Jeffrey C. Carver — Page 2

arXiv2020

Software Engineering Practices for Scientific Software Development: A Systematic Mapping Study

Background: The development of scientific software applications is far from trivial, due to the constant increase in the necessary complexity of these applications, their increasing size, and their need for intensive maintenance and reuse. Aim: To this end, developers of scientific software (who usually lack a formal computer science background) need to use appropriate software engineering (SE) practices. This paper describes the results of a systematic mapping study on the use of SE for scientific application development and their impact on software quality. Method: To achieve this goal we have performed a systematic mapping study on 359 papers. We first describe a catalogue of SE practices used in scientific software development. Then, we discuss the quality attributes of interest that drive the application of these practices, as well as tentative side-effects of applying the practices on qualities. Results: The main findings indicate that scientific software developers are focusing on practices that improve implementation productivity, such as code reuse, use of third-party libraries, and the application of "good" programming techniques. In addition, apart from the finding that performance is a key-driver for many of these applications, scientific software developers also find maintainability and productivity to be important. Conclusions: The results of the study are compared to existing literature, are interpreted under a software engineering prism, and various implications for researchers and practitioners are provided. One of the key findings of the study, which is considered as important for driving future research endeavors is the lack of evidence on the trade-offs that need to be made when applying a software practice, i.e., negative (indirect) effects on other quality attributes.

cs.SE↗

arXiv2018

Guidelines for Systematic Mapping Studies in Security Engineering

Security engineering in the software lifecycle aims at protecting information and systems to guarantee confidentiality, integrity, and availability. As security engineering matures and the number of research papers grows, there is an increasing need for papers that summarize results and provide an overview of the area. A systematic mapping study "maps" a research area by classifying papers to identify which topics are well-studied and which need additional study. Therefore, systematic mapping studies are becoming increasingly important in security engineering. This chapter provides methodological support for systematic mapping studies in security engineering based on examples from published security engineering papers. Because security engineering is similar to software engineering in that it bridges research and practice, researchers can use the same basic systematic mapping process, as follows: (1) study planning, (2) searching for studies, (3) study selection, (4) study quality assessment, (5) data extraction, (6) data classification, (7) data analysis, and (8) reporting of results. We use published mapping studies to describe the tailoring of this process for security engineering. In addition to guidance on how to perform systematic mapping studies in security engineering, this chapter should increase awareness in the security engineering community of the need for additional mapping studies.

cs.SE↗