What Works Better? A Study of Classifying Requirements

Abad, Zahra Shakeri Hossein; Karras, Oliver; Ghazi, Parisa; Glinz, Martin; Ruhe, Guenther; Schneider, Kurt

doi:10.1109/re.2017.36

Cited by 76 publications

(63 citation statements)

References 17 publications

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“…This information together can support a better choice among the tools for requirement classification process. The outcomes of our experiments have also confirmed the results of former researches [9,7,8].…”

Section: Introductionsupporting

confidence: 89%

“…Some researchers investigated the use of ontologies which have been created on standards' basis [5,6]. Some researchers like Lu Megmen et al [7] or Abad et al [8] utilized supervised learning methods, others utilized semi-supervised learning techniques such as Expectation Maximization strategy [9]. Abad et al applied also clustering techniques to identify the best method for processing requirements sentences.…”

Section: Introductionmentioning

confidence: 99%

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Study of Various Classifiers for Identification and Classification of Non-functional Requirements

Tóth

Vidács

2018

Computational Science and Its Applications – ICCSA 2018

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Identification of non-functional requirements in an early phase of software development process is crucial for creating a proper software design. These requirements are often neglected or given in too general forms. However, interviews and other sources of requirements often include important references also to non-functional requirements which are embedded in a bigger textual context. The non-functional requirements have to be extracted from these contexts and should be presented in a formulated and standardized way to support software design. The set of requirements extracted from their textual context have to be classified to formalize them. This task is to be accomplished manually but it can be very demanding and error-prone. Several attempts have been made to support identification and classification tasks using supervised and semisupervised learning processes. These efforts have achieved remarkable results. Researchers were mainly focused on the performance of classification measured by precision and recall. However, creating a tool which can support business analysts with their requirements elicitation tasks, execution time is also an important factor which has to be taken into account. Knowing the performance and the results of benchmarks can help business analysts to choose a proper method for their classification tasks. Our study presented in this article focuses on both the comparison of performances of the classification processes and their execution time to support the choice among the methods.

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Section: Introductionsupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Study of Various Classifiers for Identification and Classification of Non-functional Requirements

Tóth

Vidács

2018

Computational Science and Its Applications – ICCSA 2018

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“…However, the filtering method we described in Section IV-A helps reduce the complexity of large-scale datasets. Further, we aim to apply classification techniques [20] on RE artifacts (e.g. requirements specification) to involve the requirements' type (i.e.…”

Section: Discussion and Research Implicationsmentioning

confidence: 99%

A Visual Narrative Path from Switching to Resuming a Requirements Engineering Task

Abad

Shymka²,

Le³

et al. 2017

2017 IEEE 25th International Requirements Engineering Conference (RE)

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Abstract-Requirements Engineering (RE) is closely tied to other development activities and is at the heart and foundation of every software development process. This makes RE the most data and communication intensive activity compared to other development tasks. The highly demanding communication makes task switching and interruptions inevitable in RE activities. While task switching often allows us to perform tasks effectively, it imposes a cognitive load and can be detrimental to the primary task, particularly in complex tasks as the ones typical for RE activities. Visualization mechanisms enhanced with analytical methods and interaction techniques help software developers obtain a better cognitive understanding of the complexity of RE decisions, leading to timelier and higher quality decisions. In this paper, we propose to apply interactive visual analytics techniques for managing requirements decisions from various perspectives, including stakeholders communication, RE task switching, and interruptions. We propose a new layered visualization framework that supports the analytical reasoning process of task switching. This framework consists of both data analysis and visualization layers. The visual layers offer interactive knowledge visualization components for managing task interruption decisions at different stages of an interruption (i.e. before, during, and after). The analytical layers provide narrative knowledge about the consequences of task switching decisions and help requirements engineers to recall their reasoning process and decisions upon resuming a task. Moreover, we surveyed 53 software developers to test our visual prototype and to explore more required features for the visual and analytical layers of our framework.

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“…We attempted to mitigate this threat by iteratively revising the list of stop-words. [19,743] 3 Availability, Reliability, Usability Reliability, Privacy, Resource Usage Better bluetooth connectivity with external devices, Information and recommendation on nutritional food * Total = 70, 592 reviews A recent study by Shakeri H. A. et al [26] shows that LDA performs poor for extracting topics from short requirements documents, as the one typical for mobile app reviews. This might question the validity of the results of RQ2.…”

Section: E Threats To Validitymentioning

confidence: 99%

Learn More, Pay Less! Lessons Learned from Applying the Wizard-of-Oz Technique for Exploring Mobile App Requirements

Abad¹,

Sims²,

Cheema³

et al. 2017

2017 IEEE 25th International Requirements Engineering Conference Workshops (REW)

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Abstract-Mobile apps have exploded in popularity, encouraging developers to provide content to the massive user base of the main app stores. Although there exist automated techniques that can classify user comments into various topics with high levels of precision, recent studies have shown that the top apps in the app stores do not have customer ratings that directly correlate with the app's success. This implies that no single requirements elicitation technique can cover the full depth required to produce a successful product and that applying alternative requirements gathering techniques can lead to success when these two are combined. Since user involvement has been found to be the most impactful contribution to project success, in this paper we will explore how the Wizard-of-Oz (WOz) technique and user reviews available in Google Play, can be integrated to produce a product that meets the demand of more stakeholders than either method alone. To compare the role of early interactive requirements specification and app reviews, we conducted two studies: (i) a case study analysis on 13 mobile app development teams who used very early stages Requirements Engineering (RE) by applying WOz, and (ii) a study analyzing 40 (70, 592 reviews) similar mobile apps on Google Play. The results of both studies show that while each of WOz and app review analysis techniques can be applied to capture specific types of requirements, an integrated process including both methods would eliminate the communication gap between users and developers at early stages of the development process and mitigates the risk of requirements change in later stages.

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What Works Better? A Study of Classifying Requirements

Cited by 76 publications

References 17 publications

Study of Various Classifiers for Identification and Classification of Non-functional Requirements

Study of Various Classifiers for Identification and Classification of Non-functional Requirements

A Visual Narrative Path from Switching to Resuming a Requirements Engineering Task

Learn More, Pay Less! Lessons Learned from Applying the Wizard-of-Oz Technique for Exploring Mobile App Requirements

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