Application of the Prototype Model in Cooperative Profile Web Application Design

The development of information technology has triggered everyone in the business world, including cooperatives, to change the service system that was initially conventional to switch to digital. This is because the traditional business approach has several shortcomings in disseminating information on cooperative business profiles to external parties, such as limited access to information, slow dissemination of information, and being time-consuming and costly. For this reason, developing a business profile web application is needed to provide efficient access to information without limitations of space and time. However, there is a problem with how to design an application that fits the needs and meets user expectations. The prototype model can be used as a benchmark for an application, whether it is feasible to implement or not, following the results of the evaluation of user satisfaction. So, in this study, it is proposed to apply a prototype model to design applications that suit the needs and expectations of users. The application's design has been assessed using a questionnaire distributed to 30 respondents. The average result of the feasibility of the prototype design made is 93.05%, with a very feasible category

What influences the speed of prototyping? An empirical investigation of twenty software startups

It is essential for startups to quickly experiment business ideas by building tangible prototypes and collecting user feedback on them. As prototyping is an inevitable part of learning for early stage software startups, how fast startups can learn depends on how fast they can prototype. Despite of the importance, there is a lack of research about prototyping in software startups. In this study, we aimed at understanding what are factors influencing different types of prototyping activities. We conducted a multiple case study on twenty European software startups. The results are two folds, firstly we propose a prototype-centric learning model in early stage software startups. Secondly, we identify factors occur as barriers but also facilitators for prototyping in early stage software startups. The factors are grouped into (1) artifacts, (2) team competence, (3) collaboration, (4) customer and (5) process dimensions. To speed up a startups progress at the early stage, it is important to incorporate the learning objective into a well-defined collaborative approach of prototypingComment: This is the author's version of the work. Copyright owner's version can be accessed at doi.org/10.1007/978-3-319-57633-6_2, XP2017, Cologne, German

Prospective Member Sourcing System

This Major Qualifying Project (MQP) details a Prospective Member Sourcing system prototype that the team developed for the Communispace Corporation\u27s Client and Consumer Services team. The project objective was to enable more efficient recruitment and resource allocation by providing the Client and Consumer Services team the ability to source community members through data centralization. Throughout this paper, the team overviews the synthesis and application of their academic knowledge, as well as their methodology, for developing the system prototype

Enhancing Use Cases with Screen Designs. A Comparison of Two Approaches

This paper presents a language called ScreenSpec that can be used to quickly specify screens during the requirements elicitation phase. Experiments and case studies presented in this paper show that it is easy to learn and effective to use. ScreenSpec was successfully applied in 9 real projects. Visual representation generated from ScreenSpec can be attached to requirements specification (e.g. as adornments to use cases)

DataMock: An Agile Approach for Building Data Models from User Interface Mockups

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches

SEARCH RESULT SYNONYMY INDEXING FOR SOCIAL NETWORK USING LATENT SEMANTIC ANALYSIS

Information retrieval (IR) has fashion the way of people acquiring information in Internet. Among of these are known as a search feature. Although semantic search is increasingly popular, not all the web has the technology to apply in their system mainly because of the various reasons of cost. Social network are known for their abstract and inconsistent of semantic data. This assessment is using term frequency vector of Wikipedia content to gather the most frequently terms within corpus as synonym data. After an overview of traditional search engine mechanism works and how synonym of a word associates meaning, the review solves broader and wider of data retrieval index by collecting same-meaning query in from search-data registry in social network by abstraction using Latent Semantic Analysis Synset. Conceptual relationships of set of query could be specified by taxonomy or it could be less passive inarticulate by statistical related to other words

DataMock: An Agile Approach for Building Data Models from User Interface Mockups

In modern software development, much time is devoted and much attention is paid to the activity of data modeling and the translation of data models into databases. This has motivated the proposal of different approaches and tools to support this activity, such as semiautomatic approaches that generate data models from requirements artifacts using text analysis and sets of heuristics, among other techniques. However, these approaches still suffer from important limitations, including the lack of support for requirements traceability, the poor support for detecting and solving conflicts in domain-specific requirements, and the considerable effort required for manually checking the generated models. This paper introduces DataMock, an Agile approach that enables the iterative building of data models from requirements specifications, while supporting traceability and allowing inconsistencies detection in data requirements and specifications. The paper also describes how the approach effectively allows improving traceability and reducing errors and effort to build data models in comparison with traditional, state-of-the-art, data modeling approaches.Laboratorio de Investigación y Formación en Informática Avanzad