A Software Requirements Specification Framework for Objective Pattern Recognition: A Set-Theoretic Classification Approach

Ghazarian, Arbi; Tehrani, Mehdi Sagheb; Ghazarian, Arin

doi:10.1109/iceccs.2011.28

Cited by 4 publications

(7 citation statements)

References 5 publications

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“…Sommerville, in [1], classifies FRs into two levels: user requirements and system requirements. In [23], Ghazarian et al classified manually FRs into only five classes. These classes include input data, output data, data persistence, application rules and actions.…”

Section: Functional Requirements' Classificationmentioning

confidence: 99%

Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering

et al. 2018

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Software applications have become a fundamental part in the daily work of modern society as they meet different needs of users in different domains. Such needs are known as software requirements (SRs) which are separated into functional (software services) and non-functional (quality attributes). The first step of every software development project is SR elicitation. This step is a challenge task for developers as they need to understand and analyze SRs manually. For example, the collected functional SRs need to be categorized into different clusters to break-down the project into a set of sub-projects with related SRs and devote each sub-project to a separate development team. However, functional SRs clustering has never been considered in the literature. Therefore, in this paper, we propose an approach to automatically cluster functional requirements based on semantic measure. An empirical evaluation is conducted using four open-access software projects to evaluate our proposal. The experimental results demonstrate that the proposed approach identifies semantic clusters according to well-known used measures in the subject.

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Section: Functional Requirements' Classificationmentioning

confidence: 99%

Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering

et al. 2018

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“…From this point of view, the second column in Table II shows the number of high level user requirements, while the third column represents the count of detailed system requirements encompassed in those high-level user requirements within each system. More details about the concept of atomic requirements can be found in [9], [4], and [6]. The atomicity property of functional software requirements makes their counts a meaningful metric because all of the requirements have the same level of granularity.…”

Section: B Multiple-case Study Process and Data Collectionmentioning

confidence: 99%

Section: B Multiple-case Study Process and Data Collectionmentioning

confidence: 99%

“…We used the functional requirements taxonomy presented in [4] as a starting point and expanded or modified it as necessary. In [4], functional requirements are categorized into 5 classes, including input data, application rules, output data, data persistence, and actions. We further divided the application rules class of functional requirements into two more specific classes, namely the business logic requirements and data validation requirements.…”

Section: B Multiple-case Study Process and Data Collectionmentioning

confidence: 99%

“…We used the classes of functional requirements described in [4] as a starting point for our classification process and extended it to cover all of the atomic requirements observed in the 15 software projects studied. This process answered our first research question regarding the types of atomic functional requirements that make up the requirements space in the studied domain.…”

Section: Functional Requirements Classesmentioning

confidence: 99%

See 2 more Smart Citations

Characterization of functional software requirements space: The law of requirements taxonomic growth

Ghazarian

2012

2012 20th IEEE International Requirements Engineering Conference (RE)

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This paper reports on a large-scale empirical multiple-case study that aimed to characterize the requirements space in the domain of web-based Enterprise Systems (ES). Results from this study, among others, showed that, on the average, about 85% of all the software functionalities in the studied domain are specified using a small core set of five requirements classes even though the results of the study hint at a larger set of nine requirements classes that should be covered. The study also uncovered a law describing the growth pattern of the emerging requirements classes in software domains. According to this law, the emergence of the classes in a requirements taxonomic scheme for a particular domain, independent of the order in which specifications of requirements in that domain are analyzed, includes a rapid initial growth phase, where the majority of the requirements classes are identified, followed by a rapid slow-down phase with periods of no growth (i.e., the stabilization phase).

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Work in progress: Transitioning from novice to expert software engineers through design patterns: Is it really working?

Ghazarian

2012

2012 Frontiers in Education Conference Proceedings

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A Software Requirements Specification Framework for Objective Pattern Recognition: A Set-Theoretic Classification Approach

Cited by 4 publications

References 5 publications

Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering

Semantic Clustering of Functional Requirements Using Agglomerative Hierarchical Clustering

Characterization of functional software requirements space: The law of requirements taxonomic growth

Work in progress: Transitioning from novice to expert software engineers through design patterns: Is it really working?

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