Maintainability is a key quality attribute of successful software systems. However, its management in practice is still problematic. Currently, there is no comprehensive basis for assessing and improving the maintainability of software systems. Quality models have been proposed to solve this problem. Nevertheless, existing approaches do not explicitly take into account the maintenance activities, that largely determine the software maintenance effort. This paper proposes a 2-dimensional model of maintainability that explicitly associates system properties with the activities carried out during maintenance. The separation of activities and properties facilitates the identification of sound quality criteria and allows to reason about their interdependencies. This transforms the quality model into a structured and comprehensive quality knowledge base that is usable in industrial project environments. For example, review guidelines can be generated from it. The model is based on an explicit quality metamodel that supports its systematic construction and fosters preciseness as well as completeness. An industrial case study demonstrates the applicability of the model for the evaluation of the maintainability of Matlab Simulink models that are frequently used in modelbased development of embedded systems.
Approximately 70% of the source code of a software system consists of identifiers. Hence, the names chosen as identifiers are of paramount importance for the readability of computer programs and therewith their comprehensibility. However, virtually every programming language allows programmers to use almost arbitrary sequences of characters as identifiers which far too often results in more or less meaningless or even misleading naming. Coding style guides somehow address this problem but are usually limited to general and hard to enforce rules like "identifiers should be self-describing". This paper renders adequate identifier naming far more precisely. A formal model, based on bijective mappings between concepts and names, provides a solid foundation for the definition of precise rules for concise and consistent naming. The enforcement of these rules is supported by a tool that incrementally builds and maintains a complete identifier dictionary while the system is being developed. The identifier dictionary explains the language used in the software system, aids in consistent naming, and supports programmers by proposing suitable names depending on the current context.
Software systems over time suffer from a gradual quality decay and therefore costs rise if no pro-active countermeasures are taken. Quality controlling is the first step to avoid this cost trap. Continuous quality assessments enable the early identification of quality problems, when their removal is still inexpensive, and aid in making adequate decisions as they provide an integrated view on the current status of a software system. As a side effect, continuous and timely feedback enables developers and maintainers to improve their skills and thereby helps to avoid future quality defects. To make regular quality controlling feasible, it has to be highly automated and assessment results need to be presented in an aggregated manner to not overwhelm users with too much data. This article gives an overview of tools that aim at solving these issues. As an example, we present the flexible, open source toolkit ConQAT that supports the creation of dashboards for quality controlling and report on its application.
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