Cross-Domain Developer Recommendation Algorithm Based on Feature Matching

Yu, Xu; He, Yongjun; Fu, Yu; Xin, Yu; Du, Junwei; Ni, Weijian

doi:10.1007/978-981-15-1377-0_35

Cited by 6 publications

(2 citation statements)

References 23 publications

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“…Project Planning [25] Requirement Management [20] Programming/Coding [14,21,37] Software Testing [7,17] Software Integration [7] Debugging [40] Software Evolution [40] Generic development [8][9][10][11][12][13]15,16,18,19,[22][23][24][26][27][28][29][30][31][32][33][34][35][36]38,39,41,42] The activities mentioned in Table 5 are the only software engineering activities where freelancers were involved as reported by the literature studies. The formulation of the category labels and classification of the studies in these categories were made on the basis of the software engineering activity that the literature studies have focused on.…”

Section: Software Development Area Research Studymentioning

confidence: 99%

Freelancers in the Software Development Process: A Systematic Mapping Study

2020

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[Context] Freelancers could catalyze the software development process by providing their niche skills to generate high quality outputs. They could help companies (including startups) to foster innovations by suggesting creative ideas and providing their expertise in implementing them (for instance, designing solutions, coding solutions etc.). Freelancers could effectively and efficiently work as a virtual member of the software development team. The company must make informed decisions about which task to allot to the freelancer, which freelancer to select, pricing the task, and evaluating the submitted work. On the other hand, the freelancer should make an informed decision about evaluating the monetary value of the task to be charged, trusting the requester, analyzing the skills requirement of the task (finding matches between skill requirement and skills processed), selecting the best task, and maintaining the highest level of reputation. However, the literature does not provide freelancers and the companies the guidelines that support their decision making. However, if freelancers are selected carefully for the most suitable task, the companies will benefit a lot in terms of improved software development metrics. [Objectives] The objective of this paper is to provide the research community the research trends in freelancer-supported software development. This helps to understand that which software development areas have higher concentrations of research efforts, which area has the support of empirical evidence to support management decision makings, and which area requires the research attention. [Method] The systematic study is conducted by planning the mapping protocol, executing the protocol, and reporting the findings using various visualization tools like bar charts and pie charts. The search process was planned to be executed using set of inclusion and exclusion conditions on four bibliographic databases (IEEExplore, Springerlink, Sciencedirect, and ACM digital library). The relevant papers are selected by applying inclusion and exclusion conditions. The google citations of the relevant papers are subject to the inclusion and exclusion conditions again to include the more relevant papers. Finally, the systematic schema was created and populated after analyzing the studies abstracts. [Results] The results indicate the following (a) The research focus is on generic software development (78%) rather on individual life cycle activities. (b) The number of empirical studies is limited (25%). (c) A number of studies proposing solutions and evaluating on live cases in industrial settings are missing from the literature. This is in comparison to the validation approaches (72%) i.e., solutions tested in laboratory settings. (d) At present, the literature has limited ability to provide the software companies (including startups) with the guidelines (in the form of opinions and experience reports) for involving freelancers in the software development process. (e) The reported challenges include Collaboration and Coordination (33%), Developer Recommendation (or selection) (19%), Team Formulation (14%), Task Recommendation (allocation) (14%), Task Decomposition (11%), Privacy and Security (Confidentiality) (11%), Budget Estimation (8%), Recognition (8%), Trust Issues (8%), Market Dynamism (6%), Intellectual Property Issues (6%), Participation of Crowd Worker (6%), and Capacity Utilization (3%). These challenges are highly interactive, and each challenge impacts all other challenges. (e) Recent focus of the researchers (total 7 studies in 2019) is on generic software development handling the collaboration and coordination (3 studies out of 7), Developer recommendation (2 studies out of 7), and task recommendation (2 studies out of 7). [Conclusion] The freelancer-driven software engineering research area has got the attraction of the researchers, but it will take a long time to gain maturity. This puts an urgent call for more empirical studies and evaluation-based solution research that could help companies (including startups) to foster innovations. Further, the research focus should be well distributed among the various development phases to address the unique challenges associated with individual activities. The accurate management of the freelancer in the software development could help companies and startups to foster innovations and remain competitive in the marketplace.

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Section: Software Development Area Research Studymentioning

confidence: 99%

Freelancers in the Software Development Process: A Systematic Mapping Study

2020

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“…Yan et al [61] used heterogeneous information network analysis across various online communities to draw a comprehensive picture of a software developer and their expertise. Yu et al [62] used feature matching developed a cross-domain developer recommendation. Venkataramani et al [63] built a recommendation system on SO based on data mined from GH.…”

Section: Software Developer Expertise Recommendation and Predictionmentioning

confidence: 99%

Understanding and Predicting Software Developer Expertise in Stack Overflow and GitHub

Vadlamani¹

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I, Sri Lakshmi Vadlamani, would like to express my sincere gratitude to my amazing supervisor, Professor Olga Baysal, for her continuous guidance, advice, and friendly discussions. I was able to successfully complete this work solely because of her continuous efforts, her valuable feedback and positive reinforcements at every stage of this project and also through out my MS journey.I am very thankful to God for giving me two sons, Karthik and Krithik; my children thoroughly supported me during this journey by showing great situational awareness and for encouraging me and keeping me optimistic at every step of this journey and especially in some difficult moments. Also, I am thankful to my parents, my in-laws, my siblings and my husband for their support and motivation. I am thankful to my peers Norbert Eke and Khadija Osman for their patience, optimism, support, and encouragement when I needed it the most.

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Decoding the apple paradox: a critical discourse analysis of gender, technology, and nationalism in China’s digital space

Tian,

2024

Humanit Soc Sci Commun

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Cross-Domain Developer Recommendation Algorithm Based on Feature Matching

Cited by 6 publications

References 23 publications

Freelancers in the Software Development Process: A Systematic Mapping Study

Freelancers in the Software Development Process: A Systematic Mapping Study

Understanding and Predicting Software Developer Expertise in Stack Overflow and GitHub

Decoding the apple paradox: a critical discourse analysis of gender, technology, and nationalism in China’s digital space

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