Supporting Domain Analysis through Mining and Recommending Features from Online Product Listings

Hariri, Negar; Castro-Herrera, Carlos; Mirakhorli, Mehdi; Cleland‐Huang, Jane; Mobasher, Bamshad

doi:10.1109/tse.2013.39

Cited by 85 publications

(59 citation statements)

References 35 publications

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“…These approaches include strategies to make decisions: when to mine, which assets to mine, and whom to involve. Others have developed reengineering approaches by analyzing non-code artifacts, such as product comparisons [20], [23]. In contrast to techniques using non-code and domain information, we extract technical constraints from code with #IFDEF variability.…”

Section: Related Workmentioning

confidence: 99%

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Nadi

Berger

Kästner

et al. 2015

IIEEE Trans. Software Eng.

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Abstract-Highly configurable systems allow users to tailor software to specific needs. Valid combinations of configuration options are often restricted by intricate constraints. Describing options and constraints in a variability model allows reasoning about the supported configurations. To automate creating and verifying such models, we need to identify the origin of such constraints. We propose a static analysis approach, based on two rules, to extract configuration constraints from code. We apply it on four highly configurable systems to evaluate the accuracy of our approach and to determine which constraints are recoverable from the code. We find that our approach is highly accurate (93 % and 77 % respectively) and that we can recover 28 % of existing constraints. We complement our approach with a qualitative study to identify constraint sources, triangulating results from our automatic extraction, manual inspections, and interviews with 27 developers. We find that, apart from low-level implementation dependencies, configuration constraints enforce correct runtime behavior, improve users' configuration experience, and prevent corner cases. While the majority of constraints is extractable from code, our results indicate that creating a complete model requires further substantial domain knowledge and testing. Our results aim at supporting researchers and practitioners working on variability model engineering, evolution, and verification techniques.

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Section: Related Workmentioning

confidence: 99%

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Nadi

Berger

Kästner

et al. 2015

IIEEE Trans. Software Eng.

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“…These patterns would serve to make explicit the different purposes that the user has when manipulating the software product, better motivating and justifying a division. As for the automation of the division itself, we envision future research on techniques to extract and isolating features in separated applications [19,23,32], going beyond the simple synthesis of feature models [7,12,39,44]. Similarly there is a large amount of approaches to locate concerns, to mine aspects or to automate the refactoring of applications in a more modular way [2,13,16,25,38].…”

Section: Perspectivesmentioning

confidence: 99%

Software Unbundling: Challenges and Perspectives

Filho

Acher²,

Barais³

2016

Lecture Notes in Computer Science

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Unbundling is a phenomenon that consists of dividing an existing software artifact into smaller ones. It can happen for different reasons, one of them is the fact that applications tend to grow in functionalities and sometimes this can negatively influence the user experience. For example, mobile applications from well-known companies are being divided into simpler and more focused new ones. Despite its current importance, little is known or studied about unbundling or about how it relates to existing software engineering approaches, such as modularization. Consequently, recent cases point out that it has been performed unsystematically and arbitrarily. In this article, our main goal is to present this novel and relevant concept and its underlying challenges in the light of software engineering, also exemplifying it with recent cases. We relate unbundling to standard software modularization, presenting the new motivations behind it, the resulting problems, and drawing perspectives for future support in the area.

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“…It is then immediate to identify recurrent features of a domain, to understand the specific characteristics of a given product, or to locate the features supported and unsupported by some products. PCMs are also an interesting potential step stone for further analysis such as: (1) formalization and generation of other domain models (e.g., feature models [10,7,11,12,13]), (2) feature recommendation [6], (3) automatic reasoning (e.g., multi-objective optimizations) [14], (4) derivation of automatic comparators and/or configurators [9].…”

Section: Introductionmentioning

confidence: 99%

“…Numerous techniques have been developed to mine variability [10,15,16] and support domain analysis [17,18,19,20,7,6,3,21,22,23], but none of them address the problem of structuring the information in a PCM.…”

Section: Introductionmentioning

confidence: 99%

Automated extraction of product comparison matrices from informal product descriptions

Nasr

Bécan

Acher

et al. 2017

Journal of Systems and Software

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Domain analysts, product managers, or customers aim to capture the important features and differences among a set of related products. A case-by-case reviewing of each product description is a laborious and time-consuming task that fails to deliver a condense view of a family of product.In this article, we investigate the use of automated techniques for synthesizing a product comparison matrix (PCM) from a set of product descriptions written in natural language. We describe a tool-supported process, based on term recognition, information extraction, clustering, and similarities, capable of identifying and organizing features and values in a PCM -despite the informality and absence of structure in the textual descriptions of products.We evaluate our proposal against numerous categories of products mined from BestBuy. Our empirical results show that the synthesized PCMs exhibit numerous quantitative, comparable information that can potentially complement or even refine technical descriptions of products. The user study shows that our automatic approach is capable of extracting a significant portion of correct features and correct values. This approach has been implemented in MatrixMiner a web environment with an interactive support for automatically synthesizing PCMs from informal product descriptions. MatrixMiner also maintains traceability with the original descriptions and the technical specifications for further refinement or maintenance by users.

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Supporting Domain Analysis through Mining and Recommending Features from Online Product Listings

Cited by 85 publications

References 35 publications

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Where Do Configuration Constraints Stem From? An Extraction Approach and an Empirical Study

Software Unbundling: Challenges and Perspectives

Automated extraction of product comparison matrices from informal product descriptions

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