article Free Access Share on Design and implementation of a generalized problem solving assistant for algorithm development Authors: Barry L. Kurtz Department of Computer Science, Louisiana Tech University, BOX 10348, Ruston, LA Department of Computer Science, Louisiana Tech University, BOX 10348, Ruston, LAView Profile , Unmesh S. Mayekar Department of Computer Science, Louisiana Tech University, BOX 10348, Ruston, LA Department of Computer Science, Louisiana Tech University, BOX 10348, Ruston, LAView Profile , Michael B. O'Neal Department of Computer Science, Louisiana Tech University, BOX 10348, Ruston, LA Department of Computer Science, Louisiana Tech University, BOX 10348, Ruston, LAView Profile Authors Info & Claims ACM SIGCSE BulletinVolume 27Issue 1March 1995 pp 97–101https://doi.org/10.1145/199691.199740Online:15 March 1995Publication History 8citation212DownloadsMetricsTotal Citations8Total Downloads212Last 12 Months7Last 6 weeks1 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF

article Watson: a modular software environment for introductory computer science education Share on Authors: Michael B. O'Neal Department of Computer Science, Louisiana Tech University, P.O. BOX 10348, Ruston, Louisiana Department of Computer Science, Louisiana Tech University, P.O. BOX 10348, Ruston, LouisianaView Profile , Barry L. Kurtz Department of Computer Science, Louisiana Tech University, P.O. BOX 10348, Ruston, Louisiana Department of Computer Science, Louisiana Tech University, P.O. BOX 10348, Ruston, LouisianaView Profile Authors Info & Claims ACM SIGCSE BulletinVolume 27Issue 1March 1995 pp 87–91https://doi.org/10.1145/199691.199735Online:15 March 1995Publication History 9citation181DownloadsMetricsTotal Citations9Total Downloads181Last 12 Months1Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access

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 little work has been done to apply software complexity concepts to nontraditional programming paradigms. This paper presents a collection of software complexity measures that were specifically designed to quantify 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 complexity based on the ways in which program rules interact with data and 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 required by them to answer questions that required comprehension of program elements. The physical order of program rules was also shown to affect comprehension. The authors conclude that the development of software complexity measures for particular programming paradigms may lead to better tools for managing program development and predicting maintenance effort in nontraditional programming environments.>