Theories and techniques for growing software: paradigm and beyond

Abstract

With advances in cloud computing and big data technologies, “human-cyber-physical” applications are providing increasingly rich information and robust functionality. This imposes new technical changes on software systems, which are required to make self-adaptation and continuous evolution to meet our increasingly higher expectations. This article explores theories and techniques for growing software to meet the challenges caused by constantly changing environments and external resources. It studies the source of the software growability problem, seeks to define software growability, and develops a paradigm for growing software. It further analyzes the challenges of supporting environmental sensing and self-adaptation, realizing seamless evolution and process optimization, and developing quality evaluation and assurance mechanisms for growing software. It also reports recent technical advances in these areas from the perspective of long-living and continuously-growing software.