Symptomatic Analysis for Software

MaintenanceA technology designed for

SERC

Symptomatic Analysis for

Software Maintenance

Development of a diagnostic and prognostic system for software that collects data from various types of sources and applies special analytical techniques to analyze the data in real-time to diagnose problems, discern impending faults, and identify maintenance procedures.

GOAL

Most Complex Living Organism

Maintenance (heath management): checkups and diagnosing illness

Most Complex Product Built by Humans

Maintenance: (no health management) fixes and updates

• Cost of maintenance is very high.• A system not designed for maintenance cannot have

maintainability retrofitted later.• Many different opinions of maintainability.• Each organization develops their own definition and

concentrates on efforts to develop mature production processes.

• Process maturity is not enough to guarantee the quality of a specific software product.– Process evaluation should always be accompanied by

product evaluation.– PRODUCT CERTIFICATION IS ALMOST NON-EXISTENT !

Today’s Software Maintenance Realities

What can be observed (learned) from health maintenance?

• Continuous• Relies on a large number of facts obtained• Reaches an accurate conclusion depending on

the timing and the sequence of the symptoms• Case history remains an important tool to

determine the nature of an illness

Future with Symptomatic Analysis for Software Maintenance

• A holistic infrastructure approach ( similar to Health Management)

• Continuously measures and evaluates software products through intelligent, automated diagnostic and prognostic programs

• Provides feedback to process and product improvement by imparting practitioners with an understanding of the condition of their software today and an assurance of its operational state tomorrow.

Based on the design metrics research of 18+ years through the SERC

Design metric analysisModule Signatures

Time-slices Clones

Error (change) analysis

The Foundations for the Symptomatic Analysis Process

The design metrics have been computed on

Raytheon defense systems CSC’s STANFINS project systems from the US Army Research Lab Magnavox’s AFATDS project Harris’ ROCC project three Northrop Grumman projects PBX system from Telcordia Technologies telecommunications systems from Motorola

Results:The design metrics typically identify 90% of the fault-prone modules.

Module SignatureAlgorithmic classification

No incomplete or inconsistent data A single metric can provide insight into product or process. However, in isolation this is seldom useful.

Tougher questions usually need more information.

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Module Signatures Example(De, Di, V(G), LOC)

Then the module signature is a 4-tuple, perhaps

(1,1,0,1)

or equivalently, 13, since

11012 = 1310

Module Signatures • 2 studies

• 98.5% accuracy in identifying change-prone modules

• False negative were only at ½ percent!

• Classes with “more” changes have more “1s” in the signature

• Signatures have the potential to predict the likely number of changes for a given module

Time (Phase) Based Analysis

• Time-slice transformations on design metrics• Before & After

Timeslices

Clone Research

• Clone evolution is a novel field• Current approaches are limited to detecting

only small specialized set of patterns in a clone’s evolution and generally lack scalability

• Empirical research suggests that some clones require higher attention than others

• Our newest discoveries

Symptomatic Analysis Architecture

Examples of Merging and Extracting Data

 

Module Signature Module Name Time Signature Clone COs1011001 Module-1 .0.0.9.9.9 NO 4 Module-2 .0.0.0.64.64 NO 1 Module-3 .0.0.0.89.d NO 3 

Module Signature Module Name Time Signature Clone COs0110000 Module-4 .0.0.44.44.44 yes 2022 3 Module-5 .0.0.0.50.50 yes 2022 1

 

Potential Benefits

A holistic infrastructure approach, as applied through the framework, will allow intelligent, automated diagnostic and prognostic programs to provide practitioners with an understanding of the condition of their software today and an assurance of its operational state tomorrow.

Questions?