176,932 research outputs found
PROMIRAR: Tool for Identifying and Managing Implicit Requirements in SRS Documents
Implicit requirements (IMRs) in software requirements specifications (SRS) are subtle and need to be identified as users may not provide all information upfront. It is found that successful functioning of a software crucially depends on addressing its IMRs. This work presents a novel system called PROMIRAR with an integrated framework of Natural Language Processing, Ontology and Analogy based Reasoning for managing Implicit Requirements. It automates early identification and management of IMRs and is found helpful in targeted application domain. We present the PROMIRAR system with its architecture, demo and evaluation
An automated tool support for managing implicit requirements using Analogy-based Reasoning
Systems requirements are crucial to the proper functioning of a software and must be met for a project to be successful. Hence the need for its effective management. Implicit Requirements (IMRs) however are difficult to manage as a result of their nature-vague, unclear, and ambiguous amongst other characteristics. The process of requirement management is a continuous cycle as change in requirements and emergence of new requirements occur in a system. Hence the need for a tool/approach which identifies and manages requirements (implicit and explicit) effectively. However, most systems do not manage implicit requirements as a lot of attention is focused on explicit requirements. This research presents an approach for identification and management of IMRs using Analogy-based Reasoning in combination with two other core technologies (Ontology and Natural Language Processing). The approach is supported by a prototype tool, which was assessed by conducting a preliminary evaluation. The results indicate that the approach enables for early identification of IMRs when used with a good domain ontology and is potentially suitable for application in practice by expert
Attempto - From Specifications in Controlled Natural Language towards Executable Specifications
Deriving formal specifications from informal requirements is difficult since
one has to take into account the disparate conceptual worlds of the application
domain and of software development. To bridge the conceptual gap we propose
controlled natural language as a textual view on formal specifications in
logic. The specification language Attempto Controlled English (ACE) is a subset
of natural language that can be accurately and efficiently processed by a
computer, but is expressive enough to allow natural usage. The Attempto system
translates specifications in ACE into discourse representation structures and
into Prolog. The resulting knowledge base can be queried in ACE for
verification, and it can be executed for simulation, prototyping and validation
of the specification.Comment: 15 pages, compressed, uuencoded Postscript, to be presented at EMISA
Workshop 'Naturlichsprachlicher Entwurf von Informationssystemen -
Grundlagen, Methoden, Werkzeuge, Anwendungen', May 28-30, 1996, Ev. Akademie
Tutzin
The REVERE project:Experiments with the application of probabilistic NLP to systems engineering
Despite natural language’s well-documented shortcomings as a medium for precise technical description, its use in software-intensive systems engineering remains inescapable. This poses many problems for engineers who must derive problem understanding and synthesise precise solution descriptions from free text. This is true both for the largely unstructured textual descriptions from which system requirements are derived, and for more formal documents, such as standards, which impose requirements on system development processes. This paper describes experiments that we have carried out in the REVERE1 project to investigate the use of probabilistic natural language processing techniques to provide systems engineering support
The Synonym management process in SAREL
The specification phase is one of the most important and least supported
parts of the software development process. The SAREL system has been
conceived as a knowledge-based tool to improve the specification phase.
The purpose of SAREL (Assistance System for Writing Software
Specifications in Natural Language) is to assist engineers in the
creation of software specifications written in Natural Language (NL).
These documents are divided into several parts. We can distinguish the
Introduction and the Overall Description as parts that should be used in
the Knowledge Base construction. The information contained in the
Specific Requirements Section corresponds to the information represented
in the Requirements Base. In order to obtain high-quality software
requirements specification the writing norms that define the linguistic
restrictions required and the software engineering constraints related
to the quality factors have been taken into account. One of the controls
performed is the lexical analysis that verifies the words belong to the
application domain lexicon which consists of the Required and the
Extended lexicon. In this sense a synonym management process is needed
in order to get a quality software specification. The aim of this paper
is to present the synonym management process performed during the
Knowledge Base construction. Such process makes use of the Spanish
Wordnet developed inside the Eurowordnet project. This process generates
both the Required lexicon and the Extended lexicon that will be used
during the Requirements Base construction.Postprint (published version
ELICA: An Automated Tool for Dynamic Extraction of Requirements Relevant Information
Requirements elicitation requires extensive knowledge and deep understanding
of the problem domain where the final system will be situated. However, in many
software development projects, analysts are required to elicit the requirements
from an unfamiliar domain, which often causes communication barriers between
analysts and stakeholders. In this paper, we propose a requirements ELICitation
Aid tool (ELICA) to help analysts better understand the target application
domain by dynamic extraction and labeling of requirements-relevant knowledge.
To extract the relevant terms, we leverage the flexibility and power of
Weighted Finite State Transducers (WFSTs) in dynamic modeling of natural
language processing tasks. In addition to the information conveyed through
text, ELICA captures and processes non-linguistic information about the
intention of speakers such as their confidence level, analytical tone, and
emotions. The extracted information is made available to the analysts as a set
of labeled snippets with highlighted relevant terms which can also be exported
as an artifact of the Requirements Engineering (RE) process. The application
and usefulness of ELICA are demonstrated through a case study. This study shows
how pre-existing relevant information about the application domain and the
information captured during an elicitation meeting, such as the conversation
and stakeholders' intentions, can be captured and used to support analysts
achieving their tasks.Comment: 2018 IEEE 26th International Requirements Engineering Conference
Workshop
Using NLP tools in the specification phase
The software quality control is one of the main topics in the Software
Engineering area. To put the effort in the quality control during the
specification phase leads us to detect possible mistakes in an early
steps and, easily, to correct them before the design and implementation
steps start. In this framework the goal of SAREL system, a
knowledge-based system, is twofold. On one hand, to help software
engineers in the creation of quality Software Requirements
Specifications. On the other hand, to analyze the correspondence between
two different conceptual representations associated with two different
Software Requirements Specification documents.
For the first goal, a set of NLP and Knowledge management tools is
applied to obtain a conceptual representation that can be validated and
managed by the software engineer.
For the second goal we have established some correspondence measures in
order to get a comparison between two conceptual representations. This
information will be useful during the interaction.Postprint (published version
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