Ambiguous software requirement specification detection

Osman, Mohd Hafeez; Zaharin, Mohd Firdaus

doi:10.1145/3195538.3195545

Cited by 25 publications

(12 citation statements)

References 15 publications

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“…The Software Requirements Specification (SRS) serves as the basis of software development, exhibiting influence over all succeeding stages. Accordingly, a high-quality SRS may increase the likelihood of excellent software quality (Osman & Zaharin, 2018). At this point, the author determined the information needs and requirements for constructing the system, as well as the system goals and objectives of the stakeholders to be designed.…”

Section: Requirement Specificationmentioning

confidence: 99%

Synergistic Information Security Design Implementation based on Role-Based Access Control, Information Classification, and AES Cryptographic Encryption

Bumalod,

Velasco

2024

ijitgeb

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Security technology has undergone significant development and research in response to increasing cyber threats. The Intranet Document Management System (IDMS) was created to centralize documents within organizations, ensuring efficiency and streamlining processes. Given the critical nature of document management in organizational workflows, secure and safe management is paramount. This study aims to develop a secure IDMS using Advanced Encryption Standard (AES) encryption, Role-Based Access Control (RBAC), and an Information Classification Model. We also provide a comprehensive overview of the key characteristics and performance metrics of each access control model and cryptographic algorithm, facilitating decision-making for system design and implementation. The system offers high granularity, ease of administration through role assignments with document classification, high flexibility with customized permissions, and scalability with roles and classification. AES is chosen for its high security and fast performance, making it a widely used encryption standard. Keywords: Advanced Encryption Standard (AES), Access Control, Cryptographic Algorithm, Document Management System, Information Classification Received Date: April 2, 2024Revised Date: May 10, 2024Accepted Date: May 14, 2024

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Section: Requirement Specificationmentioning

confidence: 99%

Synergistic Information Security Design Implementation based on Role-Based Access Control, Information Classification, and AES Cryptographic Encryption

Bumalod,

Velasco

2024

ijitgeb

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“…Recently, Sabriye et al [8] proposed a framework for detecting ambiguity in SRS based on NLP, but this research is still at an early stage. The framework consists of three components: preprocessing, processing, and postprocessing, using an ambiguity detector to check the syntactic ambiguity of any sentence in the Stanford POS tagger; in 2018, Osman et al [9] proposed an automated detection method that combines text mining and machine learning to detect ambiguous requirements specifications. However, the shortcomings of NLP technology are also obvious, such as the detected defect type is relatively single, and the accuracy rate is not high (misjudgment).…”

Section: Related Research 21 Detection Of Defectsmentioning

confidence: 99%

A Defect Detection Method for the Primary Stage of Software Development

Zhi¹,

Pu²,

Ren³

et al. 2023

Computers, Materials &Amp; Continua

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In the early stage of software development, a software requirements specification (SRS) is essential, and whether the requirements are clear and explicit is the key. However, due to various reasons, there may be a large number of misunderstandings. To generate high-quality software requirements specifications, numerous researchers have developed a variety of ways to improve the quality of SRS. In this paper, we propose a questions extraction method based on SRS elements decomposition, which evaluates the quality of SRS in the form of numerical indicators. The proposed method not only evaluates the quality of SRSs but also helps in the detection of defects, especially the description problem and omission defects in SRSs. To verify the effectiveness of the proposed method, we conducted a controlled experiment to compare the ability of checklist-based review (CBR) and the proposed method in the SRS review. The CBR is a classic method of reviewing SRS defects. After a lot of practice and improvement for a long time, CBR has excellent review ability in improving the quality of software requirements specifications. The experimental results with 40 graduate students majoring in software engineering confirmed the effectiveness and advantages of the proposed method. However, the shortcomings and deficiencies of the proposed method are also observed through the experiment. Furthermore, the proposed method has been tried out by engineers with practical work experience in software development industry and received good feedback.

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“…Data imbalance means that the number of instances of minority class are much lower than those of the majority class. Because of the unbalanced distribution of data, classifiers are misled while learning the minority class, resulting in biased and erroneous findings [3]. A good software requirements categorization model will be one that has been trained on a similar distribution of functional and non-functional requirement classes.…”

Section: Introductionmentioning

confidence: 99%

Software Requirements Classification using Deep-learning Approach with Various Hidden Layers

Vijayvargiya¹,

Kumar²,

Murthy³

et al. 2022

Annals of Computer Science and Information Systems

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Software requirement classification is becoming increasingly crucial for the industry to keep up with the demand of growing project sizes. Based on client feedback or demand, software requirement classification is critical in segregating user needs into functional and quality requirements. However, because there are numerous machine learning (ML) and deep-learning (DL) models that require parameter tuning, the use of ML to facilitate decision-making across the software engineering pipeline is not well understood. Five distinct word embedding techniques were applied to the functional and quality software requirements in this study. The imbalanced classes in the dataset are balanced using Synthetic Minority Oversampling technique (SMOTE). Then, to reduce duplicate and unnecessary features, feature selection and dimensionality reduction techniques are used. Dimensionality reduction is accomplished with Principal Component Analysis (PCA), while feature selection is accomplished with the Rank-Sum Test (RST). For binary categorization into functional and non-functional needs, the generated vectors are provided as inputs to eight distinct Deep Learning classifiers. The findings of the research show that using a combination of word embedding and feature selection techniques in conjunction with various classifiers can accurately classify functional and quality software requirements.

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Ambiguous software requirement specification detection

Cited by 25 publications

References 15 publications

Synergistic Information Security Design Implementation based on Role-Based Access Control, Information Classification, and AES Cryptographic Encryption

Synergistic Information Security Design Implementation based on Role-Based Access Control, Information Classification, and AES Cryptographic Encryption

A Defect Detection Method for the Primary Stage of Software Development

Software Requirements Classification using Deep-learning Approach with Various Hidden Layers

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