Essay 14 - Mutability Analysis

date:2005-09-18 16:24:15 category:War Stories and Advice

First, there are several tiers of mutability in requirements in general. These tiers define typical levels of change context, problem and forces that select a solution.

1. Natural Laws (i.e., Gravity). As well as metaphysical “laws” (i.e., reality). These don’t change much. Sometimes we encapsulate this information with static final constants so we can use names to identify the constants. Pi, e, seconds_per_minute, etc.
2. Legal Context (both statutory law and case law), as well as standards and procedures with the effect of law (i.e. GAAP). Most software products are implicitly constrained, and the constraints are so fundamental as to be immutable. They aren’t design constraints, per se, they are constraints on the context space for the basic description of the problem. Like air, these are hard to see, and their effects are usually noted indirectly.
3. Industry . That is to say, industry practices and procedures which are prevelant, and required to be called a business in a particular industry. Practices and procedures that cannot be ignored without severe, business-limiting consequences. These are more flexible than laws, but as pervasive and almost as implicit. Some software will call out industry-specific features. Health-care packages, banking packages, etc., are explicitly tailored to an industry context.
4. Company . Constraints imposed by the organization of the company itself. The structure of ownership, subsidiaries, stock-holders, directors, trustees, etc. Often, this is reflected in the accounting, HR and Finance systems. The chart of accounts is the backbone of these constraints. These constraints are often canonized in customized software to create unique value based on the company’s organization, or in spite of it.
5. Line of Business . Line of business changes stem from special considerations for subsets of vendors, customers, or products. Sometimes it is a combination of company organization and line of business considerations, making the relationship even more obscure. Often, these are identified as special cases in software. In many cases, the fact that these are special, abnormal cases is lost, and the “normal” case is hard to isolate from all the special cases. Since these are things change, they often become opaque mysteries.
6. Operational Bugs and Workarounds . Some procedures or software are actually fixes for problems introduced in other software. These are the most ephemeral of constraints. The root cause is obscure, the need for the fix is hidden, the problem is enigmatic.

Of these, tiers 1 to 3 are modeled in the very nature of the problem, context and solution. They aren’t modeled explicitly as constraints on X, or business rules that apply to X, they are modeled as X itself. These things are so hard to change that they are embodied in packaged applications, from third parties, that don’t create unique business value, but permit engaging in business to begin with.

Layers 4 to 6, however, might involve software constraints, explicitly packaged to make it clear. Mostly, these are procedural steps required to either expose or conceal special cases. Once in a while these become actual limitations on the domain of allowed data values.

After considering changes to the problem, we also have to consider changes to the solution. The mutation of the implementation can be decomposed into procedural mutation and data model mutation. The Zachman Framework gives us the hint the communication, people and motivation may also change. Often these changes are manifested through procedural or data changes.

Procedural mutation means programming changes. This implies that flexible software is required to respond to business changes, customer/vendor/product changes, and evolving workarounds for other IT bugs. Packaged solutions aren’t appropriate, the maintenance costs are astronomical. Internally developed solutions that require extensive development, installation and configuration aren’t appropriate either. Scripted solutions using tools like Python and Perl are most appropriate to support flexible adaptation of business processes.

Data model mutations fall into two deeper categories: structural and non-structural.

When data values are keys (natural, primary, surrogate or foreign) they generally must satisfy integrity constraints (they must exist, or must not exist, or are mandatory or occur 0..m times). These are structural. The data is uninterpretable, incomplete and broken without them. When these change, it is a either a profound change to the business or a long-standing bug in the data model. Either way the fix is expensive. These have to be considered carefully and understood fully.

When data values are non-key values, the constraints must be free to evolve. The semantics of non-key data fields are rarely fixed by any formalism. Changes to the semantics are rampant, and sometimes imposed by the users without resorting to software change. In the face of such change, the constraints must be chosen wisely.

“Yes, it says its the number of days overdue, but it’s really the deposit amount in pennies. They’re both numbers, after all.”

Mutability Analysis, then, seeks to characterize expected changes to requirements (the problem) as weel as the data and processing aspects of the solution. With some care, this will direct the selection of solutions.