Wyniki wyszukiwania - BazTech

1

Measurement and Impact Factors of Speed of Reviews and Integration in Continuous Software Engineering

Staron M., Meding W., Söder O., Bäck M.

Foundations of Computing and Decision Sciences

|

2018

|

Vol. 43, No. 4

281--303

EN

Continuous integration and continuous software deployment depend on the mix of automated and manual activities. The automated build and test processes are often intertwined with manual reviews and bug-fixing activities. In this paper, we set o to study how these manual and automated activities influence the speed of reviews and integration. We conduct a case study of two companies developing embedded software, measure the time required for reviewing and integrating software code (alias speed), and conduct a workshop to identify factors which explain the quantitative results. Our results show that the measurement of speed is a good alias for calendar time and triggers improvements better than using measures for velocity. We have also found that the distribution of code repositories, frequent reminders and team proximity decrease the time needed to deploy the software. Our findings are that there is a difference in the structure of code repositories between the fast and slow integration cases, which contributes to the debate on the pros and cons of different repository structures in modern companies.

2

Milestone-Oriented Usage of Key Performance Indicators – An Industrial Case Study

Staron M., Niesel K., Bauman N.

e-Informatica Software Engineering Journal

|

2018

|

Vol. 12, nr 1

217--236

EN

Background: Key Performance Indicators are a common way of quantitative monitoring of project progress in modern companies. Although they are widely used in practice, there is little evidence on how they are set, and how many of them are used in large product development projects. Goal: The goal of this paper is to explore how KPIs are used in practice in a large company. In particular, it is explored whether KPIs are used continuously or only during short, predefined periods of time. It is also explored whether software-related KPIs are reported differently from non-software-related KPIs. Method: A case study of 12 projects at the Volvo Car Group in Sweden was conducted. The data from the project progress reporting on tools was collected and triangulated with data from interviews conducted with experts from the company. Results: KPIs are reported mostly before the milestones and the manual assessment of their status is equally important as the automated data provision in the KPI reporting system. The trend of reporting software-related KPIs is very similar to the non-software-related KPIs. Conclusions: Despite the documented good practices of using KPIs for project monitoring, it is difficult to develop a clear status-picture solely using quantitative data from progress reporting tools. It was also shown that the trends in reporting the software-related KPIs are similar to the trends in reporting the non-software related KPIs.

3

Factors determining long-term success of a measurement program: an industrial case study

Staron M., Medig W.

e-Informatica Software Engineering Journal

|

2011

|

Vol. 5, nr 1

7--23

EN

Introducing measurement programs into organizations is a lengthy process affected by organizational and technical constraints. There exist several aspects that determine whether a measurement program has the chances of succeeding, like management commitment or existence of proper tool support. The establishing of a program, however, is only a part of the success. As organizations are dynamic entities, the measurement programs should constantly be maintained and adapted in order to cope with changing needs of the organizations. In this paper we study one of the measurement programs at Ericsson AB in Sweden and as a result we identify factors determining successful adoption and use of the measurement program. The results of our research in this paper are intended to support quality managers and project managers in establishing and maintaining successful metrics programs.

4

Defect inflow prediction in large software project

Staron M., Meding W.

e-Informatica Software Engineering Journal

|

2010

|

Vol. 4, nr 1

89--107

EN

Performance of software projects can be improved by providing predictions of various project pcharacteristics. The predictions warn managers with information about potential problems and provide them with the possibility to prevent or avoid problems. Large software projects are characterized by a large number of factors that impact the project performance, which makes predicting project characteristics difficult. This paper presents methods for constructing prediction models of trends in defect inflow in large software projects based on a small number of variables. We refer to these models as short-term prediction models and long-term prediction models. The short-term prediction models are used to predict the number of defects discovered in the code up to three weeks in advance, while the long-term prediction models provide the possibility of predicting the defect inflow for the whole project. The initial evaluation of these methods in a large software project at Ericsson shows that the models are sufficiently accurate and easy to deploy.