Abstract:
Waste in software development projects is defined as anything that consumes resources such as time, effort, room, and money without adding value to the customer. Methods and techniques to identify waste indicators, which are specific for each project, are applied to part of total interactions and the development phases; and spend analysts and developers’ time and effort. Therefore, this paper aims to define a method to identify waste within the software development process in Scrum teams, from data based on JIRA tool, which supports software development planning, management and controlling activities. According to the bibliographic review are defined: (i) indicators for types of waste according to Lean software development principles; (ii) JIRA’s attributes, mathematical operators, keywords, functions and reports related to such indicators. In the proposed method are defined requirements that establish a semantic relation between each indicator variables and formulas to the set of JIRA’S attributes, functions and keywords and, based on them, queries in JIRA Query Language are implemented to quantify the indicators. The method validation is performed using graphics that show queries results classified and grouped by project, indicator and type of waste, acquired from a software project base for a company in the Brazilian financial market. Through the quantitative analysis of results, it is possible to suggest a hypothesis for the occurrence of the types of observed wastes.
Reference:
BUFON, Marcio Trovão; LEAL, Adriano Galindo. Method for identification of waste in the process of software development in agile teams using lean and scrum. In: TING, I-Hsien; CORCHADO, Juan Manuel. (Eds.) Knowledge management in organizations. Switzerland: Springer, 2019. p.466-476. (Communication in Computer and Information Science – CCIS, 1027) (Trabalho apresentado no INTERNANATIONAL CONFERENCE ON KNOWLEDGE MANAGEMENT IN ORGANIZATION, 14., 2019, Zamora, Spain.)
Access to work on the Publisher’s website:
https://rd.springer.com/chapter/10.1007/978-3-030-21451-7_40
Waste in software development projects is defined as anything that consumes resources such as time, effort, room, and money without adding value to the customer. Methods and techniques to identify waste indicators, which are specific for each project, are applied to part of total interactions and the development phases; and spend analysts and developers’ time and effort. Therefore, this paper aims to define a method to identify waste within the software development process in Scrum teams, from data based on JIRA tool, which supports software development planning, management and controlling activities. According to the bibliographic review are defined: (i) indicators for types of waste according to Lean software development principles; (ii) JIRA’s attributes, mathematical operators, keywords, functions and reports related to such indicators. In the proposed method are defined requirements that establish a semantic relation between each indicator variables and formulas to the set of JIRA’S attributes, functions and keywords and, based on them, queries in JIRA Query Language are implemented to quantify the indicators. The method validation is performed using graphics that show queries results classified and grouped by project, indicator and type of waste, acquired from a software project base for a company in the Brazilian financial market. Through the quantitative analysis of results, it is possible to suggest a hypothesis for the occurrence of the types of observed wastes.
Reference:
BUFON, Marcio Trovão; LEAL, Adriano Galindo. Method for identification of waste in the process of software development in agile teams using lean and scrum. In: TING, I-Hsien; CORCHADO, Juan Manuel. (Eds.) Knowledge management in organizations. Switzerland: Springer, 2019. p.466-476. (Communication in Computer and Information Science – CCIS, 1027) (Trabalho apresentado no INTERNANATIONAL CONFERENCE ON KNOWLEDGE MANAGEMENT IN ORGANIZATION, 14., 2019, Zamora, Spain.)
Access to work on the Publisher’s website:
https://rd.springer.com/chapter/10.1007/978-3-030-21451-7_40
