Understanding Interaction and Communication Challenges Present in Software Engineering

Researchers have largely identified that interactions and communications pose major challenges in software development, especially when extracting requirements. However, they have not appreciated the sources and the depth of them, thus approaching them with mechanisms that have not (fully) achieved the desired objectives. In this position, we claim that such challenges can be explained using three major theories coming from social sciences: the theory of verbal and nonverbal communication, systemic theory, and democratic theory. We also argue that some of the successful practices of agile methods can be explained in terms of these theories. Finally, we stipulate that a full appreciation of these theories can result in a significant leap forward in the discipline, identifying new mechanisms that can help to overcome the mentioned challenges, understanding fully what we are doing and wh

Characterizing industry-academia collaborations in software engineering: evidence from 101 projects

Research collaboration between industry and academia supports improvement and innovation in industry and helps ensure the industrial relevance of academic research. However, many researchers and practitioners in the community believe that the level of joint industry-academia collaboration (IAC) projects in Software Engineering (SE) research is relatively low, creating a barrier between research and practice. The goal of the empirical study reported in this paper is to explore and characterize the state of IAC with respect to industrial needs, developed solutions, impacts of the projects and also a set of challenges, patterns and anti-patterns identified by a recent Systematic Literature Review (SLR) study. To address the above goal, we conducted an opinion survey among researchers and practitioners with respect to their experience in IAC. Our dataset includes 101 data points from IAC projects conducted in 21 different countries. Our findings include: (1) the most popular topics of the IAC projects, in the dataset, are: software testing, quality, process, and project managements; (2) over 90% of IAC projects result in at least one publication; (3) almost 50% of IACs are initiated by industry, busting the myth that industry tends to avoid IACs; and (4) 61% of the IAC projects report having a positive impact on their industrial context, while 31% report no noticeable impacts or were “not sure”. To improve this situation, we present evidence-based recommendations to increase the success of IAC projects, such as the importance of testing pilot solutions before using them in industry. This study aims to contribute to the body of evidence in the area of IAC, and benefit researchers and practitioners. Using the data and evidence presented in this paper, they can conduct more successful IAC projects in SE by being aware of the challenges and how to overcome them, by applying best practices (patterns), and by preventing anti-patterns.The authors would like to thank the researchers and practitioners who participated in this survey. João M. Fernandes was supported by FCT (Fundação para a Ciência e Tecnologia) within the Project Scope UID/CEC/00319/2013. Dietmar Pfahl was supported by the institutional research grant IUT20-55 of the Estonian Research Council. Andrea Arcuri was supported by the Research Council of Norway (grant agreement No 274385). Mika Mäntylä was partially supported by Academy of Finland grant and ITEA3 / TEKES grant

Towards Developer-Centered Automatic Program Repair:Findings from Bloomberg

This paper reports on qualitative research into automatic program repair (APR) at Bloomberg. Six focus groups were conducted with a total of seventeen participants (including both developers of the APR tool and developers using the tool) to consider: the development at Bloomberg of a prototype APR tool (Fixie); developers' early experiences using the tool; and developers' perspectives on how they would like to interact with the tool in future. APR is developing rapidly and it is important to understand in greater detail developers' experiences using this emerging technology. In this paper, we provide in-depth, qualitative data from an industrial setting. We found that the development of APR at Bloomberg had become increasingly user-centered, emphasising how fixes were presented to developers, as well as particular features, such as cus-tomisability. From the focus groups with developers who had used Fixie, we found particular concern with the pragmatic aspects of APR, such as how and when fixes were presented to them. Based on our findings, we make a series of recommendations to inform future APR development, highlighting how APR tools should 'start small', be customisable, and fit with developers' workflows. We also suggest that APR tools should capitalise on the promise of repair bots and draw on advances in explainable AI

Towards Developer-Centered Automatic Program Repair: Findings from Bloomberg

This paper reports on qualitative research into automatic program repair (APR) at Bloomberg. Six focus groups were conducted with a total of seventeen participants (including both developers of the APR tool and developers using the tool) to consider: the development at Bloomberg of a prototype APR tool (Fixie); developers' early experiences using the tool; and developers' perspectives on how they would like to interact with the tool in future. APR is developing rapidly and it is important to understand in greater detail developers' experiences using this emerging technology. In this paper, we provide in-depth, qualitative data from an industrial setting. We found that the development of APR at Bloomberg had become increasingly user-centered, emphasising how fixes were presented to developers, as well as particular features, such as cus-tomisability. From the focus groups with developers who had used Fixie, we found particular concern with the pragmatic aspects of APR, such as how and when fixes were presented to them. Based on our findings, we make a series of recommendations to inform future APR development, highlighting how APR tools should 'start small', be customisable, and fit with developers' workflows. We also suggest that APR tools should capitalise on the promise of repair bots and draw on advances in explainable AI.Output Status: Forthcomin

Towards Developer-Centered Automatic Program Repair: Findings from Bloomberg

This paper reports on qualitative research into automatic program repair (APR) at Bloomberg. Six focus groups were conducted with a total of seventeen participants (including both developers of the APR tool and developers using the tool) to consider: the development at Bloomberg of a prototype APR tool (Fixie); developers' early experiences using the tool; and developers' perspectives on how they would like to interact with the tool in future. APR is developing rapidly and it is important to understand in greater detail developers' experiences using this emerging technology. In this paper, we provide in-depth, qualitative data from an industrial setting. We found that the development of APR at Bloomberg had become increasingly user-centered, emphasising how fixes were presented to developers, as well as particular features, such as cus-tomisability. From the focus groups with developers who had used Fixie, we found particular concern with the pragmatic aspects of APR, such as how and when fixes were presented to them. Based on our findings, we make a series of recommendations to inform future APR development, highlighting how APR tools should 'start small', be customisable, and fit with developers' workflows. We also suggest that APR tools should capitalise on the promise of repair bots and draw on advances in explainable AI

What Do Software Engineers Care About? Gaps Between Research And Practice

It is a cliché to say that there is a gap between research and practice. As the interest and importance in the practical impact of research has been growing, the gap between research and practice is expected to be narrowing. However, our study reveals that there still seems to be a wide gap. We survey software engineers about what they care about when developing software. We then compare our survey results with the research topics of the papers published in ICSE/FSE recently. We found the following discrepancy: while software engineers care more about software development productivity than the quality of software, papers on research areas closely related to software productivity—such as software development process management and software development techniques—are significantly less published than papers on software verification and validation that account for more than half of publications. We also found that software engineers are in great need for techniques for accurate effort estimation, and they are not necessarily knowledgable about techniques they can use to meet their needs

What do software engineers care about? Gaps between research and practice

It is a clich?? to say that there is a gap between research and practice. As the interest and importance in the practical impact of research has been growing, the gap between research and practice is expected to be narrowing. However, our study reveals that there still seems to be a wide gap. We survey software engineers about what they care about when developing software. We then compare our survey results with the research topics of the papers published in ICSE/FSE recently. We found the following discrepancy: while software engineers care more about software development productivity than the quality of software, papers on research areas closely related to software productivity-such as software development process management and software development techniques-are significantly less published than papers on software verification and validation that account for more than half of publications. We also found that software engineers are in great need for techniques for accurate effort estimation, and they are not necessarily knowledgable about techniques they can use to meet their needs. ?? 2017 Association for Computing Machinery

A influência de fatores na produtividade do desenvolvimento de software de acordo com um modelo de estruturas teóricas

This work presents an evidence-based model describing the effects of a set of factors on software development productivity, obtained through an evidence synthesis method in Software Engineering. Thus, the relationships among this set and the software development productivity (observed phenomena) are described as results of combining theoretical structures capable of expressing and dealing with differences between different effects and uncertainties varying according to the types of studies found in the literature. Besides, to evaluate the model found, its findings are confronted with a survey capturing the practitioners’ perception (managers and leaders of software projects in Brazilian organizations). The degree of agreement between research (the model) and practice (the practitioners’ perception) shows that scientific knowledge does not differ considerably from the reality experienced by software projects when both of them refer to the influence of factors on software development productivity. The impression that research and practice on the theme go through different paths persists. According to this work, the reasons for this impression are more related to the use of non-standardized and, perhaps, inappropriate measures used to perceive and monitor the influence of factors as well as to measure the software development productivityEste trabalho apresenta um modelo baseado em evidências que descreve efeitos de alguns fatores na produtividade do desenvolvimento de software, obtidos através de um método de síntese de evidências em Engenharia de Software. Deste modo, as relações entre um conjunto de fatores e a produtividade do desenvolvimento de software (fenômenos observados) são descritas como resultados da combinação de estruturas teóricas capazes de expressar e tratar diferenças entre efeitos e incertezas variadas de acordo com os tipos de estudos primários encontrados na literatura. Além disso, para avaliar o modelo encontrado, seus achados são confrontados com uma pesquisa de opinião realizada para capturar a percepção de profissionais da prática (gestores e líderes de projetos de software em organizações brasileiras). O grau de concordância entre a pesquisa (o modelo) e a prática (a percepção dos profissionais) demonstra que, aparentemente, o conhecimento científico não diverge consideravelmente da realidade vivenciada pelos projetos de software no Brasil, quando ambos se referem à influência de fatores na produtividade do desenvolvimento de software. Persiste a impressão, entretanto, de que a pesquisa e a prática no tema percorrem caminhos distintos. De acordo com este trabalho, a impressão do distanciamento parece estar relacionadas à questão do uso de medidas não-padronizadas e, talvez, inapropriadas para mensurar os fatores e a produtividade do desenvolvimento de softwar