Today’s small and medium-sized enterprises (SMEs) in the software industry are faced with major challenges. While having to work efficiently using limited resources they have to perform quality assurance on their code to avoid the risk of further effort for bug fixes or compensations. Automated static analysis can reduce this risk because it promises little effort for running an analysis. We report on our experience in analysing five projects from and with SMEs by three different static analysis techniques: code clone detection, bug pattern detection and architecture conformance analysis. We found that the effort that was needed to introduce those techniques was small (mostly below one person-hour), that we can detect diverse defects in production code and that the participating companies perceived the usefulness of the presented techniques as well as our analysis results high enough to include the techniques in their quality assurance.
Kautz @cite_14 developed and used metrics to evaluate how new practices and tools for configuration and change management were affecting the software process at three SMEs. This work considers that the key to successful software measurement is to make metrics meaningful and to tailor them to a particular organisation. We confirm that observation in the context of software measurement.
@cite_14
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The key to successful measurement programs is to make the metrics meaningful and tailor them to the organization-however small it might be. Here the author explains how he helped three small companies reduce the time spent handling change requests, correcting errors, and generating system versions and production releases. Both the developers and customers appreciated the improved practices.