International Business Machines Corporation

Kyndryl, Inc.

Santanu Bandyopadhyay

Suryanarayana K Rao

Ramesh Chandra Pathak

Vishal Anand

Sautam Sengupta

Sougata Mukherjea

Ramesh Kumar Goel

Rejy Sasidharan

A system and method for multiple parameter based composite rule data validation includes receiving a request to validate target data of a target object based on constituent parameters, identifying the data type of the target data, suggesting validation rules based on the data type of the target object, generating a set of composite validation queries, identifying at least one composite validation query in the set of composite validation queries corresponding to the constituent parameters and values, validating the target data of the target object against the at least one composite validation query, and returning a validation result for the target data.

Multiple parameter based composite rule data validation

A method for validating data in a hybrid cloud model that includes providing a validation layer in the brokerage module of the hybrid architecture. The validation layer is separate from an applications layer of the hybrid architecture. The method includes sending target object values to a centralized brokerage layer composite query generator (BLCQG) component of the validation layer from an application needing validation of target data time. The method continues with generating a composite validation rule set with the brokerage layer composite query generator (BLCQG) component based on the parameters of the target object values. The method further includes validating the target data item of the target object values with the composite validation rule in the validation rules validator (VRV) component; and sending the target data item that has been validated to the application.

Multiple parameter based composite rule wise data validation in cloud hybrid model

A method, computer program product, and a system to replace monolithic applications with microservices includes a processor(s) obtaining a requirement for the monolithic application. The processor(s) automatically identifies, based on a sentence comprising the requirement, a given component of the monolithic application, based on analyzing the requirement. The processor(s) determines, based on syntax of the sentence, an initial class and a responsibility for the given component. The processor(s) generates a bounded context for the given component, based on analyzing one or more additional sentences comprising the requirement, to identify additional classes beyond the initial class associated with the responsibility in the requirement. The processor(s) identifies, in a microservices architecture executing in a shared computing environment, one or more microservices within the bounded context. The processor(s) generates a stub for use by the user, via the client, for accessing the one or more identified microservices.

Automatic discovery of microservices from monolithic applications

A method, a system and a computer program product for automated ASCII-based object-oriented database schema (OODBS) generation. A parser runs through text sentences of a textual document from a requirements gathering team that includes object-oriented application requirements, and identifies nouns corresponding to an object, and each noun's attributes. An Object-oriented dictionary based ASCII interpreter analyzes the ASCII of the captured requirements. For each identified noun, the system creates first key-value structures mapping each identified object to one or more associated attributes. There is further identified, from the created first key-value structures, any attributes that reference to an identified object, and for each of these identified objects, the system creates second key-value structures mapping, for each attribute identified as a reference, associating a corresponding key where the reference is found as an attribute. An ASCII-based OODB schema is generated based on the first key-values and second key-value structures mappings.

ASCII based instant object oriented schema generation

Relational database schema generation includes obtaining an input requirements specification for a relational database to be generated, interpreting text characters of the requirements specification as values of a predefined character encoding, parsing the interpreted text characters and identifying complete sentences of the requirements specification, identifying, using an input dictionary that specifies combinations of character values of the predefined character encoding, proper nouns in the identified complete sentences and common nouns in the identified complete sentences, and generating a relational database schema script for the relational database, the generating including indicating the identified proper nouns of the complete sentences as entities of the relational database and indicating the identified common nouns of the complete sentences as attributes of those entities.

Relational database schema generation

An approach to generating an application prototype. The approach parses ASCII text-based requirements into a collection of sentences and parses the collection of sentences into collections words associated with the collection of sentences. The approach then uses an ASCII dictionary to determine the nouns and verbs found in the collections of words marking the nouns as entities and the verbs as responsibilities. Further, the approach determines if nouns are shared among the collection of sentences and if they are, then records relationships between the sentences. The approach then generates metadata describing these components and generates byte code based on the metadata. The approach packages the byte code, other data relating to the entry point and type of prototype application, e.g., web-based or standalone and an encryption module for distribution.

ASCII based instant prototype generation

A dynamic cache engine designed to perform advanced, dynamic, application-specific data caching, based on multiple application and user parameters included in client requests that are sent to a server.

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Kolkata, India

Santanu Bandyopadhyay