Wednesday, January 18, 2012

The Problem of Analysis and Identification in Software Change Management

Studies in the field of Software Change Management have helped IT managers to identify a number of problem areas in software development. Problems related to software change management tend to occur in five areas: analysis and identification related problems, communication issues, decision-making challenges, effectiveness roadblocks, traceability issues and problems with tools. If we examine each of these we can see a number of important issues that frequently crop-up, especially within third-generation languages (3GL).

Today, I’d like to focus on a high-level review of analysis and identification related problems in software change management. How can we identify and analyze problems in our software to best understand and realize where we have errors that require correction. More importantly, how can we change our approach to application development in a way that reduces the impact and likelihood of errors?

Analysis and identification problems can be seen in several areas. First of all, problems with analysis and identification are driven by concurrent and parallel development approaches. The problems occur because with concurrent efforts it becomes more difficult to determine root causes of program errors. This is exacerbated by the fact that standalone testing does not find the problems leading to the error conditions. Solutions can be found by reducing the number of developers, engaging in  more frequent cycles (such as with agile development or SCRUM), testing without compiling and ultimately by delegating more basic functions to an application platform in a post-3GL approach.

Another factor driving analysis and identification problems is code optimization. For one thing, optimized code, especially optimized C, C# and C++ code is very difficult to understand. In addition, with optimized code, object oriented development tends to create a ripple effect that is not apparent in typical source. Code optimization issues can be avoided by leveraging pre-optimized code, i.e., avoiding heavy 3GL development projects with more advanced development platforms.

A third factor leading to analysis and identification problems comes from the use of shared software components. Here we see impacts across the code base and ripple effects. These can be avoided through better pre-planning, wise use of inheritance principles and by leveraging a platform rather than resorting to line-by-line coding.

The need for high reliability makes the problem of analysis and identification of the impact of software changes particularly important. It is difficult to predict the impact of changes and at times corrective actions may seem difficult or impossible. Avoid this sense of being overwhelmed by engaging in iterative development and testing. Make use of an application platform to better overcome challenges in the analysis and identification of software change management problems. 

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