Automated Fixing of Inconsistent Contexts
Xiaokang Chen · Jisuanji kexue yu tansuo · 2013
In pervasive computing, environmental contexts are subject to frequent changes. Context-aware applications need to adapt their behavior accordingly. However, contexts can be easily inconsistent due to many reasons including unpredicted environmental noises and dynamics. Context inconsistency can lead to anomaly or even failure to applications. To address such problems, this paper proposes a novel technique for automatically fixing inconsistent contexts. It consists of two stages: generating abstract repair cases; executing them concretely to validate whether context inconsistency has been fixed. The generated repair cases can be complete or sound, depending on actual requirements from users. The experimental results show that the technique achieves a higher repairing rate than existing techniques.