Metrics for measuring the consistencies of requirements with objectives and constraints

Byun, Jung-Won; Rhew, Sung-Yul; Hwang, Mansoo; Sugumara, Vijayan; Park, Sooyong; Park, Soo‐Jin

doi:10.1007/s00766-013-0180-9

Cited by 11 publications

(3 citation statements)

References 13 publications

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“…E-Government applications significantly differ from other software solutions, as specific issues including stakeholders and legislation should be broadly considered. For a long time, functionality-based development has been considered as the main target for most development project, underestimating usability issues and other stakeholder interests [68]. This paper is focused on such concern, providing the basis of stakeholder and legislation analysis to carry out e-Government application development through a user-centered approach.…”

Section: Resultsmentioning

confidence: 99%

A set of prescribed activities for enhancing requirements engineering in the development of usable e-Government applications

Sánchez

Macías

2017

Requirements Eng

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Over the last years, e-Government applications have become indispensable in every country as they help stakeholders carry out tasks with the administration. However, and despite their growing usage, most of these applications are created through a developercentered approach instead of a user-centered one, using traditional development processes that do not fit well with the diversity of stakeholders and existing legislation that involve e-Government applications today. Besides, usability is an important clue in the development of such solutions, so a user-centered approach, combined with a successful stakeholder and legislation analysis, should be considered overall. This paper is focused on addressing these concerns, and it provides a set of prescribed activities, tasks and products to be carried through a user-centered process in order to design usable web-based e-Government solutions. Specifically, our approach considers requirements engineering activities enhancing usability by analyzing the diversity and interests of the stakeholders involved, as well as the specific legislation as a source of organizational requirements. In addition, a validation is provided through a case study, showing the feasibility of the approach presented.

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Section: Resultsmentioning

confidence: 99%

A set of prescribed activities for enhancing requirements engineering in the development of usable e-Government applications

Sánchez

Macías

2017

Requirements Eng

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“…Over time many different metrics have been proposed. Process metrics [41], [42], [43], [44], [45], change metrics [46], [47], [48], [49], semantic metrics [24], [25], [26], [27] and others.…”

Section: B Metrics Prediction Granularity and Approaches To Sdpmentioning

confidence: 99%

Empirical Study: How Issue Classification Influences Software Defect Prediction

et al. 2023

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Software defect prediction aims to identify potentially defective software modules to better allocate limited quality assurance resources. Practitioners often do this by utilizing supervised models trained using historical data. This data is gathered by mining version control and issue tracking systems. Version control commits are linked to issues they address. If the linked issue is classified as a bug report, the change is considered as bug fixing. The problem arises from the fact that issues are often incorrectly classified within issue tracking systems. This introduces noise into the gathered datasets. In this paper, we investigate the influence issue classification has on software defect prediction dataset quality and resulting model performance. To do this, we mine data from 7 popular open-source repositories, create issue classification and software defect prediction datasets for each of them. We investigate issue classification using four different methods; a simple keyword heuristic, an improved keyword heuristic, the FastText model and the RoBERTa model. Our results show that using the RoBERTa model for issue classification produces the best software defect prediction datasets, containing on average 14.3641% of mislabeled instances. SDP models trained on such datasets achieve superior performance, to those trained on SDP datasets created using other issue classification methods, in 65 out of 84 experiments, with 55 of them being statistically relevant. Furthermore, in 17 out of 28 experiments we could not show a statistically relevant performance difference between SDP models trained on RoBERTa derived software defect prediction datasets and those created using manually labeled issues.

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“…Semantic relationships between requirements are discovered manually using similarity and consistency analysis. In the research that we studied, the consistency of requirements is maintained by checking requirements with design‐level specifications or with objective‐level constraints . Finding contradictions between requirements texts is usually ignored in the state‐of‐the‐art analysis the authors performed.…”

Section: Quality Analysis Of Requirementsmentioning

confidence: 99%

Automatic requirements extraction, analysis, and graph representation using an approach derived from computational linguistics

Mokammel¹,

Coatanéa²,

Coatanéa³

et al. 2018

Systems Engineering

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The quality of requirements is fundamental in engineering projects. Requirements are usually expressed partly or totally in a natural language (NL) format and come from different documents.Their qualities are difficult to analyze manually, especially when hundreds of thousands of them have to be considered. The assistance of software tools is becoming a necessity. In this article, the goal was to develop a set of metrics supported by NL processing (NLP) methods supporting different types of analysis of requirements and especially the dependencies between requirements.An NLP approach is used to extract requirements from text; to analyze their quality, links, similarities, and contradictions; and to cluster them automatically. The analysis framework includes different combinations of methods such as cosine similarity, singular value decomposition, and Kmeans clustering. One objective is to assess the possible combinations and their impacts on detections to establish optimal metrics. Three case studies exemplify and support the validation of the work. Graphs are used to represent the automatically clustered requirements, as well as similarities and contradictions. A new contradiction analysis process that includes a rules-based approach is proposed. Finally, the combined results are presented as graphs, which unveil the semantic relationships between requirements. Subsection 4.8 compares the results provided by the tool and the results obtained from experts. The proposed methodology and network presentation not only support the understanding of the semantics of the requirements but also help requirements engineers to review the interconnections and consistency of requirements systems and manage traceability. The approach is valuable during the early phases of projects when requirements are evolving dynamically and rapidly. K E Y W O R D S contradictions analysis, network representation, requirements management, similarity Systems Engineering. 2018;21:555-575. c 2018 Wiley Periodicals, Inc. 555 wileyonlinelibrary.com/journal/sys AUTHORS' BIOGRAPHIES FAISAL MOKAMMEL is a doctoral student at Aalto University and work at Selko Oy developing a commercial version of the requirement extractor and analyser tool developed during his doctoral thesis. ERIC COATANÉA is tenured professor at Tampere University of Technology and was the initiator of the requirement extractor and analyser project. JOONAS COATANÉA is developer at Selko Oy. MOKAMMEL ET AL. 575 VLADISLAV NENCHEV is software developer and formal logic expert at Selko Oy. ERIC BLANCO is professor at INP Grenoble. MATTI PIETOLA is tenured professor at Aalto University. How to cite this article: Mokammel F, Coatanéa E, Coatanéa J, Nenchev V, Blanco E, Pietola M. Automatic requirements extraction, analysis, and graph representation using an approach derived from computational linguistics. Systems Engineering. 2018;21:555-575. https://doi.

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Metrics for measuring the consistencies of requirements with objectives and constraints

Cited by 11 publications

References 13 publications

A set of prescribed activities for enhancing requirements engineering in the development of usable e-Government applications

A set of prescribed activities for enhancing requirements engineering in the development of usable e-Government applications

Empirical Study: How Issue Classification Influences Software Defect Prediction

Automatic requirements extraction, analysis, and graph representation using an approach derived from computational linguistics

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