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.

Context: Software Engineering solves real world problems and thus requires future engineers to amass experience solving problems in authentic contexts during their formal education. Active learning provides learning contexts where students can acquire experience by doing contextualized and meaningful activities that involve high-order thinking. Despite active learning being proved to be more effective providing hands-on experience in software engineering situations traditional learning activities such as lectures still rival the former. Objectives: Identify and define what active learning strategies are used in software engineering higher education (1) and what application experiences of such strategies have been conducted between 2018 and 2023 (2). Method: A secondary study with Rapid Review as a research method. A Rapid Review is a secondary study which balances literature search breadth and resources available with the purpose of accelerating a systematic mapping study. Results: 18 active learning strategies on software engineering were found across 49 studies. Games and Project-Based Learning were the most frequently used strategies. Conclusions: There are diverse active learning strategies used in software engineering higher education. Active learning strategies can be deployed in varied higher education settings and promote competencies development. Active learning strategies can be combined with other active learning strategies as well as combined with traditional learning activities like lectures in order to foster both lower and higher order thinking skills.

Context: The Open Science (OS) movement promotes the value of making public the research artifacts (datasets, analysis scripts, guidelines, etc.) used during empirical studies. OS is widely known in areas such as Medicine or Biology, where the process of sharing research artifacts is subject to strict protocols. Unfortunately, in Software Engineering (SE), this process is carried out in a non-systematic way, resulting in incomplete or inaccurate material shared by researchers, which hinders the reproducibility and replicability of empirical studies. Nevertheless, in recent years, it seems that the Empirical Software Engineering (ESE) community is embracing some of the proposed OS initiatives, such as the one proposed by the Association for Computing Machinery (ACM), which provides a badge system to evaluate the quality of a research artifact. This badge system has been adopted by several SE conferences as a method of assessing research artifacts. Aims: Focusing on human-oriented experiments (HOEs) in SE, whose research artifacts are more complex than those for computational experiments, this work applies Design Science Research (DSR) with a twofold purpose: (i) review the current status of HOEs research artifacts publication through evaluation of this practice in the most relevant ESE journals , and (ii) propose a structured outline for HOEs research artifacts driven by the aforementioned ACM badging policy. Method: Regarding the first purpose, we carried out a survey to analyze the current status of the publication of research artifacts considering relevant peer review journals and the quality of 106 research artifacts published in these journals with respect to the ACM badging policy. For the second purpose, an iterative process was carried out to review the content of 106 research artifacts research and their concordance with ACM badges, obtaining a structured scheme for HOEs research artifacts that has been validated through a detailed review of 12 research artifacts obtained from some of those of ACM badges in relevant SE conferences. In addition, we validated the proposal in the research artifacts of 2 of our own experiments. Results: Our survey reveals issues such as the 39,70% of journal studies making completely accessible their research artifacts; most of the analyzed research artifacts are incomplete; the most common repositories used in the ESE community to share the research artifacts are GitHub, institutional repositories, and Zenodo. On the other hand, the validated and structured research artifact outline consists of a list of ordered sections containing a set of artifacts, which can be mandatory or not to achieve a particular ACM badge. For its internal validation, several improvement iterations on the first release of the outline have been carried out based on the conference guidelines, the ACM badging policy, and other relevant proposals. Conclusions: Although the ESE community is making great efforts in standardization, review, and digital publishing related to OS, the availability and completeness of research artifacts can be improved. Our proposal for the elaboration of structured research artifact outline meets the requirements of HOEs in SE. Nevertheless, further research is needed not only to improve and externally validate it but also to disseminate its use among the research community.

Technical debt (TD) expresses the lack of internal quality directly affecting software evolution. Therefore, it has gained the attention of software researchers and practitioners recently. Software researchers have performed empirical studies to observe the perspective of TD in different software cultures and organizations. However, it is important to replicate such studies in more places and with more practitioners to strengthen the perception of TD. In this paper, we present the results of a set of new research questions from an evolved survey design of a survey replication in the Uruguayan software industry to characterize how the software industry professionals understand, perceive, and adopt TD management (TDM) activities. The results allow us to observe that different participant contexts (startups, government, job roles) show different levels of awareness and perception of TD. Details in the form of the adoption of each TDM activity were presented. We could observe some difficulties in conducting some TDM activities that the practitioners consider very important, especially in TDM and monitoring. Differences in specific organizational contexts like startups and government could indicate the need for research efforts in other software engineering communities that meet their specific TD challenges and needs.

A software startup is an emerging company focused on the creation and development of an innovative software-intensive product or service as the basis for creating business value. Given the limited resources that startups have, the Lean Startup model advocates the creation of a Minimum Viable Product (MVP) to validate the assumptions about the product or service, and the target market. This study presents the results of a series of interviews with founders of software ventures in relation to the type of MVP they implement, the choice of potential clients, validation mechanisms and difficulties they face in the process of developing and validating the MVP. The main results indicate that the preferred MVP types are landing pages and mock-ups with some functionalities, validation with selected early adopters, obtaining feedback based on interviews and comments, and that the main difficulties encountered are due to lack of experience in software development and in choosing the right technology.

This paper describes and discusses a pilot study about code quality practices from the software development leader perspective. Semi-structured interview and thematic analysis have been selected as qualitative analysis methods. This article introduces the design of the research protocol, the execution of the interviews and the analysis process. The results drawn from the present study suggest potential dependence of the practices according to the context of the organisation: type of client and methodology. Code review, pull request in distributed repositories and coding standards emerge as the main code quality practices.

Background: Technical debt (TD) has been an important focus of attention in recent years by the scientific community and the software industry. TD is a concept for expressing the lack of internal software quality that directly affects its capacity to evolve. Some studies have focused on the TD industry perspective. Aims: To characterize how the software industry professionals in Uruguay understand, perceive, and adopt technical debt management (TDM) activities. Method: To replicate a Brazilian survey with the Uruguayan software industry and compare their findings. Results: From 259 respondents, many indicated any awareness of the TD concept due to the faced difficult to realize how to associate such a concept with actual software issues. Therefore, it is possible to observe a considerable variability in the importance of TDM among the respondents. However, a small part of the respondents declares to carry out TDM activities in their organizations. A list of software technologies declared as used by practitioners was produced and can be useful to support TDM activities. Conclusions: The TD concept and its management are not common yet in Uruguay. There are indications of TD unawareness and difficulties in the conduction of some TDM activities considered as very important by the practitioners. There is a need for more effort aiming to disseminate the TD knowledge and to provide software technologies to support the adoption of TDM in Uruguay. It is likely other software engineering communities face similar issues. Therefore, further investigations in these communities can be of interest.

This study is aimed to validate a text processing architecture for knowledge acquisition and analyze the performance of several populations under controlled validation studies by focusing on empirical methods. We report our experience by analyzing three case studies whose performance issues have been addressed by using a proposed natural-language-mapping model. We discuss the advantages and the disadvantages of an automated prototype for implementing such architectural model, compared with a by-hand one. We compare the cases running out on the prototype in order to identify the suitable features the software systems should have. The final goal of the validation process is describing an ongoing research work concerned with the definition of an approach to automate processes for knowledge extraction in requirements engineering. Some of achieved findings of the performance analysis are: (i) the approach can be applied to business-based technical documents regardless of the organizational process involved; (ii) the activities related to the domain understanding can be executed in a low-costs process; and (iii) empirical methods can be used in controlled validation studies for knowledge extraction approaches.

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 Empirical Software Engineering community is taking a growing interest in replicating experiments, but replications still pose a challenge for researchers. To be able to do better replications, we require detailed knowledge of what happens when a replication is performed. This article introduces a procedure for empirically evaluating replications designed to identify experimental incidents. The evaluation employs a qualitative method to analyze interviews with the principal investigator and other sources of information. We evaluated five replications of the same experiment run by different experimenters at different sites. We identified 49 incident types that occurred between 1 and 4 times across the evaluated replications. Although the replications were conducted within an experimentation network which was set up with collaborative instruments, we identified incidents in all the experimental activities. If experimenters know which incidents are likely to occur in replications, they will be able to focus on the identified problems and improve the replications that they perform. This report is a first step to create and improve experiment communication instruments such as laboratory packages.

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.

In Software Engineering technical literature the references about the benefits of software inspections are abundant. In contrast, some authors raise the problem of low adoption of this process. From this issue a literature review is made to produce a map on most researched topics in the area, factors causing low adoption and possible solutions. Results showed a list of 64 articles selected using a search protocol, which were classified according to a defined taxonomy. The founded factors were codified and a list of solutions founded in the reviewed papers was made. The main conclusion was that most of the factors causing low adoption are related to developers perceptions about the process, lack of training and some characteristics of the process as the rigidity, complexity and the difficulty of connecting the effort made with the final product quality. These factors should be studied in future works.

In the literature there are many empirical studies to evaluate techniques for automatic structural test case generation. However, there isn't a systematic study about the kind of experiments that are conducted to automate the process. The main objective of this paper is the classification and thematic analysis of the experiments reported in the literature to increase the efficacy and efficiency of the automation of structural testing and a classification of the techniques for generating test data. The methodology is a systematic mapping study. The results indicate that the experiments are mainly focused in three areas (test data generation, reduction of test suites and techniques for dealing with complex structures of programs), and that there are different combined approaches to make the generation more effective and efficient.

Some verification and validation techniques have been evaluated both theoretically and empirically. Most empirical studies have been conducted without subjects, passing over any effect testers have when they apply the techniques. We have run an experiment with students to evaluate the effectiveness of three verification and validation techniques (equivalence partitioning, branch testing and code reading by stepwise abstraction). We have studied how well able the techniques are to reveal defects in three programs. We have replicated the experiment eight times at different sites. Our results show that equivalence partitioning and branch testing are equally effective and better than code reading by stepwise abstraction. The effectiveness of code reading by stepwise abstraction varies significantly from program to program. Finally, we have identified project contextual variables that should be considered when applying any verification and validation technique or to choose one particular technique.