Empirical Study on Benchmarking Software Development Tasks

Author(s):  
Li Ruan ◽  
Yongji Wang ◽  
Qing Wang ◽  
Mingshu Li ◽  
Yun Yang ◽  
...  
2020 ◽  
Vol 12 (23) ◽  
pp. 10106 ◽  
Author(s):  
Varun Gupta ◽  
Jose Maria Fernandez-Crehuet ◽  
Chetna Gupta ◽  
Thomas Hanne

Context: freelancers and startups could provide each other with promising opportunities that lead to mutual growth, by improving software development metrics, such as cost, time, and quality. Niche skills processed by freelancers could help startups reduce uncertainties associated with developments and markets, with the ability to quickly address market issues (and with higher quality). This requires the associations between freelancers and startup to be long-term, based on trust, and promising agreements driven by motivations (leading to the growth of both parties). Freelancers could help startups foster innovations and undertake software development tasks in better ways than conducted in-house, if they are selected using informed decision-making. Objectives: the paper has three objectives, (1) to explore the strategies of startups to outsource software development tasks to freelancers (termed as freelancing association strategies); (2) to identify challenges in such outsourcings; and (3) to identify the impacts of outsourcing tasks to freelancers on overall project metrics. The overall objective is to understand the strategies for involving freelancers in the software development process, throughout the startup lifecycle, and the associated challenges and the impacts that help to foster innovation (to maintain competitive advantages). Method: this paper performs empirical studies through case studies of three software startups located in Italy, France, and India, followed by a survey of 54 freelancers. The results are analyzed and compared in the identification of association models, issues, challenges, and reported results arising because of such associations. The case study results are validated using members checking with the research participants, which shows a higher level of result agreements. Results: the results indicate that the freelancer association strategy is task based, panel based, or a hybrid. The associations are constrained by issues such as deciding pricing, setting deadlines, difficulty in getting good freelancers, quality issues with software artefacts, and efforts to access freelancer work submissions for reward. The associations have a positive impact on software development if there is availability of good freelancers (which lasts long for various tasks). The paper finally provides a freelancing model framework and recommends activities that could result in making the situation beneficial to both parties, and streamline such associations. Fostering innovation in startups is, thus, a trade-off situation, which is limited and supported by many conflicting parameters.


2017 ◽  
Vol 27 (09n10) ◽  
pp. 1507-1527
Author(s):  
Judith F. Islam ◽  
Manishankar Mondal ◽  
Chanchal K. Roy ◽  
Kevin A. Schneider

Code cloning is a recurrent operation in everyday software development. Whether it is a good or bad practice is an ongoing debate among researchers and developers for the last few decades. In this paper, we conduct a comparative study on bug-proneness in clone code and non-clone code by analyzing commit logs. According to our inspection of thousands of revisions of seven diverse subject systems, the percentage of changed files due to bug-fix commits is significantly higher in clone code compared with non-clone code. We perform a Mann–Whitney–Wilcoxon (MWW) test to show the statistical significance of our findings. In addition, the possibility of occurrence of severe bugs is higher in clone code than in non-clone code. Bug-fixing changes affecting clone code should be considered more carefully. Finally, our manual investigation shows that clone code containing if-condition and if–else blocks has a high risk of having severing bugs. Changes to such types of clone fragments should be done carefully during software maintenance. According to our findings, clone code appears to be more bug-prone than non-clone code.


2017 ◽  
Vol 66 (3) ◽  
pp. 806-824 ◽  
Author(s):  
Tse-Hsun Chen ◽  
Stephen W. Thomas ◽  
Hadi Hemmati ◽  
Meiyappan Nagappan ◽  
Ahmed E. Hassan

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Mahmoud O. Elish ◽  
Tarek Helmy ◽  
Muhammad Imtiaz Hussain

Accurate estimation of software development effort is essential for effective management and control of software development projects. Many software effort estimation methods have been proposed in the literature including computational intelligence models. However, none of the existing models proved to be suitable under all circumstances; that is, their performance varies from one dataset to another. The goal of an ensemble model is to manage each of its individual models’ strengths and weaknesses automatically, leading to the best possible decision being taken overall. In this paper, we have developed different homogeneous and heterogeneous ensembles of optimized hybrid computational intelligence models for software development effort estimation. Different linear and nonlinear combiners have been used to combine the base hybrid learners. We have conducted an empirical study to evaluate and compare the performance of these ensembles using five popular datasets. The results confirm that individual models are not reliable as their performance is inconsistent and unstable across different datasets. Although none of the ensemble models was consistently the best, many of them were frequently among the best models for each dataset. The homogeneous ensemble of support vector regression (SVR), with the nonlinear combiner adaptive neurofuzzy inference systems-subtractive clustering (ANFIS-SC), was the best model when considering the average rank of each model across the five datasets.


Sign in / Sign up

Export Citation Format

Share Document