A Multicriteria Approach to Support Task Allocation in Projects of Distributed Software Development

Abstract

Organizations are increasingly investing in Distributed Software Development (DSD) over the years. A typical decision-making problem in the distributed scenario consists of deciding which team should be allocated each task. That decision takes into account a relative degree of subjectivity. That setting is suitable for applying Verbal Decision Analysis (VDA). This paper introduces an approach to support the allocation of tasks to distributed units in DSD projects, structured on the hybridisation of methods of Verbal Decision Analysis for classification and rank ordering applied to influencing factors and executing units. Firstly, a review of the literature was conducted aiming to identify the approaches to support the allocation of tasks in DSD contexts. Then, an approach was developed by applying VDA-based methods for classification and ordering. Bibliographic research and the application of surveys with professionals allowed identifying and characterising the main elements that influence task assignment in DSD projects. Afterwards, experiences were carried out in five real-world companies. In the end, the proposed approach has been submitted to the evaluation by the professionals of the participating companies and by some project management experts. The proposed approach comprises a workflow containing responsible actors and descriptions of the activities. Automated tools are also employed in automating the implementation of the approach. After applying the approach in five companies, task assignment recommendations are presented in groups for each company, according to the task type, i.e., requirements, architecture, coding, and testing, ranging from the most to the least preferable office. Results of the experiences and evaluations held during this work present evidence that the proposed approach is flexible, adaptable, and easy to understand and to use. Moreover, it helps to reduce decision subjectivity and to think of new aspects, supporting the task allocation process in DSD.

Crowdsourcing usage, task assignment methods, and crowdsourcing platforms: A systematic literature review

“…Simão Filho et al 17 Task allocation in distributed software development An approach has been presented for allocation of various tasks in distributed software development. The approach is developed by applying verbal decision analysis methods for the purpose of ordering and classification.…”

“…15 Crowdsourcing applications to software engineering include software requirements, designing, coding, testing, verification, evolution, and software maintenance. 1,17 Most of the companies leverage crowdsourcing in order to decrease the cost and the time to the market for the production of software's. 18 The scope of the software development has been greatly expand by the crowdsourcing platforms, which greatly enhances the software solutions.…”

“…19 The details of some of the papers are given in Table 11. 20 Task recommendation in crowdsourcing systems 0.5 0 1 1 2.5 Mao et al 40 Pricing CSD tasks 0.5 1 1 1 3.5 Stol and Fitzgerald 41 CSD case study 1 0 0.5 0.5 2 Cheung et al 42 Distributed time-sensitive task selection 0.5 0 1 0.5 2 Saremi and Yang 18 Simulation of workers and task completion 0 1 0 1 2 Maalej and Ellmann 7 On the similarity of task contexts 0 1 0 0 1 Roy et al 24 Task assignment optimization 0.5 0 1 1 2.5 Qiu et al 26 Crowdsourcing tasks accuracy through behavior prediction and user selection 0.5 0.5 1 1 3 Alelyani and Yang 19 Software crowdsourcing and developers behavior study 0.5 1 1 1 3.5 Machado et al 4 Task allocation in crowdsourcing 0.5 1 1 0.5 3 Borromeo et al 43 Crowd and task influence on crowdsourced work quality 0.5 0.5 0 1 2 Yang et al 12 Dynamic decision support for crowd workers 1 1 1 0.5 3.5 Han et al 44 Budgeted task scheduling for crowdsourced knowledge acquisition 0.5 0 0 0.5 1 Li et al 45 Crowdsourced data management overview and challenges 1 1 0.5 1 3.5 Cui et al 28 Learning task allocation strategies 1 1 1 1 4 Wang et al 14 Recommending CSD by considering Skill Improvement 1 1 0.5 0.5 3 Sanagavarapu and Reddy 46 Crowdsourcing security-opportunities and challenges 0 0.5 0 1 1.5 Costa and Nascimento 37 In-route task selection in crowdsourcing 0.5 0 1 0.5 2 Jiang et al 47 Crowdsourcing task assignment based on workers quality 0.5 0 1 1 2.5 Shin and Paek 48 Task classification in crowdsourcing 0 0 0 1 1 Simão Filho et al 17 Task allocation in distributed SD 0.5 1 1 0 2.5 Pan et al 34 Recommendation of crowdsourcing tasks based on Word2vec semantic tags 0.5 0 1 1 2.5 Weidema et al 49 Toward microtask crowdsourcing software design work 0 0 0 1 1 Song et al 50 Task selection and allocation framework 1 0 1 0 2 Li et al 23 Crowdsourced data management: a survey 1 1 0 1 3 Zhang and Sugiyama 25 Task selection in crowdsourcing 1 1 1 0.5 3.5 Zhang et al 51 On reliable task as...…”

A Protocol for the Diagnosis of Autism Spectrum Disorder Structured in Machine Learning and Verbal Decision Analysis

“…In this study, the preference scale was established through the analysis of the resulting tree and, subsequently, the scale was subjected to the ZAPROS method to classify the tests involved in the case studied [ 31 ]. This hybrid model shows the potential of integrating VIDA with machine learning solutions [ 32 ].…”

A Decentralized Framework for Managing Task Allocation in Distributed Software Engineering

“…Closely related to the issue of task allocation is the issue of task dependency [17]. A few authors have adopted multi-criteria approaches for efficient task distribution among team members [18][19][20]. These approaches use multiple factors in an organization, such as perform context characterization, and rank influencing factors using the verbal decision analysis (VDA) method for evaluation and decision making.…”