member of the group chat; a development unit that develops chatbots that understand natural language and interact in a group chat using natural dialogue; a network connection; a first database that stores a knowledge base extracted from all the utterances exchanged by members of the group chat; a second database that stores all interactions between the user and the group chat, and a third database that stores all interaction protocols used by the members of the group chat.

Abstract: A question database storing questions and a conditional probability of one question to be asked given that a previous question was asked is searched to predict a future question based on the conditional probability stored in the question database given an input question as the previous question. The future question is suggested to a user. Responsive to receiving an acceptance of the future question, the question database is updated to strengthen the conditional probability associated with the future question occurring given the input question. An answer to the future question is provided and searching, predicting, suggesting and updating may be repeated, with the future question as the input question, until the future question is declined.