Software Engineering field has many goals, among them we can certainly deal with monitoring and controlling the development process in order to meet the business requirements of the released software artifact. Software engineers need to have empirical evidence that the development process and the overall quality of software artifacts is converging to the required features. Improving the development process's Effectiveness leads to higher productivity, meaning shorter time to market, but understanding or even measuring the software de- velopment process is an hard challenge. Modern software is the result of a complex process involving many stakeholders such as product owners, quality assurance teams, project manager and, above all, developers. All these stake- holders use complex software systems for managing development process, issue tracking, code versioning, release scheduling and many other aspect concerning software development. Tools for project management and issues/bugs tracking are becoming useful for governing the development process of Open Source soft- ware. Such tools simplify the communications process among developers and ensure the scalability of a project. The more information developers are able to exchange, the clearer are the goals, and the higher is the number of developers keen on joining and actively collaborating on a project. By analyzing data stored in such systems, researchers are able to study and address questions such as: Which are the factors able to impact the software productivity? Is it possible to improve software productivity shortening the time to market?. The present work addresses two major aspect of software development pro- cess: Effectiveness and Affectiveness. By analyzing data stored in project man- agement and in issue tracking system of Open Source Communities, we mea- sured the Effectiveness as the time required to resolve an issue and analyzed factors able to impact it.

Mining software repositories: measuring effectiveness and affectiveness in software systems.

ORTU, MARCO
2015-04-27

Abstract

Software Engineering field has many goals, among them we can certainly deal with monitoring and controlling the development process in order to meet the business requirements of the released software artifact. Software engineers need to have empirical evidence that the development process and the overall quality of software artifacts is converging to the required features. Improving the development process's Effectiveness leads to higher productivity, meaning shorter time to market, but understanding or even measuring the software de- velopment process is an hard challenge. Modern software is the result of a complex process involving many stakeholders such as product owners, quality assurance teams, project manager and, above all, developers. All these stake- holders use complex software systems for managing development process, issue tracking, code versioning, release scheduling and many other aspect concerning software development. Tools for project management and issues/bugs tracking are becoming useful for governing the development process of Open Source soft- ware. Such tools simplify the communications process among developers and ensure the scalability of a project. The more information developers are able to exchange, the clearer are the goals, and the higher is the number of developers keen on joining and actively collaborating on a project. By analyzing data stored in such systems, researchers are able to study and address questions such as: Which are the factors able to impact the software productivity? Is it possible to improve software productivity shortening the time to market?. The present work addresses two major aspect of software development pro- cess: Effectiveness and Affectiveness. By analyzing data stored in project man- agement and in issue tracking system of Open Source Communities, we mea- sured the Effectiveness as the time required to resolve an issue and analyzed factors able to impact it.
27-apr-2015
emotion mining
mining software repositories
software maintenance
software productivity
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/266596
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