Industry Application of Software Development Task Measurement System: TaskPit

Pawin Suthipornopas, Pattara Leelaprute, Akito Monden, Hidetake Uwano, Yasutaka Kamei, Naoyasu Ubayashi, Kenji Araki, Kingo Yamada, Ken Ichi Matsumoto

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

To identify problems in a software development process, we have been developing an automated measurement tool called TaskPit, which monitors software development tasks such as programming, testing and documentation based on the execution history of software applications. This paper introduces the system requirements, design and implementation of TaskPit; then, presents two real-world case studies applying TaskPit to actual software development. In the first case study, we applied TaskPit to 12 software developers in a certain software development division. As a result, several concerns (to be improved) have been revealed such as (a) a project leader spent too much time on development tasks while he was supposed to be a manager rather than a developer, (b) several developers rarely used e-mails despite the company's instruction to use e-mail as much as possible to leave communication records during development, and (c) several developers wrote too long e-mails to their customers. In the second case study, we have recorded the planned, actual, and self reported time of development tasks. As a result, we found that (d) there were unplanned tasks in more than half of days, and (e) the declared time became closer day by day to the actual time measured by TaskPit. These findings suggest that TaskPit is useful not only for a project manager who is responsible for process monitoring and improvement but also for a developer who wants to improve by him/herself.

Original languageEnglish
Pages (from-to)462-472
Number of pages11
JournalIEICE Transactions on Information and Systems
VolumeE100D
Issue number3
DOIs
Publication statusPublished - Mar 2017

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All Science Journal Classification (ASJC) codes

  • Software
  • Hardware and Architecture
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering
  • Artificial Intelligence

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