Factoring requirement dependencies in software requirement selection using graphs and integer programming

Mougouei, Davoud

doi:10.1145/2970276.2975936

Cited by 17 publications

(29 citation statements)

References 30 publications

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“…[43][44][45]), requirements prioritization techniques [46], and studies on managing dependencies between requirements/features (e.g. [47][48]). This body of knowledge has often included an inherent dimension of importance, based on complex multi-criteria, which resembles value.…”

Section: Value-based Feature Selectionmentioning

confidence: 99%

A Theory of Value for Value-Based Feature Selection in Software Engineering

Rodríguez

Urquhart

Mendes

2022

IIEEE Trans. Software Eng.

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Value-Based Software Engineering stresses the role of value in software related decisions. In the context of feature selection, software features judged to provide higher value take priority in the development process. This paper focuses on what value means when selecting software features. Using grounded theory, we conducted and analyzed semi-structured interviews with 21 key stakeholders (decision-makers) from three software/software-intensive companies, within a context where valuebased decision-making was already established. Our analysis led to the building of a theory of value for value-based feature selection that identifies the nature of value propositions considered by key stakeholders when selecting software features (i.e. decision-making criteria for deciding upon software features, as suggested by Boehm (2003)). We found that some value propositions were common to all three company cases (core value propositions), whereas others were dependent upon the context in which a company operates, and the characteristics of the product under development (specific value propositions). Moreover, value propositions vary according to the stakeholder group and the type of feature being assessed. Our study provides significant insight into value in the context of feature selection, and generates new concepts around value-based feature selection such as new value propositions.

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Section: Value-based Feature Selectionmentioning

confidence: 99%

A Theory of Value for Value-Based Feature Selection in Software Engineering

Rodríguez

Urquhart

Mendes

2022

IIEEE Trans. Software Eng.

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“…Value dependencies are fuzzy relations (Carlshamre et al, 2001) with varying strengths (e.g. weak, moderate, strong) and qualities (positive or negative) which are imprecise, and hard to specify (Carlshamre et al, 2001;Mougouei, 2016). Requirement selection methods hence, should consider qualities and strengths of explicit and implicit value dependencies among software requirements.…”

Section: Background and Related Workmentioning

confidence: 99%

Dependency-aware release planning for software projects using fuzzy graphs and integer programming

Mougouei

Powers

2019

IFS

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Software requirements selection aims to find an optimal subset of the requirements with the highest value while respecting the project constraints. But the value of a requirement may depend on the presence or absence of other requirements in the optimal subset. Such Value Dependencies, however, are imprecise and hard to capture. In this paper, we propose a method based on integer programming and fuzzy graphs to account for value dependencies and their imprecision in software requirements selection. The proposed method, referred to as Dependency-Aware Software Requirements Selection (DARS), is comprised of three components: (i) an automated technique for the identification of value dependencies from user preferences, (ii) a modeling technique based on fuzzy graphs that allows for capturing the imprecision of value dependencies, and (iii) an Integer Linear Programming (ILP) model that takes into account user preferences and value dependencies identified from those preferences to reduce the risk of value loss in software projects. Our work is verified by studying a realworld software project. The results show that our proposed method reduces the value loss in software projects and is scalable to large requirement sets.

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“…[29], [30], [31]), requirements prioritization techniques [32] and studies on managing dependencies between requirements/features (e.g. [33], [34]). Although only a few prioritization techniques have explicitly considered value [32], this body of knowledge has not focused only on cost, effort, or schedule but has often included an inherent dimension of importance, based on complex multi-criteria, which resembles value [32].…”

Section: Introductionmentioning

confidence: 99%

Key Stakeholders’ Value Propositions for Feature Selection in Software-Intensive Products: An Industrial Case Study

Rodríguez

Mendes

Turhan

2020

IIEEE Trans. Software Eng.

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Numerous software companies are adopting value-based decision making. However, what does value mean for key stakeholders making decisions? How do different stakeholder groups understand value? Without an explicit understanding of what value means, decisions are subject to ambiguity and vagueness, which are likely to bias them. This case study provides an in-depth analysis of key stakeholders' value propositions when selecting features for a large telecommunications company's software-intensive product. Stakeholders' value propositions were elicited via interviews, which were analyzed using Grounded Theory coding techniques (open and selective coding). Thirty-six value propositions were identified and classified into six dimensions: customer value, market competitiveness, economic value/profitability, cost efficiency, technology & architecture, and company strategy. Our results show that although propositions in the customer value dimension were those mentioned the most, the concept of value for feature selection encompasses a wide range of value propositions. Moreover, stakeholder groups focused on different and complementary value dimensions, calling to the importance of involving all key stakeholders in the decision making process. Although our results are particularly relevant to companies similar to the one described herein, they aim to generate a learning process on value-based feature selection for practitioners and researchers in general.

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Factoring requirement dependencies in software requirement selection using graphs and integer programming

Cited by 17 publications

References 30 publications

A Theory of Value for Value-Based Feature Selection in Software Engineering

A Theory of Value for Value-Based Feature Selection in Software Engineering

Dependency-aware release planning for software projects using fuzzy graphs and integer programming

Key Stakeholders’ Value Propositions for Feature Selection in Software-Intensive Products: An Industrial Case Study

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