Poor Requirements Yield Poor Cost Estimates

Poor cost estimation can be traced back to these top five causes that all relate to the requirements process:

1. Frequent requirements changes
2. Missing requirements
3. Insufficient communication with users
4. Poor specification of requirements
5. Insufficient analysis

Here are some ways to improve your requirements process:

• Use prototyping to reduce the risk of incorrect requirements.
• Use configuration management to control change.
• Plan new requirements for future releases.
• Use more formal approaches for requirements analysis and specification.

Reference:
Lederer, A. and J. Prasad, "Nine Management Guidelines for Better Cost Estimating," Communications of the ACM, February 1992.

Take Responsibility

In all the [licensed] engineering disciples, when a design fails, the engineers are blamed. Thus, when a bridge collapses, we ask, "What did the engineers do wrong?" When software fails, the engineers are rarely blamed. If they are, the engineers respond with, "The error always existed. My change just exposed it," or "I was just following the pattern," or "My manager made me do it," or " The schedule left insufficient time to do it right." The fact is that the best methods can be utilized in any engineering discipline to produce awful designs. And the most antiquated methods can be utilized in any engineering discipline to produce elegant designs.

There are no excuses. If you are the developer of a system, it is your responsibility to do it right. Take that responsibility. Do it right, or don't do it at all.


Reference:
Hoare, C.A.R., "Software Engineering: A Keynote Address," IEEE 3rd International Conference on Software Engineering, 1978.

Research-Then-Transfer Doesn't Work

The achievements of software engineering research laboratories have difficulties making it into practice. Some reasons would be:

1. Software researchers have little experience developing real systems.
2. Solving a technical problem is easier than making sure it fits in a real system.
3. Researchers and practitioners have different vocabularies which results in difficult communication.

To best improve the chances of successful transfers, you need to from close ties between research and practice in the beginning. Use the industrial environment as the laboratory in which to germinate ideas. Don't try to formulate an idea then transfer it into industry.

Reference:
Basili, V., and J. Musa, "The Future Engineering of Software: A Management Perspective," IEEE Computer, Sept 1991.

Use The Same Name For The Same Concept

Technical documentation must always use the same words to refer to the same concept and the same sentence structure for similar messages. To do otherwise could confuse the reader, causing the reader to spend time trying to determine if there was a technical message in the rewording itself.

For example,

There are three types of special commands. Regular commands come in four varieties.

is not as good as:

There are three types of special commands. There are four types of regular commands.

Reference:
Meyer, B., "On Formalism in Specifications," IEEE Software, January 1985.

Every Software Document Needs An Index

An index is a list of all terms and concepts used in the document, together with one or more page numbers where the term or concept is defined, used, or referenced. This is useful for requirements, design, test cases, and maintenance documents. The index is essential to finding information quickly and during maintenance.

Every Document Needs A Glossary

It is a frustrating experience to read a document and come across a term that is not familiar. The frustration is short-lived; however, when a glossary is available.

The definitions of all terms should be written in a manner that minimizes the need to use the glossary. One technique is first to explain the term in common, everyday terminology, and then add a second definition that uses other glossary terms. Terms used within definitions that are themselves defined elsewhere should be italicized.

Use Documentation Standards

If your project requires that a documentation standard be followed, then, of course, follow it. However, never blame a standard for doing a bad job. Standards exist to provide organizational and content guidance.

Innovate! Follow the standard and do it intelligently. That means including what you know needs to be included regardless of what the standard says. It means writing in clear language. It means adding additional levels of organization that makes sense. If you are not required to follow a standard, at least use one as a checklist to verify that you don't have major omissions.


Reference:
IEEE Computer Society, Software Engineering Standards Collection, Washington, D.C.: IEEE Computer Society Press, 1993.

Don't Ignore Technology

Software engineering technology is evolving rapidly. You cannot afford to sit around without keeping abreast of new developments. Software engineering appears to grow by waves. Each wave brings with it a large collection of fads and buzzwords. Although each wave appears to last just five to seven years, the wave does not simply disappear. Instead each subsequent wave stands upon the best features of all previous waves. (Hopefully "best" means "most effective," but unfortunately it often means "most popular.")

I know of two ways to keep abreast of the technology: reading the right magazines (and books - if very recently published) and talking to the right people. IEEE Software and Communications of the ACM magazines are a good place to learn about what's likely to be useful in the zero-to-five-year timeframe. To learn from talking to people, you must meet the right people. Although talking to folks in your own organization is necessary, it isn't sufficient. Try attending one or two key conferences per year. The presentations are probably not as important as the conversations you have in the hallways.


Reference:
Meyer, B., "On Formalism in Specifications," IEEE Software, January 1985.

Follow The Lemmings With Care

"If 50 million people say a foolish thing, it is still a foolish thing."
-- Anatole France

Just because many (perhaps even, most) people are doing something does not make it right for you. It may be right, but you need to carefully assess its applicability to your environment. Some examples are:

• object-orientation, software measurement
• You Can Optimize Whatever You Want*
• Collect Data Unobtrusively*
• Know Before You Count*
• Collect Productivity Data*
• Don't Forget Team Productivity*
• software reuse
• You Can Reuse Without a Big Investment
• process maturity
• Use an Appropriate Process Model
• computer-aided software engineering (CASE)
• Technique Before Tools
• Use Tools, but Be Realistic
• Give Software Tools to Good Engineers
• Tools Are Expensive
• prototyping
• Build the Right Kind of Prototype
• Build the Right Features into a Prototype
• Build Throwaway Prototypes Quickly
• Prototypes Reduce Risk in Selecting User Interfaces

In all cases, these offer very positive opportunities for increased quality, decreased cost, or increased user satisfaction. However, the advantages are available only to those organizations in which it makes sense. Although the rewards are significant, their potentials are often oversold and are by no means guaranteed or universal.

When you learn about a "new" technology, don't readily accept the inevitable hype* associated with it. Read carefully. Be realistic with respect to payoffs and risks. Run experiments before making major commitments. But by no means can you afford to ignore "new" technologies (Don't Ignore Technology).

Reference:
Davis, A., "Software Lemmingineering," IEEE Software, September 1993.

Fast Software Performance

Here are some aspects of software development that should be considered when trying to improve an application's performance.

Write Better Algorithms

Ultimately, the performance of an application is based on how well is is written. If the program loops around all elements in an array, the JVM will optimize the array bounds-checking so that the loop runs faster, and it may unroll the loop operations to provide an additional speedup. But if the purpose of the loop is to find a specific item, no optimization in the world is going to make the array-based code as fast as a different version that uses a HashMap.

A good algorithm is the most important thing when it comes to fast performance.

Improving your Algorithms & Data Structure Skills | medium

Write Less Code

A small well-written program will run faster than a large well-written program. This is true in general of all programs, and it applies specifically to Java programs. The more code that has to be compiled, the longer it will take until that code runs quickly. The more objects that have to be allocated and deallocated, the more work the garbage collector will have to do. If the objects are allocated and retained, the longer a garbage collection cycle will take. The more classes that have to be loaded from disk in the JVM, the longer it will take for a program to start. The more code that is executed, the less likely it will fit in the hardware caches on the computer. And the more code that has to be executed, the longer it will take.

More code / more features is a "Death by a thousand cuts". A developer will add a very small check for a feature then other developers will do the same and suddenly the performance has regressed. The cycle is repeated in the next release, and the performance starts to be noticeable. A couple of times during the process, performance testing might hit some resource threshold - a critical point in memory use, or a code cache overflow, etc. In those cases, the regular performance tests might make it possible to fix what appears to be a major regression. But over time, as the small regressions creep in, it will be harder and harder to fix.

I'm not advocating that you never add new features or code. The benefits of enhancing your applications is clear. But be aware of the small trade-offs you are making.

Writing Less Damn Code | heydonworks
Write Less Code | codeahoy
The Best Code Is No Code At All | codinghorror

Optimization Best Practices

Software engineers are expected to be familiar with the coding constructs that are known to be bad for performance. When writing code it is not "premature optimization" to apply your knowledge of best practices. So long as you are able to write clean, straightforward code that is simple to read and understand then you don't need to worry that you are prematurely optimizing your code.

30 Java Programming Tips and Best Practices for Beginners | javacodegeeks

Look Elsewhere

If you are developing standalone applications that use no external resources, then the performance of that application is mostly all that matters. Once an external resource such as a database is added, then the performance of both programs is important. And in a distributed environment, say an application server, a load balancer, a database, and more, then the performance of the single application server might be the least of the performance issues. In such an environment, a structured approach must be taken towards all aspects of the system. CPU usage, I/O latencies, and throughput of all parts of the system must be measured and analyzed; only then can it be determined which component is causing the performance bottleneck.

Optimize for the Common Case

It is tempting to treat all performance aspects as equally important. But focus should be given to the common use case scenarios.

• Optimize code by profiling it with realistic usage and focusing on the operations taking the most time.
• Apply Occam's razor to diagnosing performance problems. The simplest explanation for a performance issue is the most conceivable cause; a performance bug in new code is more likely than a bug in the JVM or the operating system.
• Write simple algorithms for the most common operations in the application. In general, optimize for the majority of your users. That will give you good overall performance stats but might not be what you need. For example, if 10% of your users, make 90% of your profit then you should optimize for that 10%.

Finally, JVM Tuning

Now that you have gone through the previous aspects that affect program performance, you are in a good place to tune the JVM.