Automatic Generation Mechanism of Cause-Effect Graph with Informal Requirement Specification Based on the Korean Language

In requirement engineering, an important issue is how to transform and tailor the informal system requirements of users or customers into more structured specification documents, which are then used by the software developers. In addition, it is both challenging and necessary to redefine and analyze, from ill-defined or unknown requirements, specifications correctly and automatically generate test cases with them. There are few kinds of research in Korea for automatically reducing requirement complexity and developing test cases of the Korean language-based requirement specifications. Why do we need requirement simplification? Requirement complexity causes analyzers less readability and low understandability. To do this, we propose the automatic cause-effect generation via a requirement simplification mechanism of informal requirement specifications with the Korean language, which works the following procedures: (1) the automatic simplification of informal requirement sentences, (2) the generation of Condition/Conjunction/Clause Tree (C3Tree) Model, (3) and the Cause-effect generation.

Towards a Robust Electronic Agriculture Platform Development

This study identified that the calls to go back to agriculture has reached high decibels and in response several individuals and institutions have shown inclinations towards these calls. The study also identified that agriculture has become knowledge intensive, such that timely, accurate and specifically tailored information have become critical determinant success factors. To aid those disposed to responding to these calls as well as the requisite critical information needs germane to achieving success, the study looked in the direction of Electronic agriculture (Electronic -Agriculture), an emerging research area. And in specific terms, the study analyzed the requirement specifications incidental to meeting the information needs of the identified challenges. And based on the insights gained, the study modeled and simulated a system whose features and functionalities met the requirements for a desirable conceptual framework for setting up an Electronic -Agriculture platform.

ScrumOntoBDD: Agile software development based on scrum, ontologies and behaviour-driven development

When developing a Learning Management System (LMS) using Scrum, we noticed that it was quite often necessary to redefine some system behaviour scenarios, due to ambiguities in the requirement specifications, or due to misinterpretations of stories reported by the Product Owners (POs). The definition of test suites was also cumbersome, resulting in test suites that were incomplete or did not at all comply with the system requirements. Based on this experience and to deal with these problems, in this paper, we propose the ScrumOntoBDD approach to agile software development, which combines Scrum, ontologies and Behaviour-Driven Development (BDD). This approach is centred on the concepts and techniques of Scrum and BDD and focuses on the planning and analysis phases of the software life cycle, since the BDD tools currently provide little support to these phases, while most of the problems during the LMS development were found exactly there. We claim that our approach improves the software development practices in this respect. Furthermore, ScrumOntoBDD employs ontologies in order to reduce ambiguities intrinsic to the use of a natural language as a BDD ubiquitous language. In this paper, we illustrate and systematically evaluate our approach, showing that it is beneficial since it improves the communication between members of an agile development team.

Ambi Detect: An Ambiguous Software Requirements Specification Detection Tool

Software Requirements Specification (SRS) is considered a highly critical artifact in the software development. All phases in software development are influenced by this artifact. Defects in software requirements may higher the risk of project overschedule that contributes to cost overrun of the project.Researchers have shown that finding defects in the initial software development phase is important becausethe cost of the bug is cheaper if it is fixed early. Hence, our main goal is to provide a platform for requirement engineers to produce better requirement specifications. We propose AmbiDetect, a (prototype) tool toautomatically classify ambiguous software requirements. AmbiDetect combines text mining and machine learning for ambiguous requirement specification detection. The text mining technique is used to extract classification features as well as generating the training set.AmbiDetect usesa machine learning technique to perform the ambiguous requirement specification detection. From an initial user study to validate the tool, the result indicates that the accuracy of detection is reasonably acceptable.Although AmbiDetect is an early experimental tool, we optimist that this tool can be a platform to improve SRS quality.

scone – A Requirements Management Tool for the Specification and Variability-Based Analysis of Product Lines

Nowadays, industrial products as well as software applications are expected to be tailored to the user’s needs in an increasingly distinct manner. This often makes it necessary to design a vast number of customized variants, which leads to complex and error prone analysis and development processes. Generally, requirements engineering is considered to be one of the most significant activities in software and system development. Variant management has proven to play an important role in handling the complexity arising from mass-customization of products. However, there are only a few, often rather complex-to-use, applications which allow adding variance information directly to requirements. Especially in case of small and medium sized enterprises, approaches to meet this challenge often result in isolated solutions that are not driven by state-of-the-art analysis methods and do not cope with future requirements. This paper introduces a lightweight requirements management tool called scone, which will be embedded into an overall variability management methodology. scone enables the user to create and manage requirement specifications and augment them with variability information. Based on this specification, the requirements can be analyzed in a formal way with respect to their variability using the variability management tool Glencoe. scone was created as a single-page web application to eliminate the need for installation and allow it to run on many devices, while offering the experience of working with a native application, rather than a website. Both tools are designed to provide a proof of concept for the seamless integration of variability information within a system development process as well as to show how variability can be handled in an easy-to-use way from the very beginning within this process.