Abstract: A computer adjusts digital content to match a user language proficiency level. The computer receives digital content including words and monitors word consumption activity of a user. The computer identifies troublesome words associated with content consumption delays and establishing a user language proficiency level based on a difficulty value associated with said troublesome words. The computer identifies content words having difficulty level above the language proficiency level. The computer identifies from a word corpus, exchange candidate words having a difficulty level equal to or below said language proficiency level. The computer generates using a natural language processing (NLP) algorithm, word embeddings for said target words and said exchange candidate words. The computer selects from the exchange candidate words, replacement words having word embeddings substantially the same as the word embeddings of said target words.

Abstract: Described herein are methods, computer program products, and computer systems for video-based user interface (UI) application testing. The method includes receiving first test video data corresponding to test video images of an application executing on a first UI, generating the test video images on a first display, generating application video images on a second display. Further, the method may include determining that a first frame of the test video images and a second frame of the application video images fail to satisfy a predetermined similarity threshold, generating a third UI comprising the second frame of the second UI on a third display, receiving user inputs at the third UI for a first duration, capturing replacement test video images from the third display for the first duration, and generating second test video images, wherein the first frame of the test video images is replaced by the replacement test video images.

Abstract: Described herein are methods, computer program products, and computer systems for video-based user interface (UI) application testing. The method includes receiving first test video data corresponding to test video images of an application executing on a first UI, generating the test video images on a first display, generating application video images on a second display. Further, the method may include determining that a first frame of the test video images and a second frame of the application video images fail to satisfy a predetermined similarity threshold, generating a third UI comprising the second frame of the second UI on a third display, receiving user inputs at the third UI for a first duration, capturing replacement test video images from the third display for the first duration, and generating second test video images, wherein the first frame of the test video images is replaced by the replacement test video images.

Abstract: Described herein are methods, computer program products, and computer systems for video-based user interface (UI) application testing. The method includes receiving first test video data corresponding to test video images of an application executing on a first UI, generating the test video images on a first display, generating application video images on a second display. Further, the method may include determining that a first frame of the test video images and a second frame of the application video images fail to satisfy a predetermined similarity threshold, generating a third UI comprising the second frame of the second UI on a third display, receiving user inputs at the third UI for a first duration, capturing replacement test video images from the third display for the first duration, and generating second test video images, wherein the first frame of the test video images is replaced by the replacement test video images.

Abstract: Embodiments of the invention provide for malware collusion detection in a mobile computing device. In one embodiment, a method for malicious inter-application interaction detection in a mobile computing device includes filtering applications installed in a mobile device to a set of related applications and then monitoring in the mobile device execution of the related applications in the set. The method additionally includes computing resource utilization of one of the related applications executing in a background of the mobile device while also computing execution performance of a different one of the related applications. Finally, the method includes responding to a determination that the computed resource utilization is high while the computed execution performance is poor by generating a notification in the display of the mobile device that the one of the related applications is suspected of malware collusion with the different one of the related applications.

Abstract: A computer adjusts digital content to match a user language proficiency level. The computer receives digital content including words and monitors word consumption activity of a user. The computer identifies troublesome words associated with content consumption delays and establishing a user language proficiency level based on a difficulty value associated with said troublesome words. The computer identifies content words having difficulty level above the language proficiency level. The computer identifies from a word corpus, exchange candidate words having a difficulty level equal to or below said language proficiency level. The computer generates using a natural language processing (NLP) algorithm, word embeddings for said target words and said exchange candidate words. The computer selects from the exchange candidate words, replacement words having word embeddings substantially the same as the word embeddings of said target words.

Abstract: An approach for generating a modified software application by leveraging a customized advertisement between application owner and application vendor. The approach includes identifying a software application from a software application store repository and retrieving information from the software application store repository associated with the software application. The approach creates a requirement based on the retrieved information and identifying one or more vendor based on the requirement. After creating the targeted advertisement aimed at an application owner based on the identified vendor then the approach launches the advertisement campaign. The approach receives the notification from the application owner based on the advertisement to engage the identified vendor and modifies the software application based on the requirement.

Abstract: Embodiments provide a computer-implemented method of recommending camera configuration parameters for taking one or more photographs, the method including: acquiring first spatial dimension data, first temporal dimension data, and first manufacturer dimension data of a particular camera for taking the one or more photographs; inputting the first spatial dimension data, the first temporal dimension data, and the first manufacturer dimension data to a trained machine learning model; recommending, by the trained machine learning model, one or more vantage points for taking the one or more photographs, each vantage point corresponding to a different set of predicted camera configuration parameters; receiving a selection of one of the one or more vantage points from the user; and providing a set of predicted camera configuration parameters corresponding to the selected vantage point.

Abstract: A method includes providing a server executing computer code embodying the chat-bot, receiving, via the server, a requirement for customization of a main computer code, the main computer code including modules, and determining, by the chat-bot, top-k modules of the main computer code potentially affected given the requirement for customization. The determination of the top-k modules includes representing each of the modules of the main computer code in an embedding vector space, representing the requirement for customization as a vector in the embedding space, and fetching the top-k modules nearest the requirement for customization in the embedding space. The method further includes determining a question, communicating the question to an entity providing the requirement for customization, receiving a response to the question, and filtering the top-k modules using the response to determine a set of the modules associated with the requirement for customization.

Abstract: Embodiments provide a computer-implemented method of recommending camera configuration parameters for taking one or more photographs, the method including: acquiring first spatial dimension data, first temporal dimension data, and first manufacturer dimension data of a particular camera for taking the one or more photographs; inputting the first spatial dimension data, the first temporal dimension data, and the first manufacturer dimension data to a trained machine learning model; recommending, by the trained machine learning model, one or more vantage points for taking the one or more photographs, each vantage point corresponding to a different set of predicted camera configuration parameters; receiving a selection of one of the one or more vantage points from the user; and providing a set of predicted camera configuration parameters corresponding to the selected vantage point.

Abstract: A method includes providing a server executing computer code embodying the chat-bot, receiving, via the server, a requirement for customization of a main computer code, the main computer code including modules, and determining, by the chat-bot, top-k modules of the main computer code potentially affected given the requirement for customization. The determination of the top-k modules includes representing each of the modules of the main computer code in an embedding vector space, representing the requirement for customization as a vector in the embedding space, and fetching the top-k modules nearest the requirement for customization in the embedding space. The method further includes determining a question, communicating the question to an entity providing the requirement for customization, receiving a response to the question, and filtering the top-k modules using the response to determine a set of the modules associated with the requirement for customization.

Abstract: A method, system, and program product for implementing a remote resource capacity and utilization optimization is provided. The method includes determining associations with a specified geographical region and an associated topic of interest with respect to social media Website traffic and trends associated with utilization of remote hardware and software resources. Current and historical software application downloads are tracked with respect to the social media Website traffic and trends and a currently consumed capacity of the remote hardware and software resources are detected with respect to the specified geographical region. Future resource requirements associated with the currently consumed capacity are determined and data representing the current and historical software application downloads is stored.

Abstract: As part of identifying a theme corresponding to a wireframe, the wireframe comprising a set of graphical elements is analyzed, the set of graphical elements specifying a graphical representation of a user interface of a front-end application. A similarity measure is computed, the similarity measure quantifying a degree of similarity between the theme and an entry in a feature implementation history stored in a code repository. From the entry, a first feature to be implemented in a back-end application is extracted, the first feature servicing a data request from the front-end application. A source code stub extracted from the code repository, comprising a partial implementation of the first feature in the back-end application, is coupled with a first graphical element in the set of graphical elements in the wireframe.

Abstract: As part of identifying a theme corresponding to a wireframe, the wireframe comprising a set of graphical elements is analyzed, the set of graphical elements specifying a graphical representation of a user interface of a front-end application. A similarity measure is computed, the similarity measure quantifying a degree of similarity between the theme and an entry in a feature implementation history stored in a code repository. From the entry, a first feature to be implemented in a back-end application is extracted, the first feature servicing a data request from the front-end application. A source code stub extracted from the code repository, comprising a partial implementation of the first feature in the back-end application, is coupled with a first graphical element in the set of graphical elements in the wireframe.

Abstract: A method for accessing a resource utilizing a reusable access token. The method includes one or more computer processors generating an initial token, wherein the initial token is associated with a remotely stored backup copy of the initial token. The method further includes transmitting the initial token to a client device. The method further includes receiving a modified token from the client device. The method further includes responding to receiving the modified token by determining that the received modified token is valid. The method further includes responding to determining that the received modified token is valid by granting access to a protected resource.

Abstract: A method for accessing a resource utilizing a reusable access token. The method includes one or more computer processors generating an initial token, wherein the initial token is associated with a remotely stored backup copy of the initial token. The method further includes transmitting the initial token to a client device. The method further includes receiving a modified token from the client device. The method further includes responding to receiving the modified token by determining that the received modified token is valid. The method further includes responding to determining that the received modified token is valid by granting access to a protected resource.

Abstract: As part of identifying a theme corresponding to a wireframe, the wireframe comprising a set of graphical elements is analyzed, the set of graphical elements specifying a graphical representation of a user interface of a front-end application. A similarity measure is computed, the similarity measure quantifying a degree of similarity between the theme and an entry in a feature implementation history stored in a code repository. From the entry, a first feature to be implemented in a back-end application is extracted, the first feature servicing a data request from the front-end application. A source code stub extracted from the code repository, comprising a partial implementation of the first feature in the back-end application, is coupled with a first graphical element in the set of graphical elements in the wireframe.

Abstract: As part of identifying a theme corresponding to a wireframe, the wireframe comprising a set of graphical elements is analyzed, the set of graphical elements specifying a graphical representation of a user interface of a front-end application. A similarity measure is computed, the similarity measure quantifying a degree of similarity between the theme and an entry in a feature implementation history stored in a code repository. From the entry, a first feature to be implemented in a back-end application is extracted, the first feature servicing a data request from the front-end application. A source code stub extracted from the code repository, comprising a partial implementation of the first feature in the back-end application, is coupled with a first graphical element in the set of graphical elements in the wireframe.

Abstract: Transforming a user-interface modality of a software application can include identifying a first workflow segment corresponding to a UI modality of an application developed to run on a predetermined data processing platform and selecting one or more other workflow segments to transform the UI modality of the application. Each other workflow segment performs on a different data processing platform a function comparable to a function performable by the first workflow segment. The one or more other workflow segments can be selected from a multi-member set of alternative workflow segments that are semantically similar to the first workflow segment. The selecting can be based on classifying the first workflow segment with a classification model trained using machine learning to map workflow segments and corresponding UI modalities to different processing platforms.

Abstract: An approach for generating a modified software application by leveraging a customized advertisement between application owner and application vendor. The approach includes identifying a software application from a software application store repository and retrieving information from the software application store repository associated with the software application. The approach creates a requirement based on the retrieved information and identifying one or more vendor based on the requirement. After creating the targeted advertisement aimed at an application owner based on the identified vendor then the approach launches the advertisement campaign. The approach receives the notification from the application owner based on the advertisement to engage the identified vendor and modifies the software application based on the requirement.