As automotive software systems evolve toward high and full driving automation, evaluating their quality becomes increasingly challenging, especially concerning emerging behaviors. Context awareness is the capability to sense the environment and adapt behavior. Automotive software systems are context-aware software systems (CASS). Previous secondary studies in technical literature indicate a need for testing techniques for CASS. However, these studies should have investigated the information provided by the industry. Therefore, this article undertakes a gray literature study to uncover evidence of CASS testing using 20 reports from 16 automotive companies as primary sources. Our findings show that industry practices exhibit quality assurance best practices, but CASS abstraction adoption still needs to be completed. Industry reports emphasize testing challenges but lack technical resolutions, relying on amassing diverse datasets for testing. This article has the potential to impact the quality assurance of automotive software systems significantly and lead industry professionals to enhance their testing process.

The integration of drones into shared airspace for beyond visual line of sight (BVLOS) operations presents significant challenges but holds transformative potential for sectors like transportation, construction, energy and defence. A prerequisite for this integration is equipping drones with enhanced situational awareness to ensure collision avoidance and safe operations. Current approaches mainly target single object detection or classification, or simpler sensing outputs that offer limited perceptual understanding and lack the rapid end-to-end processing needed to convert sensor data into safety-critical insights. In contrast, our study leverages radar technology for novel end-to-end semantic segmentation of aerial point clouds to simultaneously identify multiple collision hazards. By adapting and optimizing the PointNet architecture and integrating aerial domain insights, our framework distinguishes five distinct classes: mobile targets like drones (DJI M300 and DJI Mini) and airplanes (Ikarus C42), and static returns (ground and infrastructure) which results in enhanced situational awareness for drones. To our knowledge, this is the first approach addressing simultaneous identification of multiple collision threats in an aerial setting, achieving a robust 94% accuracy. This work highlights the potential of radar technology to advance situational awareness in drones, facilitating safe and efficient BVLOS operations.

Context: Context-awareness challenges the engineering of contemporary software systems and jeopardizes their testing. The variation of context represents a relevant behavior that deepens the limitations of available software testing practices and technologies. However, such software systems are mainstream. Therefore, researchers in non-academic settings also face challenges when developing and testing contemporary soft-ware systems. Objective: To understand how researchers deal with the variation of context when testing context-aware software systems developed in non-academic settings. Method: To undertake a secondary study (Rapid Review) to uncover the necessary evidence from primary sources describing the testing of context-aware software systems outside academia. Results: The current testing initiatives in non-academic settings aim to generate or improve test suites that can deal with the context variation and the sheer volume of test input possibilities. They mostly rely on modeling the systems' dynamic behavior and increasing computing resources to generate test inputs to achieve this. We found no evidence of test results aiming at managing context variation through the testing lifecycle process. Conclusions: So far, the identified testing initiatives and strategies are not ready for mainstream adoption. They are all domain-specific, and while the ideas and approaches can be reproduced in distinct settings, the technologies are to be re-engineered and tailored to the context-awareness of contemporary software systems in different problem domains. Further and joint investigations in academia and experiences in non-academic settings can evolve the body of knowledge regarding the testing of contemporary soft-ware systems in the field.

Technical Debt is a metaphor that explains a phenomenon that occurs in software development when programmers are faced with trade-off decisions (usually ship first vs. quality assurance). This work analyses the amount of technical debt incurred by undergraduate students using different coding techniques. This observational study uses source code from seventy-five students. We provided students with similar exercises to compare techniques by measuring with static code analyzers (Sonar, FindBugs). The techniques are TDD, Test Last, and ad hoc programming. Our results could not find a statistically significant difference of technical debt incurred by each development practices. Nonetheless, with both tools ad hoc programming measures less technical debt than TDD, and TDD measures less than Test Last. Furthermore, we observed that the two measurement tools outputs are not statistically correlated. Finally, we discuss implications for the research of technical debt stemming from our observations.

The technical debt metaphor has received wide attention by both practitioners and researchers alike. The metaphor has been proven useful to explain in economy's terms aspects which occur during the software development process. This work studies the applicability of the metaphor in reflection activities of agile projects. To achieve this, a qualitative research methodology has been carried out to study the records of a live agile development projects. Our results confirm the applicably of the proposal by the identification of terms related to the metaphor in this records. Moreover, our study has further validated the applicability of cost factors used in technical debt measurement reported in the literature.

In the last decade we have witnessed a growth in outsourcing and outshoring development. Following the promise of reducing costs and round-the-clock development, software organizations have grown from local to global enterprises. In the same decade, agile software development methodologies have emerged as a viable alternative to produce software. There is a myriad of agile processes and methodologies now available for any software development organization to choose from. These agile processes follow the values signed in the Agile Manifesto that preaches the exaltation of the individual programmer, high feedback, customer interaction and just enough planning and documentation. But how does global distribution affect these values? Can agile software development be implemented under the global software development context? This paper presents a systematic literature review aimed at identifying factors that affect the adoption of agile factors in global distributed teams. Our findings show that the literature is still in its initial case study publication stage. But most notably, we have found that only a few of the factors found are related to the agile values. Even though more research is clearly needed, this can be a signal that the factors affecting team distribution has more impact on software development than the values and practices preached by the agile processes.