Metrics to measure the complexity of partial programs
Journal of Systems and Software
Software design and development
Software design and development
Whether software engineering needs to be artificially intelligent
IEEE Transactions on Software Engineering
PROUST: An automatic debugger for Pascal programs
Artificial intelligence and instruction: Applications and methods
Plans in programming: definition, demonstration, and development
Papers presented at the first workshop on empirical studies of programmers on Empirical studies of programmers
Cognitive processes in program comprehension
Papers presented at the first workshop on empirical studies of programmers on Empirical studies of programmers
Artificial intelligence (2nd ed.)
Artificial intelligence (2nd ed.)
The partial metrics system: modeling the stepwise refinement process using partial metrics
Communications of the ACM
Metric-based reasoning about pseudocode design in the partial metrics system
Information and Software Technology
CSC '90 Proceedings of the 1990 ACM annual conference on Cooperation
The sciences of the artificial (3rd ed.)
The sciences of the artificial (3rd ed.)
Software Component with ADA
Knowledgebased Pgm Constr
Elements of Software Science (Operating and programming systems series)
Elements of Software Science (Operating and programming systems series)
Software Maintenance: The Problems and Its Solutions
Software Maintenance: The Problems and Its Solutions
Chunking in Soar: The Anatomy of a General Learning Mechanism
Machine Learning
The chunking of goal hierarchies: a model of practice and stimulus-response compatibility
The chunking of goal hierarchies: a model of practice and stimulus-response compatibility
Learning to recognize reusable software modules by induction
Learning to recognize reusable software modules by induction
An object-oriented approach to the acquisition of software engineering knowledge
CSC '91 Proceedings of the 19th annual conference on Computer Science
Document Processing for Automatic Knowledge Acquisition
IEEE Transactions on Knowledge and Data Engineering
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A system called partial metrics (PM) which utilizes chunking as a model for acquiring knowledge about program implementation is described. The chunking paradigm has three phases. The first phase partitions the object to be chunked into relatively independent parts called aggregates. The objects to be chunked in PM are code modules. Modules are separated into a collection of aggregates based on a model of stepwise refinement. A heuristic that generates a hierarchically structured collection of refinement steps describing how the program could have been developed as a set of independent refinement decisions (object-oriented stepwise implementation) is given. The second phase encodes (abstracts) each of the aggregates. Various techniques for symbolic learning can be applied to produce a frame-based encoding of information present in the code. This abstraction contains information about the aggregate's role in the refinement process as well as the code's functionality. The third phase inserts the chunked aggregate into a hierarchically structured library of cases based on the contents of its frame description. The storage of an aggregate enables its future use in problem-solving activities. An example of how this approach can be used to acquire knowledge from a sort module is described.