Locating Expertise in Agile Software Development Projects

Rejab, Mawarny Md.; Noble, James; Allan, George

doi:10.1007/978-3-319-06862-6_19

Cited by 8 publications

(9 citation statements)

References 14 publications

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“…This scenario could be happened when team members contribute their expertise for helping each other [15,16]. This indirectly supports expertise coordination, when sharing expertise requires team members to rely on each other for locating, recognizing, and accessing expertise [17][18][19]. Deriving KPIs should focus on team goals not on individuals due to nature of Agile methods [7,20].…”

Section: Discussionmentioning

confidence: 99%

Principles of reforming an agile-compliant performance appraisal

Rejab

Omar

Ahmad

et al. 2019

IJEECS

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This paper presents principles of reforming an Agile-compliant performance appraisal. In this study, several semi-structured interviews have been carried out and discovered eight principles for reforming an Agile-compliant performance appraisal for Agile teams. Performance appraisal for software engineers in an Agile software development environment is complex and different from the traditional software development. Performance appraisal should be aligned to Agile values, principles, and practices, which advocate interactions, collaborations, teamwork, and knowledge transfer among Agile team members. Therefore, a transition to Agile Software Development requires the implementation of Agile-compliant performance appraisal. These principles embark the proper practices and guidance to support management and Agile teams in deriving and implementing an Agile-compliant performance appraisal. Therefore, the emerged principles can be a baseline in generating an Agile-compliant performance appraisal to assess Agile team members in a fair and consistent manner. This indirectly increases motivation amongst team members and tends to produce capable workforce to perform at a higher level.

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Section: Discussionmentioning

confidence: 99%

Principles of reforming an agile-compliant performance appraisal

Rejab

Omar

Ahmad

et al. 2019

IJEECS

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“…Instead, the conference was often more a general software engineering venue than one related to agile software per se. However, the present author appreciated those few studies dealing with human aspects of software development, e.g., (Fagerholm & Pagels, 2014;Rejab et al, 2014).…”

Section: The Present Author's Experiencementioning

confidence: 95%

“…The dojo rarely exemplified good practice, but there were occasions of this and several discussions. Rejab, Nobl, & Allan (2014) dealt with locating expertise in agile software development projects. In particular, the authors argued that it is important to know who knows what in the context of software projects.…”

Section: Recent Trends In Agile Processes and Software Engineering Rementioning

confidence: 99%

Recent trends in agile processes and software engineering research - XP 2014 conference report

Graziotin¹

2014

The Winnower

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“…The research conducted in [12] showed that in order to maintain the quality of code, experienced programmers used heuristics to identify code written by novice programmers so that expert suggestions could be presented to improve it. Rejab et al [31] proposed four different ways to identify and quantify the expertise of players of the agile software development team. The research introduced an instrument to estimate the coding skills of Java programmers by analysing their performance on various programming tasks.…”

Section: Background and Related Workmentioning

confidence: 99%

Discovering software developer's coding expertise through deep learning

et al. 2020

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The field of software development is growing rapidly and prevailing in every walk of life. The role of software developers in such a challenging and complex activity is very much important. The allocation of right software developers (i.e. who possesses appropriate coding skills) to projects is one of the crucial factors for successful software development. The problem is that it is very difficult for a client, project manager, as well as for software development organisations to find out an appropriate developer and assign him/her to a particular project. To achieve this, there is a need for such a sound mechanism that could detect the level of software developer coding expertise. This study has formulated criteria for novice and expert developers and carried out such criteria to discover the level of coding expertise of software developers using three different models of deep learning. These models include long short-term memory (LSTM), convolution 1D and hybrid (a combination of LSTM and convolution 1D). The deep learning models have analysed software developers' previously written source code collected from the GitHub repository. An experiment was conducted to evaluate the performance of models. The results showed that the LSTM model performed better in comparison to other models by achieving 96.25% accuracy.

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Locating Expertise in Agile Software Development Projects

Cited by 8 publications

References 14 publications

Principles of reforming an agile-compliant performance appraisal

Principles of reforming an agile-compliant performance appraisal

Recent trends in agile processes and software engineering research - XP 2014 conference report

Discovering software developer's coding expertise through deep learning

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