SYSTEM DESIGN DISCOURSE

One embodiment provides a method including capturing, by a computing device, first information and deliverable information. Traceability is set up across the first information and deliverable information to identify gaps in the first information and the deliverable information. The first information and the deliverable information are analyzed and mapped to layers based on consumers of information. Objectivity in the first information and the deliverable information in each of the layers is determined. The deliverable information that is created during an entire development lifecycle is broken down to mapping the deliverable information to interrogative keywords for the layers. The first information is consumed upon the consumers of information having a discourse with a computing system.

BACKGROUND

The field of embodiments of the present invention relates to a discourse query system that utilizes a level map based on the end user consumption.

Information on rational decision making in product design is not available after various changes and time lapse. Questions can arise in users on the rationale for a particular feature/function. After some time elapses, usage patterns could vary with users coming up with improvement/enhancement needs that could fit in well if information on the architecture/design rationale could be available.

SUMMARY

Embodiments relate to a discourse query system that utilizes a level map based on the end user consumption. One embodiment provides a method including capturing, by a computing device, first information and deliverable information. Traceability is set up across the first information and deliverable information to identify gaps in the first information and the deliverable information. The first information and the deliverable information are analyzed and mapped to layers based on consumers of information. Objectivity in the first information and the deliverable information in each of the layers is determined. The deliverable information that is created during an entire development lifecycle is broken down to mapping the deliverable information to interrogative keywords for the layers. The first information is consumed upon the consumers of information having a discourse with a computing system.

A computer system and a computer program product configured to perform the above-described method are also disclosed herein.

These and other features, aspects and advantages of the present embodiments will become understood with reference to the following description, appended claims and accompanying figures.

DETAILED DESCRIPTION

Embodiments relate to a discourse query system that utilizes a level map based on the end user consumption. One embodiment provides a method including capturing, by a computing device, first information (e.g., assumptions, requirements, design, code, reviews, tests and alternatives per phase of development) and deliverable information. Traceability is set up across the first information and deliverable information to identify gaps in the first information and the deliverable information. The first information and the deliverable information are analyzed and mapped to layers based on consumers of information. Objectivity in the first information and the deliverable information in each of the layers is determined. The deliverable information that is created during an entire development lifecycle is broken down to mapping the deliverable information to interrogative keywords for the layers. The first information is consumed upon the consumers of information having a discourse with a computing system. The embodiments significantly improve design discourse. Some of the features contribute to the advantage of storing data in a level consumer map, i.e., per deliverable/consumable point of the end user, hence the traceability works right to left as right most items are the pieces seen and felt by consumers. The embodiments further contribute to the advantage that based on each consumer query/concern, the logical reasoning for the decision and options considered while taking the decision are derived. Still further, embodiments contribute to the advantage that they are able to either find responses for consumers or be able to take inputs for reconsideration with subject matter experts (SMEs) to understand why it was not considered and to be consumed in any such future venture.

A computer system and a computer program product configured to perform the above-described method are also disclosed herein.

One or more of the following features may be included. In some embodiments the consumers of information comprise end users, maintenance teams and technical owners.

In one or more embodiments, the objectivity in the first information and the deliverable information is stored in a referenceable way. The objectivity in the first information and the deliverable information includes mapping against decision, alternatives considered, decision parameters, and cost-benefit ratio.

In some embodiments, the first information and the analysis are mapped to the layers on an objective basis, and rationalizing subjective content to bring about objective end to end traceability for interrogative queries.

In one or more embodiments, discourse is held as an exchange of concerns about the application or the system to which using APIs, objective data appropriate to a query in a concern is presented back in a scientific manner.

In some embodiments, upon an exchange terminating with responses measured as being incomplete, a computing device (or processor) pushes the exchange to stakeholders.

Requirement, Design or Code/Build are completed as per the need time when processed. This is limited to a few discussions, brainstorming, etc., but largely as mentioned on the need of the time. These details are captured in one or more collaborative (life cycle management) tools. But the problem arises after some years, when users use/see it, they start saying that why was it designed/built in this manner. Could they have not thought of making it differently? And more such similar questions/comments. The end user is not at fault as with the passage of time situations have changed, and now the user may see it as a bad requirement/design/code. Here an intelligent system is needed, where the end user identifies an opportunity of improvement in terms of questions or comment(s), and can raise the same and be provided with the response derived from a collaborative tool (e.g., a software application, etc.) and receive a response.

Conventional techniques mention system design and requirements mapping. These techniques show how changes in the requirements are mapped to the design. Distinguishable, none of these conventional systems provide a level (or leveled) map where each deliverable has a point of interaction that is connected to a level consumer map, which derives the relevant requirement, design, solutions considered, choice proceeded with, etc. The embodiments significantly improve the query processing since based on a query (e.g., search query, etc.), relevant data is presented, and if a sticky point is identified that was not considered during construction of the deliverable it is taken as an input and shared with the relevant stakeholder for further analysis and consumption.

FIG.1illustrates a system architecture10for defining end user levels, mapping a query/concern to the user level and providing a representation of analysis structure data, according to one embodiment. In some embodiments, the system architecture includes a query analyzer/level input (discourse exchange)12that interacts with an end user11, a user level and content level determiner13, an objectivity analyzer and decoder14, information decoder15, a level wise store (e.g., database, storage device, etc.)16and a content source (e.g., database, storage device, etc.)17.

Some embodiments provide mapping for end user consumers at each stage of the process, and for each deliverable for consumers, the system prepares a level consumer map. In one or more embodiments, the level map works for traceability establishments from right to left. In some embodiments, right most items are end products for each consumer level consumed deliverable. Each deliverable has the points of interaction. In some embodiments, generated tree mapping includes the assumptions, decisions, alternate solutions, etc., affecting each interaction point that is derived and mapped. This data is exposed in a manner that on any user raising a concern, that user may be presented with the logic undertaken for that architecture/design/code. Further, based on the query if a sticky point is identified that is raised by the deliverable consumer, and the system identifies that it was not discussed, then the concerned logic is further shared with the system/application owner for their consumption.

In one or more embodiments, a new model of information is represented as content. Some embodiments determine the facts in the content, the instantiation of the facts as data representation if any and capturing the intent of the author or their thread of thinking. One or more embodiments looks at concepts, contexts and prior information structure from an author for the event/session as it creates the proposed information structure. Some embodiments look at the text or textual representation of images, audio, video (enabling art) and determine the facts from the content. In one or more embodiments, the system determines if a noun/adverb/verb is a fact by applying the conditions that it is something that may be sensed in some form or other by a sensor as an extension of human senses; and if it can be described by using the hands/limbs of a user (meaning it can show up as an image). This enables one to detect if it is a fact or an abstract concept. If there is an abstraction as the word represents an instantiation, then such an abstraction as determined by either group representation synonyms or other hierarchical terms is used as the fact. Thus, the content is analyzed to determine the facts and the instantiations. In some embodiments, there is a construct for the facts, instantiations, concepts, and line of thought. In one or more embodiments, information security policies are defined/documented and provided as input to the level map analyzer engine28(FIG.2) that creates rules from a document where necessary. The incoming information is checked for the facts and instantiation against the rules and if anything is to be hidden due to rule exception, that is pointed out (e.g., messaging sent, displayed, report generation, etc.).

FIG.2illustrates a system flow diagram20, according to one embodiment. In some embodiments, the system flow diagram20includes a legacy artifact storage with traceability21, a level map analyzer engine28and user end points32. In one or more embodiments, assumptions, requirements22, design23, code24, test25and reviews27are captured in a collaborative tool (e.g., a software application, etc.). Alternatives (e.g., options considered for each piece) per phase of development26are also captured in the collaborative tool. In one embodiment, in the alternatives per phase of development26implemented with the collaborative tool, the cost benefit analysis of why the implemented solution versus the alternate options is also captured. In some embodiments, the collaborative tool includes a provision to capture the above-mentioned information in a structured manner. In some embodiments, the capturing of the information may be implemented with known technology.

In one or more embodiments, an analyzer (query analyzer/level input12,FIG.1) performs analyzing the traceability for each of the artifacts delivered across phases. The analyzer additionally analyzes the thought process for each piece of a solution, and identifies if there are assumptions, alternate options and performs a cost benefit analysis of the options. If any of these assumptions, and alternate options are found missing, an owner of that artifact is alerted to update. For example, if for some artifacts any of the parameters is missing, the owner needs to confirm this using the collaborative tool. This helps in capturing the thought process for each piece of solution developed.

In some embodiments, the data after this analysis is processed by the level map analyzer engine28to map to end deliveries that an end user would consume/use. This starts with block29that identifies end user points based on what is visible or accessible to users. Block29performs identification of what the end user is consuming. Here the end user consumers might vary at each level. Just as coders would be consumers for design and requirements, clients would be consumers for requirements22, design23, code24, test25, reviews27, etc. The layers of consumers are defined, and based on the identification, end points of deliveries consumed are identified. This analyzed data is stored in the level wise store16(FIG.1).

In one or more embodiments, in block30related requirements22, design23, code24, test25, reviews27, etc. are derived based on end user points. A level map is also prepared in block30. In block31, for new end user points pointed, the system gets the data set with the help of SMEs. At the end of this, each consumed deliverable is broken down in a manner that the user would consume. This is based on what data the user inputs or gets as outputs. In some embodiments, additional considerations may be time, ease of use, etc. For example, when code is being written where a function is being called and results in certain output, the considered values are input and output values. In one example of a function A:Function A (Integer B, Integer c) {Integer D=B+C;Output D;}
In this example, the values of consideration would be B, C, D. Then the requirement and design decision for why two variables are being input, added and output provided are mapped. In some embodiments, similarly on a graphical user interface (GUI) screen, a user sees two input boxes and an output box. Then the options considered from requirements22, design23, code24and test25are fetched. While fetching the data, the intent of the decision is mapped. The mapped analyzed data is stored on one or more servers in the level wise store16(FIG.1).

In one or more embodiments, the data is exposed using APIs that take input and pull out the reasons for the artifact or system to behave in that manner. In one embodiment, this is performed using a mechanism upon an end user raising a concern. Each application is provided an interface, where the user can raise the concern. In some embodiments, this processing may implement conventional techniques.

In some embodiments, concern (of the user) is mapped to the layer to which that user belongs. Then the concern is mapped to the field for which concern is raised. From the analyzed data structure, relevant assumptions, logic and alternate solutions with their cost benefit analysis are fetched. This analysis is presented to the consumer for his/her consumption.

In one or more embodiments, in the user end points processing32, in block33the user is provided a user mechanism (e.g., a GUI, API, etc.) to enter a query for each end user point. In block34, the query is shared with the level map analyzer engine28for processing. In block35, the logic at all levels for approach taken for the query raised is displayed. The display of the analysis user feedback would be requested to understand if the intent of the user question is satisfied. If the user acknowledges that they are completely satisfied, then no further analysis is performed. For unsatisfied users, the input question/concern is sent to the supervised learning team (SMEs) to further refine the end point map and the user analysis map.

FIG.3illustrates a process40for using a computing device to perform processing for a discourse query system that utilizes a level map based on the end user consumption, according to an embodiment. In one embodiment, in block41process40performs capturing, by a computing device, first information (e.g., assumptions, requirements, design, code, reviews, tests and alternatives per phase of development) and deliverable information. In block42, process40performs setting up traceability across the first information and deliverable information to identify gaps in the first information and the deliverable information. In block43, process40performs analyzing and mapping the first information and the deliverable information to layers based on consumers of information. In block44, process40performs determining objectivity in the first information and the deliverable information in each of the layers. In block45, process40performs breaking down the deliverable information that is created during an entire development lifecycle to mapping the deliverable information to interrogative keywords for the layers. In block46, process40performs consuming the first information upon the consumers of information having a discourse with a computing system. Thus, the process40achieves design discourse with the advantage of storing data in a level consumer map, i.e., per deliverable/consumable point of the end user, hence the traceability works right to left as right most items are the pieces seen and felt by consumers. Process40contributes to the advantage that based on each consumer query/concern, the logical reasoning for the decision and options considered while taking the decision are derived. Process40further contributes to the advantage that it is able to either find responses for consumers or be able to take inputs for reconsideration with SMEs to understand why it was not considered and to be consumed in any such future venture.

In one or more embodiments, process40may further include the feature that the first information is generated in various phases and comprises information about a system or an application, and the deliverable information comprises requirements, architecture, design, pseudo-code, and verification information.

In one or more embodiments, process40may include the feature that the consumers of information comprise end users, maintenance teams and technical owners.

In some embodiments, process40may further include processing for storing the objectivity in the first information and the deliverable information in a referenceable way. The objectivity in the first information and the deliverable information includes mapping against decision, alternatives considered, decision parameters, and cost-benefit ratio.

In one or more embodiments, process40may further include processing for mapping the first information and the analysis to the layers on an objective basis, and rationalizing subjective content to bring about objective end to end traceability for interrogative queries.

In some embodiments, process40may include the feature that discourse is held as an exchange of concerns about the application or the system to which using APIs, objective data appropriate to a query in a concern is presented back in a scientific manner.

In one or more embodiments, process40may further include the feature that upon an exchange terminating with responses measured as being incomplete, a computing device (or processor) pushes the exchange to stakeholders.

In one example embodiment, a use case for a residential building is described as follows. In some embodiments, the starting point is the requirement of what the end user expects in the building, such as three (3) rooms with attached bathrooms, one (1) dining room, a living room, a kitchen, and a garden. These requirements are captured in the collaborative tool (e.g., a software application, etc.) and then a design prepared that provides an overview of what the building would look like. In one or more embodiments, the collaborative tool maps with the dimensions of the land. Then a lower-level design is prepared with the overall size of each room, layout, gates, windows, etc. This is reviewed and the final construction is performed as per the design. While in construction there may be changes based on some feasibility and run time decisions that are recorded in the collaborative tool. It can be seen that there is traceability beginning from the requirement to the final delivered residential building, i.e., left to right traceability. Further, while generating a level map, the map is prepared based on the end user consumption; just as it would involve gates, windows, air conditioners, and other parameters. Hence the collaborative tool derives all the related construction points, low- and high-level design, reviews and requirements related to each consumable item. This level map might not have all the consumption points listed at one go. Therefore, in one or more embodiments the level map is an extendible map, which as consumers point out would add to the level map and try to derive related points. Therefore, the same may be shared with the consumer. For example, a consumer is trying to put a nail on the wall and has query or concern for the same. Then the wall and cement related quality details are fetched. If there are no responses or details found, then the query/observation would be shared with the SMEs.

In another example embodiment, a use case for a software financial application is described as follows. The starting point is the requirement of what the end user expects from the application for financial payments. For example, the collaborative tool may need a user to register with details in order to be able to login. The end user may then choose the payee to make a payment and logoff. This requirement is captured in the collaborative tool and then a design is prepared that provides an overview of what the software financial application would look like. In some embodiments, the collaborative tool maps with the usage flow, and load capacity. Then a lower-level design is generated per functionality or per module/process of how that independent system would work, in terms of the compliances. In one or more embodiments, the design is reviewed at each step and final coding is generated as per the design. While coding there would be changes based on some feasibility and run time decisions that are recorded in the collaborative tool. It can be seen that there is traceability beginning from the requirement to the final delivered software financial application, i.e., left to right traceability. While preparing a level map, it is prepared based on the end user consumption. For example, the map would involve registration fields, login screen, payment screen and its fields, logout screen and other parameters. Hence the collaborative tool derives all the related points, requirements, low- and high-level design, reviews and requirements related to each consumable item. This level map might not have all the consumption points listed at one go. Therefore, in some embodiments the level map is an extendible level map, which as consumers point out would add to the level map and try to derive related points, such that the same may be shared with the consumer. For example, a consumer is trying to make payment in decimals and has a query or concern for the same, then the related quality details are fetched. If there is no response or details found, then the query/observation would be shared with the SMEs.