Process mining multiple repositories for software defect resolution from control and organizational perspective

Gupta, Monika; Sureka, Ashish; Padmanabhuni, Srinivas

doi:10.1145/2597073.2597081

Cited by 32 publications

(16 citation statements)

References 15 publications

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“…Process mining has been applied to not only healthcare, but also municipalities [15,32], informatics [33,34,35], education [36,37,38], finance [39,40], and manufacturing [16,41].…”

Section: Related Workmentioning

confidence: 99%

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

Doğan

Bayo-Monton

Fernández-Llatas

et al. 2019

Sensors

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The study presents some results of customer paths’ analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men’s bathroom or women’s bathroom. Since the study has a comprehensive scope, we focused on male and female customers’ behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.

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“…Process mining has been applied to not only healthcare, but also municipalities [15,32], informatics [33,34,35], education [36,37,38], finance [39,40], and manufacturing [16,41].…”

Section: Related Workmentioning

confidence: 99%

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

Doğan

Bayo-Monton

Fernández-Llatas

et al. 2019

Sensors

View full text Add to dashboard Cite

show abstract

“…Their DECLARE approach produces a set of LTL constraints. Gupta et al [18] conducted process mining across an issue-tracking system, a code review system, and a version control system. They map events from these systems into a single process (based on states) and determine transition occurrences.…”

Section: Related Workmentioning

confidence: 99%

Using Constraint Mining to Analyze Software Development Processes

Krismayer

Mayr-Dorn²,

Tuder

et al. 2019

2019 IEEE/ACM International Conference on Software and System Processes (ICSSP)

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Most software development organizations nowadays use issue-tracking tools to manage software processes throughout the life-cycle. Still, understanding development processes, keeping track of process execution, and reacting to deviations in projects remains challenging. In particular, the actual process usually differs from the process perceived by developers, making it hard to define the processes developers are expected to carry out. This is further challenged by frequently changing processes and process variations in different projects and teams. In this paper we describe an empirical study in which we applied a constraint mining approach from the field of software monitoring to automatically extract process definitions in the form of constraints. Specifically, we applied the approach to datasets extracted from four real-world projects (using the Jira issue-tracking tool) in a company developing a recreational activities platform. The mined constraints describe the boundaries of the actual processes and thus help to understand process behavior. Constraints can be frequently re-mined to understand process evolution. The mined constraints can also be used to monitor future processes to detect problems in the development process early on. We involved a domain expert to evaluate the usefulness of our results and investigated to what extent the mined constraints reflect the official development process of the company. We also report mining results for different issue types, across projects, and over different time windows.

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“…Detection is usually treated as a classification problem [45]- [49], [52]. Roughly speaking, previous work takes efforts to address this problem from two ways: defining sufficient software metrics [14], [19], [22], [23], [27] and employing statistical learning techniques [20], [21]. Nagappan et al [27] examined code complexity metrics with principle component analysis to build an universally detection model for post-release bugs which can be generalized to arbitrary projects.…”

Section: Bug Detectionmentioning

confidence: 99%

Understanding Effects of Collaborations in Developing Mobile Computing Systems: Popularity, Efficiency, and Quality

Mao

Sun

et al. 2019

IEEE Access

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The development of mobile computing systems is an inherently collaborative activity, and the nature of the collaboration likely affects systems success. Collaboration can lead to faster development of systems and increased creativity, but it may also adversely affect the quality of systems. As one of the most popular and active Web services for developing open source software, Github has been a place of origin of many novel mobile computing systems with the Internet of Things, such as OpenEdge and CloudSim. Meanwhile, Github provides a place for people to collaborate with each other on developing novel mobile service computing systems. In this paper, we explore the effects of collaboration in developing systems hosted by Github and use a model of collaboration to detect bugs of systems aiming to enhance their quality. We conduct an at-scale study of more than five million projects on GitHub to reveal collaboration's effects on the popularity of software systems and speed of development. We find that having more collaborators results in higher popularity but slower development. Projects that use Objective-C are at an even more significant risk for lower development speeds than other projects. We define collaboration networks and co-commit networks, which capture the projects' collaboration patterns and use structural features of these networks to identify files within commits with bugs. By examining 18 large popular projects, we find that involving these features statistically significantly improves bug detection by 6.7% on average.

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Process mining multiple repositories for software defect resolution from control and organizational perspective

Cited by 32 publications

References 15 publications

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application

Using Constraint Mining to Analyze Software Development Processes

Understanding Effects of Collaborations in Developing Mobile Computing Systems: Popularity, Efficiency, and Quality

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