Detecting and classifying patterns of requirements clarifications

Knauss, Eric; Damian, Daniela; Poo-Caamaño, Germán; Cleland‐Huang, Jane

doi:10.1109/re.2012.6345811

Cited by 41 publications

(27 citation statements)

References 13 publications

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“…Naïve Bayes classifier is used in several studies [12], [13] for automatic classification of requirements. Therefore, we included Naïve Bayes in our study to be comparable with other classifiers.…”

Section: Related Workmentioning

confidence: 99%

What Works Better? A Study of Classifying Requirements

Abad¹,

Karras

Ghazi

et al. 2017

2017 IEEE 25th International Requirements Engineering Conference (RE)

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Abstract-Classifying requirements into functional requirements (FR) and non-functional ones (NFR) is an important task in requirements engineering. However, automated classification of requirements written in natural language is not straightforward, due to the variability of natural language and the absence of a controlled vocabulary. This paper investigates how automated classification of requirements into FR and NFR can be improved and how well several machine learning approaches work in this context. We contribute an approach for preprocessing requirements that standardizes and normalizes requirements before applying classification algorithms. Further, we report on how well several existing machine learning methods perform for automated classification of NFRs into sub-categories such as usability, availability, or performance. Our study is performed on 625 requirements provided by the OpenScience tera-PROMISE repository. We found that our preprocessing improved the performance of an existing classification method. We further found significant differences in the performance of approaches such as Latent Dirichlet Allocation, Biterm Topic Modeling, or Naïve Bayes for the sub-classification of NFRs.

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Section: Related Workmentioning

confidence: 99%

What Works Better? A Study of Classifying Requirements

Abad¹,

Karras

Ghazi

et al. 2017

2017 IEEE 25th International Requirements Engineering Conference (RE)

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“…Previous research on communication and coordination in software ecosystems has focused in a temporal analysis of information flows [37], and then obtained a structural map about flows between actors [38]. To our knowledge, the requirements and challenges that release managers face in software ecosystems have not been explored, and little is known about how FOSS ecosystems conduct release management.…”

Section: Introductionmentioning

confidence: 99%

Herding cats in a FOSS ecosystem: a tale of communication and coordination for release management

Poo-Caamaño

Knauss

Singer

et al. 2017

J Internet Serv Appl

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Release management in large-scale software development projects requires significant communication and coordination. It is particularly challenging in Free and Open Source Software (FOSS) ecosystems, in which hundreds of loosely connected developers and their projects are coordinated to release software to a schedule. To better understand this process and its challenges, we analyzed over two and half years of communication in the GNOME ecosystem and studied developers' interactions. Through a case study, we cataloged communication channels, determined the main channel from which we categorized high level communication and coordination activities spanning five releases, and triangulated our results by interviewing ten key developers. We found that a release schedule, influence (instead of direct control), and diversity are the main factors that positively impact the release process in the GNOME ecosystem. We report a set of lessons learned that encapsulates our understanding of how the Release Management process function in a FOSS ecosystem, we learned that: (1) ensure that the release team follows the main communication channels used by developers, (2) provide a common place for coordination for an ecosystem, (3) consider including both good technical and social skills in a release team, (4) aim for a diverse release team, (5) based on lack of power, lobbying and consensus based management must be followed, (6) help the release team in the coordination process with a well defined schedule, and (7) release team work is different from regular software work. Our results can help organizations build better large-scale teams and show that research focused on individual projects might miss important parts of the picture.

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“…This is known as just-in-time RE [3,4] which encompasses two key aspects: lightweight representation (defining requirements at a convenient level of detail) and evolutionary refinement (clarifying them when needed). Projects adopting such practice include both open source systems like Mozilla [4] and proprietary ones such as IBM's Rational Team Concert [5].…”

Section: Introductionmentioning

confidence: 99%

“…One challenge refers to the stagnation of the requirements that developers have already started to implement. A recent study investigated 157 user stories and showed that about 10% failed to be realized even after certain coding efforts were made [5]. Another major issue concerns the hindrance to the fulfillment of future requirements.…”

Section: Introductionmentioning

confidence: 99%

Traceability-enabled refactoring for managing just-in-time requirements

Niu

Bhowmik

Liu

et al. 2014

2014 IEEE 22nd International Requirements Engineering Conference (RE)

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Abstract-Just-in-time requirements management, characterized by lightweight representation and continuous refinement of requirements, fits many iterative and incremental development projects. Being lightweight and flexible, however, can cause wasteful and procrastinated implementation, leaving certain stakeholder goals not satisfied. This paper proposes traceabilityenabled refactoring aimed at fulfilling more requirements fully. We make a novel use of requirements traceability to accurately locate where the software should be refactored, and develop a new scheme to precisely determine what refactorings should be applied to the identified places. Our approach is evaluated through an industrial study. The results show that our approach recommends refactorings more appropriately than a contemporary recommender.

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Detecting and classifying patterns of requirements clarifications

Cited by 41 publications

References 13 publications

What Works Better? A Study of Classifying Requirements

What Works Better? A Study of Classifying Requirements

Herding cats in a FOSS ecosystem: a tale of communication and coordination for release management

Traceability-enabled refactoring for managing just-in-time requirements

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