COMPLEXITY-MEASURES FOR RULE-BASED PROGRAMS

Software complexity measures are quantitative estimates of the amount of effort required by a programmer to comprehend a piece of code. Many measures have been designed for standard procedural languages, but li ttle work has been done to apply software complexity concepts to nontr aditional programming paradigms. This paper presents a collection of s oftware complexity measures that were specifically designed to quantif y the conceptual complexity of rule-based programs. These measures are divided into two classes: bulk measures, which estimate complexity by examining aspects of program size, and rule measures, which gauge com plexity based on the ways in which program rules interact with data an d other rules. A pilot study was conducted to assess the effectiveness of these measures. Several measures were found to correlate well with the study participants' ratings of program difficulty and the time re quired by them to answer questions that required comprehension of prog ram elements. The physical order of program rules was also shown to af fect comprehension. The authors conclude that the development of softw are complexity measures for particular programming paradigms may lead to better tools for managing program development and predicting mainte nance effort in nontraditional programming environments.