Some embodiments of the invention provide a method for defining code-based policies. The method generates a policy-builder first view of a policy for display in a graphical user interface (GUI) by processing a syntax tree that is generated from a code second view of the policy. The method receives, through the policy-builder first view, a modification to a portion of the policy. To reflect the modification, the method updates a portion of the syntax tree that corresponds to the portion of the policy that is affected by the modification. Based on the updating of the syntax tree, the method updates the code second view by modifying a portion of the code second view that corresponds to the updated portion of the syntax tree.

A separate relationship management interface for applications that utilize application data objects to implement various application features is used to track changes to relationships between application data objects. Requests that cause writes corresponding to relationships between application data objects and requests that cause reads of relationships between application data objects may be handled using an interface that interacts with a separate data store tracking the relationships between application data objects.

A separate relationship management interface for applications that utilize application data objects to implement various application features is used to track changes to relationships between application data objects. Requests that cause writes corresponding to relationships between application data objects and requests that cause reads of relationships between application data objects may be handled using an interface that interacts with a separate data store tracking the relationships between application data objects.

A method for facilitating automatic assignment of code topics is provided. The method includes accessing a database, the database including data that is associated with a known code topic and data that is associated with an unknown code topic; parsing the database to identify a data file that includes a code snippet, document strings, and/or dependencies. Dividing the identified data file into a training data set and a testing data set; generating a first set of features for each element of the code snippet, document strings, and dependencies, for the training data set; generating a second set of features for the testing data set; identifying, by using a model, a representative feature for the training data set based on frequency distribution of the training data set, the representative feature including a corresponding probability; and determining, by using clustering, a code topic for the data file.

Rules can be generated for migrating dependencies of a software application. For example, a computing device can receive a source version of a dependency of a software application and a target version of the dependency of the software application. The computing device can compare the source version to the target version to determine a difference between the source version and the target version. The computing device can receive a template for a rule indicating a location in the source version to be modified for the software application to support the target version. The template can include a fillable section. The computing device can populate the fillable section of the template with a value based on the difference between the source version and the target version.

Rules can be generated for migrating dependencies of a software application. For example, a computing device can receive a source version of a dependency of a software application and a target version of the dependency of the software application. The computing device can compare the source version to the target version to determine a difference between the source version and the target version. The computing device can receive a template for a rule indicating a location in the source version to be modified for the software application to support the target version. The template can include a fillable section. The computing device can populate the fillable section of the template with a value based on the difference between the source version and the target version.

According to an aspect of an embodiment, operations include receiving a set of NL descriptors and a corresponding set of PL codes. The operations further include determining a first vector associated with each NL descriptor and a second vector associated with each PL code, using language models. The operations further include determining a number of a set of semantic code classes to cluster the set of PL codes into the set of semantic code classes, based on the number, the first vector, and the second vector. The operations further include training a multi-class classifier model to predict a semantic code class, from the set of semantic code classes, corresponding to an input NL descriptor. The operations further include selecting an intra-class predictor model based on the predicted semantic code class. The operations further include training the intra-class predictor model to predict a PL code corresponding to the input NL descriptor.

An obfuscated and secured computer-executable source code and a method for providing such a code is provided. Plain text source code is obfuscated and secured so that it is protected and it is more difficult to manipulate and copy it.

An obfuscated and secured computer-executable source code and a method for providing such a code is provided. Plain text source code is obfuscated and secured so that it is protected and it is more difficult to manipulate and copy it.

Methods, computer program products, and/or systems are provided that perform the following operations: reading lines of code included in a collection of source code; identifying an assigned tag in the collection of source code; identifying a start tag location and an end tag location associated with the assigned tag, wherein the lines of code included between the start tag location and the end tag location identify a code block; processing the code block to generate logging data for the code block based, at least in part, on the assigned tag; and providing the logging data for linking to executable byte code compiled from the collection of source code, wherein the logging data is used to log code data relating to the code block during execution of the executable byte code.