Quality indicators regarding a software project under development that has a plurality of functional areas are collected. Each quality indicator is normalized to a coverage of the functional area of the software project to which the quality indicator corresponds. The normalized quality indicators are correlated to previously identified anomalies of the software project, yielding an anomaly indicative value for each normalized quality indicator corresponding to a probability that the normalized quality indicator is revelatory of unidentified anomalies of the software project. A normal behavior for each normalized quality indicator is estimated. For each functional area of the software project, an anomaly score indicative of a likelihood of an unidentified anomaly within the functional area is calculated. The anomaly score is based on, for each normalized quality indicator corresponding to the functional area, how the normalized quality indicator departs from its estimated normal behavior as weighted by its anomaly indicative value.

Quality indicators regarding a software project under development that has a plurality of functional areas are collected. Each quality indicator is normalized to a coverage of the functional area of the software project to which the quality indicator corresponds. The normalized quality indicators are correlated to previously identified anomalies of the software project, yielding an anomaly indicative value for each normalized quality indicator corresponding to a probability that the normalized quality indicator is revelatory of unidentified anomalies of the software project. A normal behavior for each normalized quality indicator is estimated. For each functional area of the software project, an anomaly score indicative of a likelihood of an unidentified anomaly within the functional area is calculated. The anomaly score is based on, for each normalized quality indicator corresponding to the functional area, how the normalized quality indicator departs from its estimated normal behavior as weighted by its anomaly indicative value.

A system and method are disclosed for creating solution design blueprints. A solution design blueprint is a machine-readable data structure that includes a conceptual design model for an application framework. A user interface is configured to receive a plain language textual request from a user that describes a desired application or solution to a problem. Artificial Intelligence is leveraged to fit the textual request to semantic data models and map elements of the textual request to components of a design library. The resulting solution design blueprint can be presented to a user, and the user interface can be used to provide feedback related to the solution design blueprint that can be utilized to update machine learning algorithms and/or neural networks. In some embodiments, the solution design blueprint can be converted to an application framework that is provided to the use in an integrated development environment of the user interface.

A graphical user interface is used to present one or more candidate patch target stages of a software development pipeline. Prior to deployment of a patch to a particular stage, an operation is performed to verify that a version of a deployed software at the particular stage has not changed since a record of a state of the particular stage was obtained. The deployment of the patch to the particular stage is initiated when the version of the deployed software has not changed.

A method for managing code development comprises: accessing at least one software code project on one or more software development platforms; computing a plurality of signature values, each signature value computed for one of a plurality of operators of the at least one software code project according to a plurality of entries associated with the operator in one of the one or more software development platforms and indicative of a plurality of software development characteristics of the operator; identifying a set of matches in the plurality of operators, each match identified between at least two of the plurality of operators according to the plurality of signature values; and providing the set of matches to at least one management software object for the purpose of performing at least one management task of the at least one code project.

A method for managing code development comprises: accessing at least one software code project on one or more software development platforms; computing a plurality of signature values, each signature value computed for one of a plurality of operators of the at least one software code project according to a plurality of entries associated with the operator in one of the one or more software development platforms and indicative of a plurality of software development characteristics of the operator; identifying a set of matches in the plurality of operators, each match identified between at least two of the plurality of operators according to the plurality of signature values; and providing the set of matches to at least one management software object for the purpose of performing at least one management task of the at least one code project.

An information processing device, includes a memory; and a processor coupled to the memory and configured to: generate second data by adding, to first data including a machine language, first machine language data that may be destroyed at a time of transfer of the first data and second machine language data that is not destroyed at the time of the transfer, and transmit the second data.

An executable application's architecture may be mapped by executing the executable application, inputting a series of request data sets into the executable application, receiving one or more responses from the executable application, and performing an evaluation based on the responses. One or more indications of an architectural component may be extracted from metadata associated with the one or more received responses and associated with a corresponding request data set of the series of request data sets. The one or more indications of an architectural component may be associated with processing by the executable application of the corresponding request data set of the series of request data sets. An architecture of the executable application may be determined based on the one or more indications of an architectural component.

An executable application's architecture may be mapped by executing the executable application, inputting a series of request data sets into the executable application, receiving one or more responses from the executable application, and performing an evaluation based on the responses. One or more indications of an architectural component may be extracted from metadata associated with the one or more received responses and associated with a corresponding request data set of the series of request data sets. The one or more indications of an architectural component may be associated with processing by the executable application of the corresponding request data set of the series of request data sets. An architecture of the executable application may be determined based on the one or more indications of an architectural component.

An improved SDK includes a set of APIs and a crash handler registered with the operating system. Each API is an interface accessible by a computer software application. Up on entrance, each API determines the current thread identifier, and inserts it into a list if it is not already in the list. Each thread identifier corresponds to an API call counter, which is incremented by one at the entrance and decremented by one at the exit point of the API. The SDK also records the identifier of the thread it creates for callback functions. When a crash occurs, the crash handler is executed. It determines that the crash is related to a callback interface if the crash thread identifier matches the callback thread identifier. The crash is determined to be caused by the SDK if the API call counter corresponding to the crash thread identifier is greater than zero.