Detection of Software Usability Deficiencies

Tamir, Dan E.; Komogortsev, Oleg V.; Mueller, Carl J.; Venkata, Divya K. D.; LaKomski, Gregory R.; Jamnagarwala, Arwa. M.

doi:10.1007/978-3-642-21708-1_59

Cited by 4 publications

(2 citation statements)

References 6 publications

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“…Interacting with their GUIs (Tamir et al, 2015), losing control of details, reliant on framework to understand dependencies, hidden encapsulated running code to developer, broken-ability to framework updates (Argon 30 Design, 2015 Computer frameworks would be further developed with potential in crowds. This has created an interesting type of framework which is based on crowdsourcing.…”

Section: Related Workmentioning

confidence: 99%

A Mathematical Framework for Crisis Spatial Crowdsourcing Services

Eivazy

Malek

2018

Preprint

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Abstract. Almost all crises or disasters have vast consequences in both spatial and temporal scale which are difficult to manage because of the size of hazards and their complexities. To conquer the vast size of consequences, it is possible to deploy potential of crowds but there are few developed tools to come over the complexity of required emergency processes.Dividing complex process into atomic crowdsourcing services would be a proper solution to use potential of crowds. We have innovated these services as atomic reply to spatial urgent requests including an informative, activity and confirmative 10 segment. Proper composition of such atomic services in both spatial and temporal components would be able to manage sophisticated crisis fields. Administration of such services requires a robust and operational framework. In this paper we have designed a crisis crowdsourcing mathematical framework which is constructed upon vector space elements and some meaningful eligible operations among them. The framework inherits tensor and differential geometry specifications. Vectors simulate crisis environment main objects in a multidimensional space. Likewise operations coincide possible actions among 15 crisis objects.Proposed Framework introduces tools to compose and arrange atomic crowdsourcing services in optimum mode to conquer complex aiding process. Framework offers a mathematical intelligible documentation method too which is able to record process details as well as objects' status in space. To evaluate our framework we simulate different scenarios in a commercial simulation software and in our proposed framework. Defined scenarios included real field crisis reports, multi-agents 20 interactive challenges for aiding and inquiry research forms for overall evaluation. Comparing results revealed considerable coincidence that could be evaluated as framework assurance. 25

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Section: Related Workmentioning

confidence: 99%

A Mathematical Framework for Crisis Spatial Crowdsourcing Services

Eivazy

Malek

2018

Preprint

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“…Over the years, feature selection has been used to reduce features in diverse fields, for instance,in health care data analysis [32], flash flood hazard assessment [33], and for medical image diagnosis [34], among other applications. It has also been used in the area of software usability, for reduction of usability attributes [8,9,11], to identify problematic usability attributes [35] and to detect usability deficiencies by monitoring the amount of time taken in different tasks by users [36].…”

Section: Introductionmentioning

confidence: 99%

Feature selection algorithm for usability engineering: a nature inspired approach

Jain

Joseph

Saxena

et al. 2021

Complex Intell. Syst.

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Software usability is usually used in reference to the hierarchical software usability model by researchers and is an important aspect of user experience and software quality. Thus, evaluation of software usability is an essential parameter for managing and regulating a software. However, it has been difficult to establish a precise evaluation method for this problem. A large number of usability factors have been suggested by many researchers, each covering a set of different factors to increase the degree of user friendliness of a software. Therefore, the selection of the correct determining features is of paramount importance. This paper proposes an innovative metaheuristic algorithm for the selection of most important features in a hierarchical software model. A hierarchy-based usability model is an exhaustive interpretation of the factors, attributes, and its characteristics in a software at different levels. This paper proposes a modified version of grey wolf optimisation algorithm (GWO) termed as modified grey wolf optimization (MGWO) algorithm. The mechanism of this algorithm is based on the hunting mechanism of wolves in nature. The algorithm chooses a number of features which are then applied to software development life cycle models for finding out the best among them. The outcome of this application is also compared with the conventional grey wolf optimization algorithm (GWO), modified binary bat algorithm (MBBAT), modified whale optimization algorithm (MWOA), and modified moth flame optimization (MMFO). The results show that MGWO surpasses all the other relevant optimizers in terms of accuracy and produces a lesser number of attributes equal to 8 as compared to 9 in MMFO and 12 in MBBAT and 19 in MWOA.

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