This paper describes a mapping study designed to investigate the available research on bug bounty programs (BBP). Based on the 72 identified papers we conclude that the research has been focused on the organisation of bug bounties from the product owner perspective, rather than on bug hunters and the market for bugs. To understand BBPs better, in addition to the open datasets available today, datasets from more diverse types of companies (e.g. safety critical systems) should be added, and more in-depth qualitative studies conducted.

Well-defined, informative and cheap indicators are important in any software development organization that needs to evaluate aspects of its development processes and product quality. This is especially true for large organizations and for organizations developing complex products; for example automotive safety functions where mechanical, electronic and software systems need to interact. In this paper we describe defect backlog profiles as a well-defined, cheap and informative indicator. We define defect backlog profiles in terms of ISO/IEC 15939, provide a theoretical framework for interpretation, and finally present an evaluation in which we applied the indicator in a longitudinal case study at an automotive manufacturer. In the case study, we compare the software integration defect backlog profile for the active safety component released in 2010 to the profile for the following generation of the same component released in 2015. The results are then linked to a number of process and product changes that occurred between the two product generations. We conclude that defect backlog profiles are cheap in terms of data collection and analysis, and can provide valuable process and product quality information although with limitations.

Domain-specific modelling (DSM) is a modern software development technology that aims at enhancing productivity. One of the claimed advantages of DSM is increased maintainability of software. However, current empirical evidence supporting this claim is lacking. In this paper, we contribute evidence from a case study conducted at a software development company. We study how the introduction of DSM affected the maintenance of a legacy system. We collected data about the maintenance phase of a system that was initially developed using manual programming, but which was gradually replaced by DSM development. We performed statistical analyses of the relation between the use of DSM and the time needed to resolve defects, the defect density, and the phase in which defects were detected. The results show that after introducing DSM the defect density is lower, that defects are found earlier, but resolving defects takes longer. Other observed benefits are that the number of developers and the number of person-hours needed for maintaining the system decreased, and the portability to new platforms increased. Our findings are useful for organizations that consider introducing DSM and would like to know which benefits can be realized in software maintenance.

In this paper, we put forth the thesis that state-of-the-art defect classification schemes – such as ODC and IEEE Std. 1044 – have failed to meet their target; limited industrial adoption is taken as part of the evidence combined with published studies on model driven software development. Notwithstanding, a number of publications show that defect reports can provide valuable information about common, important, or dangerous problems with software products. In this paper, we present the synthesis of two industrial case studies that illustrate that even expert judgement can be deceptive; demonstrating the need for more objective evidence to allow project stakeholder to make informed decisions, and that defect classification is one effective means to that end. Finally, we propose a roadmap that will contribute to improving the defect classification approach, which in consequence will lead to a wider industrial adoption.

Objective: Defect classification is an essential part of software development process models as a means of early identification of patterns in defect inflow profiles. Such classification, however, may often be a tedious task requiring analysis work in addition to what is necessary to resolve the issue. To increase classification efficiency, adapted schemes are needed. In this paper a light-weight defect classification scheme adapted for minimal process footprint -- in terms of learning and classification effort -- is proposed and initially evaluated. Method: A case study was conducted at Volvo Car Corporation to adapt the IEEE Std. 1044 for automotive embedded software. An initial evaluation was conducted by applying the adapted scheme to defects from an existing software product with industry professionals as subjects. Results: The results showed that the classification scheme was quick to learn and understand -- required classification time stabilized around 5-10 minutes already after practicing on 3-5 defects. The results also showed that the patterns in the classified defects were interesting for the professionals, although in order to apply statistical methods more data was needed. Conclusions: We conclude that the adapted classification scheme captures what is currently tacit knowledge and has the potential of revealing patterns in the defects detected in different project phases. Furthermore, we were, in the initial evaluation, able to contribute with new information about the development process. As a result we are currently in the process of incorporating the classification scheme into the company's defect reporting system.

A Bayesian decision-theoretic decision-making framework for integrated vehicle safety systems is introduced. The framework tries to address the increasing need for introduction of optimal decision-making to integrated vehicle safety. The framework tries to capture all the interdependencies between systems in one optimisation problem by designing appropriate risk functions. This is achieved by incorporating driver behaviour model and pre-crash occupant position tracking. New software methods and tools should also be developed to efficiently accommodate this. The framework, in general, leads to higher design flexibility and scalability.