An empirical study of the impact of project factors on software economics

Huang, Jianglin; Sun, Hongyi; Li, Yan‐Fu

doi:10.1109/ieem.2015.7385605

Cited by 4 publications

(6 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Personnel factors have been investigated as a crucial factor for successful SD (Rodríguez et al , 2012; Sudhakar, 2012). Generally, all the analyzed impacts of these factors can be summarized as software economics (Huang et al , 2015). Over the decades, TS is the most studied factor mainly for productivity, quality, cost and project duration (Biffl and Gutjahr, 2001; Mockus et al , 2002; Pendharkar and Rodger, 2009; Tohidi and Tarokh, 2006).…”

Section: Research Synthesismentioning

confidence: 99%

“…These constraints are associated with software economics. The definition of software economics is ultimately extended to include productivity, quality, cost and project duration (Huang et al , 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Huang et al (2015), Pendharkar and Rodger (2007) and Rodríguez et al (2012) analyzed the impact of TS on various software factors based on the data from International Software Benchmarking Standards Group (ISBSG) team factors, such as individual capability and experience, are all regarded critical for project success in SD (Krishnan, 1998). Selection of an appropriate TS may affect the optimal management of the team’s time for the assigned tasks (Acuña et al , 2009).…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Analyzing time pressure for software economics

Razzaq

Huang

Sun

et al. 2019

JEIM

Self Cite

View full text Add to dashboard Cite

Purpose The research on people and project factors is found extensively in general but not specific to software engineering. Secondly, the existing research has not concentrated on the communication and time complexity of the teams on software economics. The purpose this paper is to develop a model to investigate and quantify the impact of time pressure (TP) on software economics through the communication influence of software team sizes (TS). Design/methodology/approach A research model and five hypotheses are developed based on the gaps in the literature. The data set from International Software Benchmarking Standards Group repository is used for testing the hypotheses. Findings Important findings include: smaller TS tends to exert less TP on average; TP is directly proportional to software economics, however; and TP does not affect the productivity required for the software. Research limitations/implications The study has the following implications: Selection of an appropriate TS for project completion that ensures minimum pressure on team members; and maximize software outcomes in stress-free environment. Practical implications This work is useful for organizations carrying out software projects with teamwork. The project managers can benefit from the results while planning the team factors for achieving the project goals. Social implications The results uphold not to exert pressure on the team as it will not only affect the duly completion of the project but also the well-being of employees. Originality/value The paper is the first one where the proposition of TP estimation is done using TS and communication complexity, and empirically evaluating the impact of TP on four major software economics are the major key contributions of this research work.

show abstract

Section: Research Synthesismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Analyzing time pressure for software economics

Razzaq

Huang

Sun

et al. 2019

JEIM

Self Cite

View full text Add to dashboard Cite

show abstract

“…According to the literature [12,15], better development platform means higher efficiency of software development. Thus, the software development cycle can be shortened.…”

Section: (5) Development Platformmentioning

confidence: 99%

“…For example, (1) Comprehensive weight calculation First, according the method of above section, the objective weight of each factor can be calculated. The steps are as following: 2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21 ,22} U/D={ (1,2,10,14), (3,4,8,9,11,13,15,17,18,19,20,21,22), (5,6,7,12,16)}…”

Section: Algorithm Calculation Processmentioning

confidence: 99%

A Novel Algorithm for Software Development Cost Estimation Based on Fuzzy Rough Set

Wang¹,

Pin²,

Xu³

et al. 2016

JESTR

View full text Add to dashboard Cite

Software project cost estimation is a key point for enterprises to make reasonable project quotations. However, most software cost estimation methods have limited features, such as requiring higher data volume or only having lower estimation accuracy. Aiming to resolve these problems, a novel algorithm for software development cost estimation based on fuzzy rough set was presented. First, the influencing factors of software development cost were analyzed. The objective weight of each influencing factor was obtained from the data analysis of completed projects by using rough set theory. Second, the comprehensive weight of each influencing factor was recalculated by combining the results of the first step with the subjective weight of the factors given by the experts. Combining the comprehensive weight with fuzzy theory, fuzzy similarities were calculated. Third, according to fuzzy similarity, several items that were most similar to the current project were selected as the samples from the completed projects. Then, the software development cost was estimated based on the cost data of samples from the completed project. Finally, this new algorithm was verified to be effective. The result showed that the maximum and average deviations of the fuzzy rough set algorithm were less than 10%, and the estimated maximum and average deviations of the fuzzy rough set algorithm were less than that of the fuzzy analogy algorithm. Thus, the algorithm could estimate the software cost accurately.

show abstract

Towards an evidence-based theoretical framework on factors influencing the software development productivity

Chapetta

Travassos

2020

Empir Software Eng

View full text Add to dashboard Cite

An empirical study of the impact of project factors on software economics

Cited by 4 publications

References 22 publications

Analyzing time pressure for software economics

Analyzing time pressure for software economics

A Novel Algorithm for Software Development Cost Estimation Based on Fuzzy Rough Set

Towards an evidence-based theoretical framework on factors influencing the software development productivity

Contact Info

Product

Resources

About