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There are many aspects of code quality, some of which are difficult to capture or to measure. Despite the importance of software quality, there is a lack of commonly accepted measures or indicators for code quality that can be linked to quality attributes. We investigate software developers’ perceptions of source code quality and the practices they recommend to achieve these qualities. We analyze data from semi-structured interviews with 34 professional software developers, programming teachers and students from Europe and the U.S. For the interviews, participants were asked to bring code examples to exemplify what they consider good and bad code, respectively. Readability and structure were used most commonly as defining properties for quality code. Together with documentation, they were also suggested as the most common target properties for quality improvement. When discussing actual code, developers focused on structure, comprehensibility and readability as quality properties. When analyzing relationships between properties, the most commonly talked about target property was comprehensibility. Documentation, structure and readability were named most frequently as source properties to achieve good comprehensibility. Some of the most important source code properties contributing to code quality as perceived by developers lack clear definitions and are difficult to capture. More research is therefore necessary to measure the structure, comprehensibility and readability of code in ways that matter for developers and to relate these measures of code structure, comprehensibility and readability to common software quality attributes.
With an increasing complexity and scale, sufficient evaluation of Information Systems (IS) becomes a challenging and difficult task. Simulation modeling has proven as suitable and efficient methodology for evaluating IS and IS artifacts, presupposed it meets certain quality demands. However, existing research on simulation modeling quality solely focuses on quality in terms of accuracy and credibility, disregarding the role of additional quality aspects. Therefore, this paper proposes two design artifacts in order to ensure a holistic quality view on simulation quality. First, associated literature is reviewed in order to extract relevant quality factors in the context of simulation modeling, which can be used to evaluate the overall quality of a simulated solution before, during or after a given project. Secondly, the deduced quality factors are integrated in a quality assessment framework to provide structural guidance on the quality assessment procedure for simulation. In line with a Design Science Research (DSR) approach, we demonstrate the eligibility of both design artifacts by means of prototyping as well as an example case. Moreover, the assessment framework is evaluated and iteratively adjusted with the help of expert feedback.