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Miki: a wiki for synchronous modeling of software requirements
Eliciting a high quality requirements model that can be traced down to implementations is a challenge. Keeping models updated for evolving software systems is a further challenge. Formal modelling methods are one approach - but one that is too rigid and costly for many small software engineering companies [1]. We propose a light-weight alternative, using a wiki as the synchronous bridge between requirements capture and more formal modeling features of the IDE such as Eclipse
Towards a framework for improving goal-oriented requirement models quality
Goal-orientation is a widespread and useful
approach to Requirements Engineering. However, quality assessment frameworks focused on goal-oriented processes are either limited or remain on the theoretical side. Requirements quality initiatives range
from simple metrics applicable to requirements documents, to general-purpose quality frameworks that include syntactic, semantic and pragmatic concerns. In some recent works, we have proposed a metrics
framework for goal-oriented models, but the approach did not cover the cycle of quality assessment. In this paper we present a semiotic-based quality assessment proposal built upon the i* framework and the SEQUAL
proposal. We propose a simplification of SEQUAL which can be applied to i* models by defining semantic, pragmatic and social metrics. As a result, we obtain suites of metrics that can be applied to i* goal-oriented requirements models. This theoretical work is put into practice by using iStarML, a XML representation of i* models, over which XQuery sentences compute the proposed metrics.Peer ReviewedPostprint (published version
Analyzing the Non-Functional Requirements in the Desharnais Dataset for Software Effort Estimation
Studying the quality requirements (aka Non-Functional Requirements (NFR)) of a system is crucial in Requirements Engineering. Many software projects fail because of neglecting or failing to incorporate the NFR during the software life development cycle. This paper focuses on analyzing the importance of the quality requirements attributes in software effort estimation models based on the Desharnais dataset. The Desharnais dataset is a collection of eighty one software projects of twelve attributes developed by a Canadian software house. The analysis includes studying the influence of each of the quality requirements attributes, as well as the influence of all quality requirements attributes combined when calculating software effort using regression and Artificial Neural Network (ANN) models. The evaluation criteria used in this investigation include the Mean of the Magnitude of Relative Error (MMRE), the Prediction Level (PRED), Root Mean Squared Error (RMSE), Mean Error and the Coefficient of determination (R2). Results show that the quality attribute “Language” is the most statistically significant when calculating software effort. Moreover, if all quality requirements attributes are eliminated in the training stage and software effort is predicted based on software size only, the value of the error (MMRE) is doubled
Assessment of 3D viewers for the display of interactive documents in the learning of graphic engineering
The purpose of this study is to determine which 3D viewers should be used for the display of interactive graphic
engineering documents, so that the visualization and manipulation of 3D models provide useful support to
students of industrial engineering (mechanical, organizational, electronic engineering, etc). The technical
features of 26 3D visualization software programmes (viewers, publishers, 3D output formats) are examined, to
select the three visualization configurations that best meet our needs at the Graphic Expression Department of
the University of Burgos (Solidworks plus Solidworks eDrawings; Catia plus Catia eDrawings and 3DXML;
several Computer-Aided Design software programmes plus Adobe Acrobat Pro Extended). These are compared
using the Quality Function Deployment tool known as House of Quality. The House of Quality has enabled us
to identify and quantify the importance attached by engineering teachers to each of their requirements for 3D
viewers, and to identify and quantify the technical importance of each of the measurable features of these
viewers
Module-based quality system functionality evaluation in production logistics
Purpose: This paper addresses a comprehensive modeling and functionality evaluation of a
module-based quality system in production logistics at the highest domain abstract level of
business processes.
Design/methodology/approach: All domain quality business processes and quality data
transactions are modeled using BPMN and UML tools and standards at the business process and
data modeling. A modular web-based prototype is developed to evaluate the models addressing
the quality information system functionality requirements and modularity in production logistics
through data scenarios and data queries.
Findings: Using the object-oriented technique in design at the highest domain level, the
proposed models are subject further development in the lower levels for the implementing case.
The models are specifically able to manipulate all quality operations including remedy and control
in a lot-based make-to-order production logistics system as an individual module.
Practical implications: Due to the specification of system as domain design structure, all
proposed BPMs, data models, and the actual database prototype are seen referential if not a
solution as a practical “to-be” quality business process re-engineering template. Originality/value: this paper sets out to provide an explanatory approach using different
practical technique at modeling steps as well as the prototype implementation.Peer Reviewe
Investigating ChatGPT's Potential to Assist in Requirements Elicitation Processes
Natural Language Processing (NLP) for Requirements Engineering (RE) (NLP4RE)
seeks to apply NLP tools, techniques, and resources to the RE process to
increase the quality of the requirements. There is little research involving
the utilization of Generative AI-based NLP tools and techniques for
requirements elicitation. In recent times, Large Language Models (LLM) like
ChatGPT have gained significant recognition due to their notably improved
performance in NLP tasks. To explore the potential of ChatGPT to assist in
requirements elicitation processes, we formulated six questions to elicit
requirements using ChatGPT. Using the same six questions, we conducted
interview-based surveys with five RE experts from academia and industry and
collected 30 responses containing requirements. The quality of these 36
responses (human-formulated + ChatGPT-generated) was evaluated over seven
different requirements quality attributes by another five RE experts through a
second round of interview-based surveys. In comparing the quality of
requirements generated by ChatGPT with those formulated by human experts, we
found that ChatGPT-generated requirements are highly Abstract, Atomic,
Consistent, Correct, and Understandable. Based on these results, we present the
most pressing issues related to LLMs and what future research should focus on
to leverage the emergent behaviour of LLMs more effectively in natural
language-based RE activities.Comment: Accepted at SEAA 2023. 8 pages, 5 figure
ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design
This paper presents prompt design techniques for software engineering, in the
form of patterns, to solve common problems when using large language models
(LLMs), such as ChatGPT to automate common software engineering activities,
such as ensuring code is decoupled from third-party libraries and simulating a
web application API before it is implemented. This paper provides two
contributions to research on using LLMs for software engineering. First, it
provides a catalog of patterns for software engineering that classifies
patterns according to the types of problems they solve. Second, it explores
several prompt patterns that have been applied to improve requirements
elicitation, rapid prototyping, code quality, refactoring, and system design
A CMMI-compliant requirements management and development process
Requirements Engineering has been acknowledged an essential discipline for Software Quality. Poorly-defined processes for eliciting, analyzing, specifying and validating requirements can lead to unclear issues or misunderstandings on business needs and project’s scope. These typically result in customers’ non-satisfaction with either the products’ quality or the increase of the project’s budget and duration. Maturity models allow an organization to measure the quality of its processes and improve them according to an evolutionary path based on levels. The Capability Maturity Model Integration (CMMI) addresses the aforementioned Requirements Engineering issues. CMMI defines a set of best practices for process improvement that are divided into several process areas. Requirements Management and Requirements Development are the process areas concerned with Requirements Engineering maturity.
Altran Portugal is a consulting company concerned with the quality of its software. In 2012, the Solution Center department has developed and applied successfully a set of processes aligned with CMMI-DEV v1.3, what granted them a Level 2 maturity certification. For 2015, they defined an organizational goal of addressing CMMI-DEV maturity level 3.
This MSc dissertation is part of this organization effort. In particular, it is concerned with the required process areas that address the activities of Requirements Engineering. Our main goal is to contribute for the development of Altran’s internal engineering processes to conform to the guidelines of the Requirements Development process area.
Throughout this dissertation, we started with an evaluation method based on CMMI and conducted a compliance assessment of Altran’s current processes. This allowed demonstrating their alignment with the CMMI Requirements Management process area and to highlight the improvements needed to conform to the Requirements Development process area. Based on the study of alternative solutions for the gaps found, we proposed a new Requirements Management and Development process that was later validated using three different approaches.
The main contribution of this dissertation is the new process developed for Altran Portugal. However, given that studies on these topics are not abundant in the literature, we also expect to contribute with useful evidences to the existing body of knowledge with a survey on CMMI and requirements engineering trends. Most importantly, we hope that the implementation of the proposed processes’ improvements will minimize the risks of mishandled requirements, increasing Altran’s performance and taking them one step further to the desired maturity level
Quality Evaluation of Requirements Models: The Case of Goal Models and Scenarios
Context: Requirements Engineering approaches provide expressive model techniques
for requirements elicitation and analysis. Yet, these approaches struggle to manage the
quality of their models, causing difficulties in understanding requirements, and increase
development costs. The models’ quality should be a permanent concern. Objectives: We
propose a mixed-method process for the quantitative evaluation of the quality of requirements
models and their modelling activities. We applied the process to goal-oriented (i*
1.0 and iStar 2.0) and scenario-based (ARNE and ALCO use case templates) models, to
evaluate their usability in terms of appropriateness recognisability and learnability. We
defined (bio)metrics about the models and the way stakeholders interact with them, with
the GQM approach. Methods: The (bio)metrics were evaluated through a family of 16
quasi-experiments with a total of 660 participants. They performed creation, modification,
understanding, and review tasks on the models. We measured their accuracy, speed,
and ease, using metrics of task success, time, and effort, collected with eye-tracking,
electroencephalography and electro-dermal activity, and participants’ opinion, through
NASA-TLX. We characterised the participants with GenderMag, a method for evaluating
usability with a focus on gender-inclusiveness. Results: For i*, participants had better
performance and lower effort when using iStar 2.0, and produced models with lower accidental
complexity. For use cases, participants had better performance and lower effort
when using ALCO. Participants using a textual representation of requirements had higher
performance and lower effort. The results were better for ALCO, followed by ARNE, iStar
2.0, and i* 1.0. Participants with a comprehensive information processing and a conservative
attitude towards risk (characteristics that are frequently seen in females) took
longer to start the tasks but had a higher accuracy. The visual and mental effort was also
higher for these participants. Conclusions: A mixed-method process, with (bio)metric
measurements, can provide reliable quantitative information about the success and effort
of a stakeholder while working on different requirements models’ tasks
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