An empirical study on decision making for quality requirements

Olsson, Thomas; Wnuk, Krzystof; Gorschek, Tony

doi:10.1016/j.jss.2018.12.002

Cited by 19 publications

(15 citation statements)

References 57 publications

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“…Two studies find that architects address quality requirements the same way as other requirements [33,84], also confirmed in other surveys [83]. However, there are also research studies indicating a varying prevalence and explicitness than other requirements [14,41,49,80,90]. We interpret the current state of evidence to be unclear on the handling of quality requirements.…”

Section: Quality Requirements and Other Requirementssupporting

confidence: 52%

A systematic literature review of empirical research on quality requirements

2022

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Quality requirements deal with how well a product should perform the intended functionality, such as start-up time and learnability. Researchers argue they are important and at the same time studies indicate there are deficiencies in practice. Our goal is to review the state of evidence for quality requirements. We want to understand the empirical research on quality requirements topics as well as evaluations of quality requirements solutions. We used a hybrid method for our systematic literature review. We defined a start set based on two literature reviews combined with a keyword-based search from selected publication venues. We snowballed based on the start set. We screened 530 papers and included 84 papers in our review. Case study method is the most common (43), followed by surveys (15) and tests (13). We found no replication studies. The two most commonly studied themes are (1) differentiating characteristics of quality requirements compared to other types of requirements, (2) the importance and prevalence of quality requirements. Quality models, QUPER, and the NFR method are evaluated in several studies, with positive indications. Goal modeling is the only modeling approach evaluated. However, all studies are small scale and long-term costs and impact are not studied. We conclude that more research is needed as empirical research on quality requirements is not increasing at the same rate as software engineering research in general. We see a gap between research and practice. The solutions proposed are usually evaluated in an academic context and surveys on quality requirements in industry indicate unsystematic handling of quality requirements.

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Section: Quality Requirements and Other Requirementssupporting

confidence: 52%

A systematic literature review of empirical research on quality requirements

2022

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“…Therefore, the requirement management process becomes more complicated during component specification and prioritization activities. In CBSD, proper and correct integration of components play a significant role, whereas, neglecting components, improper integration, and wrong interaction behavior of components, particularly in complex and configurable systems results in system failure [2,14,18,[20][21][22][23][24][25][26][27][28].…”

Section: Cybermentioning

confidence: 99%

Towards Aspect Based Components Integration Framework for Cyber-Physical System

Ali¹,

Hafeez²,

Bilal³

et al. 2022

Computers, Materials &Amp; Continua

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Cyber-Physical Systems (CPS) comprise interactive computation, networking, and physical processes. The integrative environment of CPS enables the smart systems to be aware of the surrounding physical world. Smart systems, such as smart health care systems, smart homes, smart transportation, and smart cities, are made up of complex and dynamic CPS. The components integration development approach should be based on the divide and conquer theory. This way multiple interactive components can reduce the development complexity in CPS. As reusability enhances efficiency and consistency in CPS, encapsulation of component functionalities and a well-designed user interface is vital for the better end-user's Quality of Experience (QoE). Thus, incorrect interaction of interfaces in the cyber-physical system causes system failures. Usually, interface failures occur due to false, and ambiguous requirements analysis and specification. Therefore, to resolve this issue semantic analysis is required for different stakeholders' viewpoint analysis during requirement specification and components analysis. This work proposes a framework to improve the CPS component integration process, starting from requirement specification to prioritization of components for configurable. For semantic analysis and assessing the reusability of specifications, the framework uses text mining and case-based reasoning techniques. The framework has been tested experimentally, and the results show a significant reduction in ambiguity, redundancy, and irrelevancy, as well as increasing accuracy of interface interactions, component selection, and higher user satisfaction.

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“…The study by Borg et al 28 highlighted the importance of considering decision context and thus tailor decision-making methods to specific needs. Furthermore, the research has been focused on developing and proposing solutions, such as processes (e.g., Badampudi et al 32 and Alégroth et al 33 ), a taxonomy (e.g., Papatheocharous et al 21 ), methods, models and tools (e.g., Axelsson et al, 39 Sentilles et al, 36 Papatheocharous et al, 46 and Cicchetti et al 38 ), as well as their empirical evaluation (e.g., Olsson et al 47 ). In addition to the three studies described above (cf.…”

Section: Introductionmentioning

confidence: 99%

Towards evidence‐based decision‐making for identification and usage of assets in composite software: A research roadmap

Wohlin

Papatheocharous

Carlson

et al. 2021

J Software Evolu Process

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Software engineering is decision intensive. Evidence-based software engineering is suggested for decision-making concerning the use of methods and technologies when developing software. Software development often includes the reuse of software assets, for example, open-source components. Which components to use have implications on the quality of the software (e.g., maintainability). Thus, research is needed to support decision-making for composite software. This paper presents a roadmap for research required to support evidence-based decision-making for choosing and integrating assets in composite software systems. The roadmap is developed as an output from a 5-year project in the area, including researchers from three different organizations. The roadmap is developed in an iterative process and is based on (1) systematic literature reviews of the area; (2) investigations of the state of practice, including a case survey and a survey; and (3) development and evaluation of solutions for asset identification and selection. The research activities resulted in identifying 11 areas in need of research. The areas are grouped into two categories: areas enabling evidence-based decision-making and those related to supporting the decision-making. The roadmap outlines research needs in these 11 areas. The research challenges and research directions presented in this roadmap are key areas for further research to support evidence-based decision-making for composite software.

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An empirical study on decision making for quality requirements

Cited by 19 publications

References 57 publications

A systematic literature review of empirical research on quality requirements

A systematic literature review of empirical research on quality requirements

Towards Aspect Based Components Integration Framework for Cyber-Physical System

Towards evidence‐based decision‐making for identification and usage of assets in composite software: A research roadmap

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