Disclosed embodiments provide techniques for generating and using a Global Error-Code Sequence (GECS), with the role of generating, at request, a unique error identification number (ID). The scope of the unique identification number can include worldwide, company-wide, or a certain application ecosystem, such as eCommerce applications, etc. The GECS forms a strong correlation between an error condition and a known solution. While other logging signatures such as line numbers, stack traces, and addresses can change with new releases or invocations, the GECS enables a tighter coupling between an error condition and a knowledgebase document, which enables faster resolution of computer application problems and reduced downtime.

A method for managing an application snippet includes: obtaining a first application snippet (S210); determining first classification information of the first application snippet (S220); determining that classification information of a first composite application on the terminal device matches the first classification information (S230); and adding the first application snippet to the first composite application (S240). According to the method for managing an application snippet, a large quantity of application snippets can be effectively managed.

A method for managing an application snippet includes: obtaining a first application snippet (S210); determining first classification information of the first application snippet (S220); determining that classification information of a first composite application on the terminal device matches the first classification information (S230); and adding the first application snippet to the first composite application (S240). According to the method for managing an application snippet, a large quantity of application snippets can be effectively managed.

A system may include a computer processor and a repository configured to store a first code fragment including language features represented in a first programming language, and a second code fragment including language features represented in a second programming language. The system may further include a universal code fragment classifier, executing on the computer processor and configured to generate a first universal abstract syntax tree for the first code fragment and a second universal abstract syntax tree for the second code fragment, generate, using a graph embedding model, first vectors for the first universal abstract syntax tree and second vectors for the second universal abstract syntax tree, and classify, by executing an abstract syntax tree classifier on the first vectors and the second vectors, the first code fragment as a first code category and the second code fragment as a second code category.

A system may include a computer processor and a repository configured to store a first code fragment including language features represented in a first programming language, and a second code fragment including language features represented in a second programming language. The system may further include a universal code fragment classifier, executing on the computer processor and configured to generate a first universal abstract syntax tree for the first code fragment and a second universal abstract syntax tree for the second code fragment, generate, using a graph embedding model, first vectors for the first universal abstract syntax tree and second vectors for the second universal abstract syntax tree, and classify, by executing an abstract syntax tree classifier on the first vectors and the second vectors, the first code fragment as a first code category and the second code fragment as a second code category.

Disclosed herein are techniques for identifying software interdependencies based on functional line-of-code behavior and relation models. Techniques include identifying a first portion of executable code associated with a first controller; accessing a functional line-of-code behavior and relation model representing functionality of the first portion of executable code and a second portion of executable code; determining, based on the functional line-of-code behavior and relation model, that the second portion of executable code is interdependent with the first portion of executable code; and generating, based on the determined interdependency, a report identifying the interdependent first portion of executable code and second portion of executable code.

A document creation assistance apparatus includes a tree structure generation unit configured to analyze a learning document for system development and generate a tree structure representing separate sections of the learning document, a frequency calculation unit configured to calculate, per leaf node of the tree structure, a frequency vector of a word that appears, a question extraction unit configured to extract, according to the frequency vector, a word about which a user is to be questioned, a question presentation unit configured to present a question about the extracted word to the user and receive an answer, and a document generation unit configured to generate a document with the extracted word and the answer set in a section of the separate sections of the leaf node according to the separate sections of the tree structure.

A system for self-directed computer system validation includes first logic to provide a graphical user interface to enable a user to select a set of selected requirements from a plurality of available requirements; second logic to select a set of procedures to satisfy the need to test against each of the requirements and document evidence of the outcomes and generate a set of documents for installing and configuring the system and test protocols including all methods and objects needed to validate the system; and third logic to provide the set of documents for installing and configuring the system and test protocols including all methods and objects needed to validate the system.

An approach for dynamically generating comments associated with software source code. The identifies a user accessing the software source code. The approach retrieves data associated with the software source code, e.g., server logs, requirements documents, etc. The approach identifies skills associated with the user. The approach, using artificial intelligence (AI), predicts the reason the user is accessing the software source code. The approach identifies navigation patterns based on the user access. The approach, using AI, dynamically generates comments for the user. The approach overlays the comments on the software sour code under review and displays the combination to the user.

An approach for dynamically generating comments associated with software source code. The identifies a user accessing the software source code. The approach retrieves data associated with the software source code, e.g., server logs, requirements documents, etc. The approach identifies skills associated with the user. The approach, using artificial intelligence (AI), predicts the reason the user is accessing the software source code. The approach identifies navigation patterns based on the user access. The approach, using AI, dynamically generates comments for the user. The approach overlays the comments on the software sour code under review and displays the combination to the user.