#1 – PREVENTING SOFTWARE FAILURE – CAPERS JONES – TECHNOLOGY@RISK™

© Capers Jones, President
Capers Jones & Associates LLC
Capers.Jones3@gmail.com

There are millions of software projects in the world, and thousands of software technologies available.  This means that research into topics that affect software project outcomes is of necessity a complicated issue.  By concentrating on the extreme ends of possible results, it is easier to see the root causes of success and failure.  Projects that set records for productivity and quality are at one of the scale.  Projects that are cancelled or have problems severe enough for litigation are at the other end of the scale. This article concentrates on “worst practices” or the factors that most often lead to failure and litigation.

For the purposes of this article, software “failures” are defined as software projects which met any of these attributes:

  1. Termination of project due to cost or schedule overruns.
  2. Schedule or cost overruns in excess of 50% of initial estimates
  3. Applications which, upon deployment, fail to operate safely.
  4. Law suits brought by clients for contractual non-compliance.

Although there are many factors associated with schedule delays and project cancellations, the failures that end up in court always seem to have four major deficiencies:

  1. Accurate estimates were either not prepared or were rejected.
  2. Change control was not handled effectively.
  3. Quality control was inadequate.
  4. Progress tracking did not reveal the true status of the project.

Let us consider each of these topics in turn.

Estimating Problems
Although cost estimating is difficult there are a number of commercial software cost estimating tools that do a capable job:  COCOMO II, KnowledgePlan, True Price, SEER, SLIM, SoftCost, CostXpert, and Software Risk Master are examples.

However just because an accurate estimate can be produced using a commercial estimating tool that does not mean that clients or executives will accept it.  In fact from information presented during litigation, about half of the cases did not produce accurate estimates at all and did not use estimating tools.  However, the other half had accurate estimates, but they were rejected and replaced by forced estimates based on business needs rather than team abilities.

The main reason that accurate estimates were rejected and replaced was the absence of supporting historical benchmark data.  Without history, even accurate estimates may not be convincing. A lack of solid historical data makes project managers, executives, and clients blind to the realities of software development.

Suppose you are a project manager responsible for a kind of software project which no company in the world has ever been able to build in less than 36 calendar months.  As a responsible manager, you develop a careful estimate and critical path analysis, and tell the client and your own executives that you think the project will require 36 to 38 months for completion.

What will often occur is an arbitrary rejection of your plan, and a directive by either the client or by your own executives to “finish this project in 18 months.”  The project in question will usually be a disaster, it will certainly run late, and from the day you receive the directive the project is essentially doomed.

A situation such as this was one of the contributing factors to the long delay in opening the Denver Airport.  Estimates for the length of time to complete and debug the very complex baggage handling software were not believed, according to the article on “Software’s Chronic Crisis” in the September 1994 issue of Scientific American Magazine by T. Wayt Gibbs.

For more than 60 years the software industry lacked a solid empirical foundation of measured results that was available to the public.  Thus almost every major software project is subject to arbitrary and sometimes irrational schedule and cost constraints.  However the International Software Benchmarking Standards Group (ISBSG), a non-profit organization, has started to improve this situation by offering schedule, effort, and cost benchmark reports to the general public.  This data is available in both CD and paper form.  Currently more than 5,000 projects are available, and new projects are added at a rate of perhaps 500 per year.

There are other collections of software benchmark data, such as those gathered by the Galorath Associates, by Gartner Group, by the David’s Consulting Group, by Price Systems,  by Software Productivity Research, and by other companies too.  However, this data is usually made available only on a subscription basis to specific clients of the organizations.  The ISBSG data, by contrast, is available to the general public.

Changing Requirements
The average rate at which software requirements change is about 1% per calendar month.  Thus for a project with a 12 month schedule, more than 10% of the final delivery will not have been defined during the requirements phase.  For a 36 month project, almost a third of the features and functions may have come in as afterthoughts.

These are only average results.  The author has observed a three-year project where the delivered product exceeded the functions in the initial requirements by about 289%.  A Canadian lawsuit dealt with a project that doubled its size in function points due to requirements creep.  A recent arbitration in 2011 deals with a project that went from 15,000 to more than 20,000 function points at a rate of change that approached 5% per calendar month.

It is of some importance to the software industry that the rate at which requirements creep or grow can now be measured directly by means of the function point metric.  This explains why function point metrics are now starting to become the basis of software contracts and outsource agreements.

(Data on requirements creep was noted in all of the breach-of-contract cases where the author participated as an expert witness.  Rates of requirements creep are measured by many companies. Among the author’s clients, more than 100 companies measure requirements creep using function point metrics.)

The current state of the art for dealing with changing requirements includes the following:

  • Effective mapping of business needs to the proposed applications
  • Estimating the number and rate of development changes before starting
  • Using function point metrics to quantify changes
  • A joint client/development change control board or designated domain experts
  • Model-based requirements methodologies
  • Running text-based static analysis tools against text requirements
  • Calculating the FOG and Flesch readability indices of requirements
  • Full time involvement by user representatives for Agile project.
  • Use of joint application design (JAD) to minimize downstream changes
  • Use of formal requirements inspections to minimize downstream changes
  • Use of formal prototypes to minimize downstream changes
  • Planned usage of iterative development to accommodate changes
  • Formal review of all change requests
  • Revised cost and schedule estimates for all changes > 10 function points
  • Prioritization of change requests in terms of business impact
  • Formal assignment of change requests to specific releases
  • Use of automated change control tools with cross-reference capabilities

Unfortunately in projects where litigation occurred, requirements changes were numerous but their effects were not properly integrated into cost, schedule, and quality estimates.  As a result, unplanned slippages and overruns occurred.

In several cases, the requirements changes had not been formally included in the contracts for development, and the clients refused to pay for changes that substantially affected the scope of the projects.  One case involved 82 changes that totaled to more than 2,000 function points or about 20% of the original size of the initial requirements.  Although the contract did include clauses for funding “out of scope” changes, the defendant asserted that the 82 changes were merely refinements rather than changes.  It is obvious that contracts need to be very specific about what constitutes “change.”

Since the defect potentials for changing requirements are larger than for the original requirements by about 10%, and since defect removal efficiency for changing requirements is lower by about 5%, projects with large volumes of changing requirements also have severe quality problems, which are usually invisible until testing begins.  When testing begins, the project is in serious trouble because it is too late to bring the schedule and cost overruns under control.

One of the observed byproducts of the usage of formal joint application design JAD sessions is a reduction in downstream requirements changes.  Rather than having unplanned requirements surface at a rate of 1% to 3% per month, studies of JAD by IBM and other companies have indicated that unplanned requirements changes often drop below 0.5% per month due to the effectiveness of the JAD technique.

Prototypes are also helpful in reducing the rates of downstream requirements changes.  Normally key screens, inputs, and outputs are prototyped so users have some “hands on” experience with what the completed application will look like.

The Agile method of having a full-time user representative attached to the project is also valuable, if this is possible.  However for very large projects with perhaps millions of potential users (such as Microsoft Windows 8) one user cannot speak for every user.  Therefore truly representative customer involvement is feasible only for projects with a fairly small number of users who are likely to utilize the application in similar ways.

Several of the new model-based requirements methods are very successful in eliminating requirements defects.  Some are so fast that they outpace requirements creep.

A new kind of static analysis tool that finds errors in text requirements is also a useful approach to minimizing requirements issues. This kind of tool can be paired with older tools that calculate the readability indexes of text documents; i.e. the FOG and Flesch readability indices.

Requirements changes will always occur for large systems.  It is not possible to freeze the requirements of any real-world application and it is naïve to think this can occur.  Therefore leading companies are ready and able to deal with changes, and do not let them become impediments to progress.  For projects developed under contract, the contract itself must include unambiguous language for dealing with changes.

Quality Problems
It is dismaying to observe the fact that one of the most effective technologies in all of software is never used on projects that turn out to be disasters and end up in court.  Formal design and code inspections have a 50 year history of successful deployment on large and complex software systems.  All “best in class” software producers utilize software inspections.  The measured defect removal efficiency of inspections is more than twice that of most forms of software testing (i.e. about 65% for inspections versus 30% for most kinds of testing).

(The term “best in class” is subjective.  In this article and other studies by the author, it refers to projects that are in the top 15% of all projects measured in terms of quality, schedules, and productivity rates at the same time.)

Effective software quality control is the most important single factor that separates successful projects from delays and disasters.  The reason for this is because finding and fixing bugs is the most expensive cost element for large systems, and takes more time than any other activity.

Successful quality control involves defect prevention, defect removal, and defect measurement activities.  The phrase “defect prevention” includes all activities that minimize the probability of creating an error or defect in the first place.  Examples of defect prevention activities include the Six-Sigma approach, joint application design (JAD) for gathering requirements, usage formal design methods, usage of structured coding techniques, and usage of libraries of proven reusable material.

The phrase “defect removal” includes all activities that can find errors or defects in any kind of deliverable.  Examples of defect removal activities include requirements inspections, design inspections, document inspections, code inspections, automated static analysis of code, complexity analysis, and all kinds of testing.

Some methods can operate in both defect prevention and defect removals domains simultaneously.  The most notable example of a method that is effective in both defect prevention and defect removal roles is that of formal design and code inspections.   Inspections are the top-ranked defect removal method in terms of efficiency.  Also, participation in formal inspections is one of the top methods for defect prevention.  After participation in several design and code inspections, participants spontaneously avoid the kinds of problems that were encountered.  The net effect of inspections in terms of defect prevention is a reduction of about 50% of potential defects.

Both “defect potentials” and “defect removal efficiency” should be measured for every project.  The “defect potentials” are the sum of all classes of defects; i.e. defects found in requirements, design, source code, user documents, and “bad fixes” or secondary defects.  It would be desirable to include defects in test cases too, since there may be more defects in test libraries than in the applications being tested.

The phrase “defect removal efficiency” refers to the percentage of defects found before delivery of the software to its actual clients or users.  If the development team finds 900 defects and the users find 100 defects in a standard time period after release (normally 90 days) then it is obvious that the defect removal efficiency is 90%.

The author strongly recommends that defect removal efficiency levels be included in software outsource and development contracts, with 95% being a proposed acceptable level of defect removal efficiency. For medical devices and weapons systems a higher rate of about 98% defect removal efficiency should be written in to the contracts.

(The U.S. average is only about 85% so a rate of 95% is a significant improvement.  For some mission-critical applications, a higher level such as 98% might be used, but it is technically challenging to achieve such high levels of defect removal efficiency.  Formal inspections and pre-test static analysis plus at least 8 forms of testing are needed to top 98% in defect removal efficiency.

Following are some of the methods for defect prevention, pre-test defect removal, and testing that are associated with high quality levels and high defect removal efficiency levels:

Defect Prevention

  • Joint application design (JAD) for gathering requirements
  • Thorough analysis of business and technical needs
  • Formal architectural analysis before starting design
  • Formal design methods
  • Structured coding methods
  • Formal defect and quality estimation
  • Formal test plans
  • Formal test case construction
  • Participation in formal inspections
  • Formal change management methods
  • Security analysis for the application
  • Six-Sigma approaches (customized for software)
  • Utilization or the Software Engineering Institute’s capability maturity model (CMM) or (CMMI).
  • Utilization of the new team and personal software processes (TSP, PSP)
  • Utilization of Quality Function Deployment (QFD)

Pre-Test Defect Removal

  • Requirements inspections
  • Requirements static analysis
  • Design inspections
  • Document inspections (user’s guides, tutorials, etc.)
  • Code static analysis
  • Code inspections
  • Test plan and test case inspection
  • Defect repair inspection
  • Software quality assurance reviews

Test Defect Removal

  • Unit testing (manual and automated)
  • Component testing
  • New function testing
  • Regression testing (manual and automated)
  • Performance testing
  • Usability testing
  • Security testing
  • System testing
  • External Beta testing
  • Acceptance testing

 

The combination of defect prevention and defect removal activities leads to some very significant differences in the overall numbers of software defects compared between successful and unsuccessful projects.

For projects in the 10,000 function point range, the successful ones accumulate development totals of around 4.0 defects per function point and remove about 95% of them before delivery to customers.  In other words, the number of delivered defects is about 0.2 defects per function point or 2,000 total latent defects.  Of these about 10% or 200 would be fairly serious defects.  The rest would be minor or cosmetic defects.

By contrast, the unsuccessful projects accumulate development totals of around 7.0 defects per function point and remove only about 80% of them before delivery.  The number of delivered defects is about 1.4 defects per function point or 14,000 total latent defects.  Of these about 20% or 2,800 would be fairly serious defects.  This large number of latent defects after delivery is very troubling for users.  The large number of delivered defects is also a frequent cause of litigation.

Unsuccessful projects typically omit design and code inspections and depend purely on testing.  The omission of up-front inspections causes three serious problems:  1) The large number of defects still present when testing begins slows down the project to a standstill;  2) The “bad fix” injection rate for projects without inspections is alarmingly high; 3) The overall defect removal efficiency associated with only testing is not sufficient to achieve defect removal rates higher than about 80%.

Software Milestone Tracking

Readers of this article who work for the Department of Defense or for a defense contractor will note that the “earned value” approach is only cited in passing.  There are several reasons for this.  First, none of the lawsuits where the author was an expert witness involved defense projects so the earned-value method was not utilized.  Second, although the earned-value method is common in the defense community, its usage among civilian projects including outsourced projects is very rare.  Third, empirical data on the effectiveness of the earned-value approach is sparse.  A number of defense projects that used earned-value methods have run late and been over budget.  There are features of the earned-value method that would seem to improve both project estimating and project tracking, but empirical results are sparse.

Once a software project is underway, there are no fixed and reliable guidelines for judging its rate of progress.  The civilian software industry has long utilized ad hoc milestones such as completion of design or completion of coding.  However, these milestones are notoriously unreliable.

Tracking software projects requires dealing with two separate issues:  1) Achieving specific and tangible milestones; 2) Expending resources and funds within specific budgeted amounts.

Because software milestones and costs are affected by requirements changes and “scope creep” it is important to measure the increase in size of requirements changes, when they affect function point totals.  However there are also requirements changes that do not affect function point totals, which are termed “requirements churn.”  Both creep and churn occur at random intervals.  Churn is harder to measure than creep and is often measured via “backfiring” or mathematical conversion between source code statements and function point metrics.

As of 2011 there are automated tools available that can assist project managers in recording the kinds of vital information needed for milestone reports.  These tools can record schedules, resources, size changes, and also issues or problems.

For an industry now more than 50 years of age, it is somewhat surprising that there is no general or universal set of project milestones for indicating tangible progress.  From SPR’s assessment and baseline studies, following are some representative milestones that have shown practical value.

Note that these milestones assume an explicit and formal review connected with the construction of every major software deliverable.  Formal reviews and inspections have the highest defect removal efficiency levels of any known kind of quality control activity, and are characteristics of “best in class” organizations.

Table 1:  Representative Tracking Milestones for Large Software Projects

  1. Requirements document completed
  2. Requirements document review completed
  3. Initial cost estimate completed
  4. Initial cost estimate review completed
  5. Development plan completed
  6. Development plan review completed
  7. Cost tracking system initialized
  8. Defect tracking system initialized
  9. Prototype completed
  10. Prototype review completed
  11. Complexity analysis of base system (for enhancement projects)
  12. Code restructuring of base system (for enhancement projects)
  13. Functional specification completed
  14. Functional specification review completed
  15. Data specification completed
  16. Data specification review completed
  17. Logic specification completed
  18. Logic specification review completed
  19. Quality control plan completed
  20. Quality control plan review completed
  21. Change control plan completed
  22. Change control plan review completed
  23. Security plan completed
  24. Security plan review completed
  25. User information plan completed
  26. User information plan review completed
  27. Code for specific modules completed
  28. Code inspection for specific modules completed
  29. Code for specific modules unit tested
  30. Test plan completed
  31. Test plan review completed
  32. Test cases for specific test stage completed
  33. Test case inspection for specific test stage completed
  34. Test stage completed
  35. Test stage review completed
  36. Integration for specific build completed
  37. Integration review for specific build completed
  38. User information completed
  39. User information review completed
  40. Quality assurance sign off completed
  41. Delivery to beta test clients completed
  42. Delivery to clients completed

The most important aspect of table 1 is that every milestone is based on completing a review, inspection, or test.  Just finishing up a document or writing code should not be considered a milestone unless the deliverables have been reviewed, inspected, or tested.

In the litigation where the author worked as an expert witness, these criteria were not met.  Milestones were very informal and consisted primarily of calendar dates, without any validation of the materials themselves.

Also, the format and structure of the milestone reports were inadequate.  At the top of every milestone report problems and issues or “red flag” items should be highlighted and discussed first.

During depositions and review of court documents, it was noted that software engineering personnel and many managers were aware of the problems that later triggered the delays, cost overruns, quality problems, and litigation.  At the lowest levels, these problems were often included in weekly status reports or discussed at team meetings.  But for the higher-level milestone and tracking reports that reached clients and executives, the hazardous issues were either omitted or glossed over.

A suggested format for monthly progress tracking reports delivered to clients and higher management would include these sections:

Suggested Format for Monthly Status Reports for Software Projects

  1. Status of last months “red flag” problems
  2. New “red flag” problems noted this month
  3. Change requests processed this month versus change requests predicted
  4. Change requests predicted for next month
  5. Size in function points for this months change requests
  6. Size in function points predicted for next month’s change requests
  7. Schedule impacts of this month’s change requests
  8. Cost impacts of this month’s change requested
  9. Quality impacts of this month’s change requests
  10. Defects found this month versus defects predicted
  11. Defects predicted for next month
  12. Costs expended this month versus costs predicted
  13. Costs predicted for next month
  14. Deliverables completed this month versus deliverables predicted
  15. Deliverables predicted for next month

Although the suggested format somewhat resembles the items calculated using the earned value method, this format deals explicitly with the impact of change requests and also uses function point metrics for expressing costs and quality data.

An interesting question is the frequency with which milestone progress should be reported.  The most common reporting frequency is monthly, although exception reports can be filed at any time that it is suspected that something has occurred that can cause perturbations.  For example, serious illness of key project personnel or resignation of key personnel might very well affect project milestone completions and this kind of situation cannot be anticipated.

It might be thought that monthly reports are too far apart for small projects that only last six months or less in total.  For small projects weekly reports might be preferred.  However, small projects usually do not get into serious trouble with cost and schedule overruns, whereas large projects almost always get in trouble with cost and schedule overruns.  This article concentrates on the issues associated with large projects.  In the litigation where the author has been an expert witness, every project under litigation except one was larger than 10,000 function points in size.

The simultaneous deployment of software sizing tools, estimating tools, planning tools, and methodology management tools can provide fairly unambiguous points in the development cycle that allow progress to be judged more or less effectively.  For example, software sizing technology can now predict the sizes of both specifications and the volume of source code needed.  Defect estimating tools can predict the numbers of bugs or errors that might be encountered and discovered.  Although such milestones are not perfect, they are better than the former approaches.

Project management is responsible for establishing milestones, monitoring their completion, and reporting truthfully on whether the milestones were successfully completed or encountered problems.  When serious problems are encountered, it is necessary to correct the problems before reporting that the milestone has been completed.

Failing or delayed projects usually lack of serious milestone tracking.  Activities are often reported as finished while work was still on going.  Milestones on failing projects are usually dates on a calendar rather than completion and review of actual deliverables.

Delivering documents or code segments that are incomplete, contain errors, and cannot support downstream development work is not the way milestones are used by industry leaders.

Another aspect of milestone tracking among industry leaders is what happens when problems are reported or delays occur.  The reaction is strong and immediate:  corrective actions are planned, task forces assigned, and correction begins to occur.  Among laggards, on the other hand, problem reports may be ignored and very seldom do corrective actions occur.

In more than a dozen legal cases involving projects that failed or were never able to operate successfully, project tracking was inadequate in every case.  Problems were either ignored or brushed aside, rather than being addressed and solved.

Because milestone tracking occurs throughout software development, it is the last line of defense against project failures and delays.  Milestones should be established formally, and should be based on reviews, inspections, and tests of deliverables.  Milestones should not be the dates that deliverables more or less were finished.  Milestones should reflect the dates that finished deliverables were validated by means of inspections, testing, and quality assurance review.

An interesting form of project tracking has been developed by the Shoulders Corporation for keeping track of object-oriented projects.  This method uses a 3-Dimensional model of software objects and classes using Styrofoam balls of various sizes that are connected by dowels to create a kind of mobile.   The overall structure is kept in a visible location viewable by as many team members as possible. The mobile makes the status instantly visible to all viewers.  Color coded ribbons indicate status of each component, with different colors indicated design complete, code complete, documentation complete, and testing complete (gold).  There are also ribbons for possible problems or delays.  This method provides almost instantaneous visibility of overall project status.  The same method has been automated using a 3-D modeling package, but the physical structures are easier to see and have proven more useful on actual projects.  The Shoulders Corporation method condenses a great deal of important information into a single visual representation that non-technical staff can readily understand.\

Summary and Results
Successful software projects can result from nothing more than avoiding the more serious mistakes that lead to disaster:  1) Look at the actual results of similar projects;  2) Make planning and estimating formal activities;  3) Plan for and control creeping requirements;  4) Use formal inspections as milestones for tracking project progress;  5) Collect accurate measurement data during your current project, to use with future projects.

Overcoming the risks shown here is largely a matter of opposites, or doing the reverse of what the risk indicates.  Thus a well-formed software project will create accurate estimates derived from empirical data and supported by automated tools for handling the critical path issues.  Such estimates will be based on the actual capabilities of the development team, and will not be arbitrary creations derived without any rigor.  The plans will specifically address the critical issues of change requests and quality control.  In addition, monthly progress reports will also deal with these critical issues.  Accurate progress reports are the last line of defense against failures.

Suggested Readings
Charette, Bob; Software Engineering Risk Analysis and Management; McGraw Hill, New York, NY; 1989.
Charette, Bob; Application Strategies for Risk Management; McGraw Hill, New York, NY; 1990.
DeMarco, Tom; Controlling Software Projects; Yourdon Press, New York; 1982; ISBN 0-917072-32-4; 284 pages.
Everett, Gerald D. and McLeod, Raymond; Software Testing – Testing Across the Entire Software Development Life Cycle; IEEE Press; 2007.
Ewusi-Mensah, Kweku;  Software Development Failures; MIT Press, Cambridge, MA; 2003; ISBN 0-26205072-2276 pages.
Fernandini, Patricia L.; A Requirements Pattern; Addison Wesley, Boston, MA; 2002; ISBN 0-201-73826-0.
Flowers, Stephen; Software Failures: Management Failures; Amazing Stories and Cautionary Tales; John Wiley & Sons; 1996.
Galorath, Dan and Evans, Michael; Software Sizing, Estimation, and Risk Management: When Performance is Measured Performance Improves; Auerbach; Philadelphia, PA; 2006.
Garmus, David and Herron, David; Function Point Analysis – Measurement Practices for Successful Software Projects; Addison Wesley Longman, Boston, MA; 2001; ISBN 0-201-69944-3;363 pages.
Gibbs, T. Wayt; “Trends in Computing: Software’s Chronic Crisis”; Scientific American Magazine, 271(3), International edition; pp 72-81; September 1994.
Gilb, Tom and Graham, Dorothy; Software Inspection; Addison Wesley, Harlow UK; 1993; ISBN 10: 0-201-63181-4.
Glass,  R.L.; Software Runaways:  Lessons Learned from Massive Software Project Failures;  Prentice Hall, Englewood Cliffs; 1998.
International Function Point Users Group (IFPUG); IT Measurement – Practical Advice from the Experts; Addison Wesley Longman, Boston, MA; 2002; ISBN 0-201-74158-X; 759 pages.
Johnson, James et al; The Chaos Report; The Standish Group, West Yarmouth, MA; 2000
Jones, Capers and Bonsignour, Olivier; The Economics of Software Quality; Addison Wesley, Boston, MA; ISBN 10 0-13-258220-1; 2011; 587 pages.
Jones; Capers; Software Engineering Best Practices; McGraw Hill, New York, NY; ISBN 978-0-07-162161-8; 2010; 660 pages.
Jones, Capers; Applied Software Measurement; McGraw Hill, 3rd edition 2008; ISBN 978-0-07-150244-3; 662 pages.
Jones, Capers; Assessment and Control of Software Risks; Prentice Hall, 1994;  ISBN 0-13-741406-4; 711 pages.
Jones, Capers; Patterns of Software System Failure and Success;  International Thomson Computer Press, Boston, MA;  December 1995; 250 pages; ISBN 1-850-32804-8; 292 pages.
Jones, Capers;  Software Quality – Analysis and Guidelines for Success; International Thomson Computer Press, Boston, MA; ISBN 1-85032-876-6; 1997; 492 pages.
Jones, Capers; Estimating Software Costs; McGraw Hill, New York; 2007; ISBN 13-978-0-07-148300-1.
Jones, Capers; Software Assessments, Benchmarks, and Best Practices;  Addison Wesley Longman, Boston, MA; ISBN 0-201-48542-7; 2000; 657 pages.
Jones, Capers: “Sizing Up Software;” Scientific American Magazine, Volume 279, No. 6, December 1998; pages 104-111.
Jones, Capers; Conflict and Litigation Between Software Clients and Developers; Software Productivity Research technical report; Narragansett, RI; 2007; 65 pages.
Kan, Stephen H.; Metrics and Models in Software Quality Engineering, 2nd edition;  Addison Wesley Longman, Boston, MA; ISBN 0-201-72915-6; 2003; 528 pages.
Pressman, Roger; Software Engineering – A Practitioner’s Approach; McGraw Hill, NY; 6th edition, 2005; ISBN 0-07-285318-2.
Radice, Ronald A.; High Qualitiy Low Cost Software Inspections;  Paradoxicon Publishingl Andover, MA; ISBN 0-9645913-1-6; 2002; 479 pages.
Robertson, Suzanne and Robertson, James; Requirements-Led Project Management; Addison Wesley, Boston, MA; 2005; ISBN 0-321-18062-3.
Wiegers, Karl E.; Peer Reviews in Software – A Practical Guide;  Addison Wesley Longman, Boston, MA; ISBN 0-201-73485-0; 2002; 232 pages.
Yourdon, Ed; Death March – The Complete Software Developer’s Guide to Surviving “Mission Impossible” Projects; Prentice Hall PTR, Upper Saddle River, NJ; ISBN 0-13-748310-4; 1997; 218 pages.
Yourdon, Ed; Outsource:  Competing in the Global Productivity Race; Prentice Hall PTR, Upper Saddle River, NJ; ISBN 0-13-147571-1; 2005; 251 pages.

Web Sites
Information Technology Metrics and Productivity Institute (ITMPI): www.ITMPI.org
International Software Benchmarking Standards Group (ISBSG): www.ISBSG.org
International Function Point Users Group (IFPUG): www.IFPUG.org
Software Engineering Institute (SEI): www.SEI.cmu.edu
Software Productivity Research (SPR): www.SPR.com

Suggested Web Sites
http://www.IASAhome.org This is the web site for the non-profit International Association of Software Architects (IASA).  Software architecture is the backbone of all large applications.  Good architecture can lead to applications whose useful life expectancy is 20 years or more.  Questionable architecture can lead to applications whose useful life expectancy is less than 10 years, coupled with increasing complex maintenance tasks and high defect levels.  The IASA is working hard to improve both the concepts of architecture and the training of software architects via a modern and extensive curriculum.

http://www.IIBA.org This is the web site for the non-profit International Institute of Business Analysis.  This institute deals with the important linkage between business knowledge and software that supports business operations.  Among the topics of concern are the Business Analysis Body of Knowledge (BABOK), training of business analysts, and certification to achieve professional skills.

http://www.IFPUG.org This is the web site for the non-profit International Function Point Users Group.  IFPUG is the largest software metrics association in the world, and the oldest association of function point users.  This web site contains information about IFPUG function points themselves, and also citations to the literature dealing with function points.  IFPUG also offers training in function point analysis and administers.  IFPUG also administers a certification program for analysts who wish to become function point counters.

http://www.ISBSG.org This is the web site for the non-profit International Software Benchmark Standards Group.  ISBSG, located in Australia, collects benchmark data on software projects throughout the world.  The data is self-reported by companies using a standard questionnaire.  About 4,000 projects comprise the ISBSG collection as of 2007, and the collection has been growing at a rate of about 500 projects per year.  Most of the data is expressed in terms of IFPUG function point metrics, but some of the data is also expressed in terms of COSMIC function points, NESMA function points, Mark II function points, and several other function point variants.  Fortunately the data in variant metrics is identified.  It would be statistically invalid to include attempt to average IFPUG and COSMIC data, or to mix up any of the function point variations.

http://www.iso.org This is the web site for the International Organization for Standardization (ISO).  The ISO is a non-profit organization that sponsors and publishes a variety of international standards.  As of 2007 the ISO published about a thousand standards a year, and the total published to date is approximately 17,000.  Many of the published standards affect software.  These include the ISO 9000-9004 quality standards and the ISO standards for functional size measurement.

http://www.PMI.org This is the web site for the Project Management Institute (PMI).  PMI is the largest association of managers in the world.  PMI performs research and collects data on topics of interest to managers in every discipline: software, engineering, construction, and so forth.  This data is assembled into the well known Project Management Body of Knowledge or PMBOK.

http://www.ITMPI.org This is the web site for the Information Technology Metrics and Productivity Institute.  ITMPI is a wholly-owned subsidiary of Computer Aid Inc.  The ITMPI web site is a useful portal into a broad range of measurement, management, and software engineering information.  The ITMPI web site also provides useful links to many other web sites that contain topics of interest on software issues.

 

http://www.sei.cmu.edu This is the web site for the Software Engineering Institute (SEI).  The SEI is a federally-sponsored non-profit organization located on the campus of Carnegie Mellon University in Pittsburgh, PA.  The SEI carries out a number of research programs dealing with software maturity and capability levels, with quality, risks, measurement and metrics, and other topics of interest to the software community.

 

http://www.stsc.hill.af.mil/CrossTalk This is the web site of both the Air Force Software Technology Support Center (STSC) and also the CrossTalk journal, which is published by the STSC.  The STSC gathers data and performs research into a wide variety of software engineering and software management issues.  The CrossTalk journal is one of few technical journals that publish full-length technical articles of 4,000 words or more.  Although the Air Force is the sponsor of STSC and CrossTalk, many topics are also relevant to the civilian community.  Issues such as quality control, estimating, maintenance, measurement, and metrics have universal relevance.

 

 

 


#1 – WRITE WAY FOR EMAILS – JOHN PROHODSKY – LIFE@RISK™

By John Prohodsky
Principal – Future Envisoned
Future Envisioned helps client invent their future. John can be reached at
john@future-envisioned.org

Email might be the riskiest behavior that you engage in every day.

I don’t mean hitting “reply all” instead of “reply” or forwarding an email to the wrong person.  Far more damaging is a poorly written email.  A poorly organized email that doesn’t communicate its intended message presents a risk to both yourself and the company.

How often have you received an email and found out later that you didn’t understand what it said or missed something important?  Embarrassed you were?  If the same person repeatedly sends emails that are hard to understand, she becomes known as a bad communicator or gets a reputation as being unorganized.

It can get worse; a poorly written email can make your boss look bad in front of his boss.  And you have a performance review next week.  Talking about bad business karma.

Let’s look at a few examples:  There is the hidden impact of a poorly written email on a project. For example, the email below is ambiguous about the topic and its urgency.

Subject: Document review
We reviewed the documents you sent and found several deficiencies that need to be attended to.  The review was done by department members and an outside consultant that we have used before.  Upon consideration of the nature of the results of the review, it was decided that department needs to review the results. Please let me know of your availability for a meeting.

This email says that a review of some documents found a few problems and that a meeting is needed.  It doesn’t sound urgent so you don’t act on it.  The attendees at the meeting thought they had resolved the problem but didn’t realize they created other problems that you would have caught.

The above email can be rewritten to convey specifics and urgency.

Subject: Serious customer problems
We reviewed the field problem reports and found several instances where our product’s malfunctions cause customers to miss delivery dates. We need to resolve these problems by the end of the week. The problems include:
(A very brief description of a few representative problems.)
We need to meet at 8 am tomorrow morning in the conference room to resolve the issues.

The rewritten email is better, but the action required is at the end of the email. The email can be revised to communicate more clearly:

Subject: Serious repeat customer problems
We reviewed the field problem reports and found several instances where our product’s malfunctions cause customers to miss delivery dates. We will meet at 8 am tomorrow morning in the conference room to resolve the issues.
The problems include:
(A very brief description of a few representative problems.)
We need to resolve these problems by the end of the week.

The revised email allows a quick scan of the email to identify the urgency of the issue and the action required. A complete reading provides background information and the objective.

Email consumes more and more of our time and has become the background noise of business. This is what you can do to improve your email communications, visit  EmailCharter.org.

 

#1 – ARE YOU MANAGING RISK OR IS IT MANAGING YOU? – PAUL KOSTEK – PROJECTS@RISK™

Paul Kostek PixYou’ve completed your project’s Risk Management Plan and now you can move forward with project execution because all of the project’s risks have been identified what can go wrong?  Well plenty.  It’s easy to get caught up in weekly (daily) reviews of the identified risks, tracking status (are the boxes going green, yellow, oh no red?).  Continue reading

#1 – REFRAMING RISK – ED PERKINS – WORK@RISK™

By Ed Perkins
e.perkins@ieee.org

We hear lots of advice on how things now are being “reframed” in terms of risk.  But what does this mean? How would I know that if I saw it? It helps to be an educated observer so you can tell when someone is ‘walking the talk’ vs. ‘blowing smoke’.

First, let’s look at how a risk view is different from the usual and customary. Every day we hear and read about many factors of concern.  Here are some examples that quickly come to mind:

  • Quality: zero defects, customer satisfaction, user-friendly, process in control
  • Cybersecurity:  threats,  anti-virus,  intrusion detection, compliance, authorization, access, integrity, hacking,
  • Operations: reliability, responsiveness, schedule, viral marketing, shipments, milestones, dependencies

These factors are weighted towards transactions and outcomes, in other words, organizational objectives, which is the primary goal of any organization.

If we step back a bit, and look up at a bigger picture, we see that all these factors of concern are based on ensuring a positive outcome or avoiding a negative outcome. We want to avoid defects, have happy customers, be in compliance, be immune from threats, have reliable products, meet schedules, achieve milestones, and have positive results from the things we have to depend upon.

What about risk? When we think about risk, we tend to think of danger and peril, although there also is risk-reward, taking a risk, going out on a limb, etc. So risk is both bad and good? No, risk is risk; it is the possible consequences of the risk that can be bad or good.

Which brings us back to reframing things in terms of risk. If we switch to a risk perspective, these factors  can be restated as (reframed):

  • zero defects as risk of defects
  • customer satisfaction as risk of customer dissatisfaction
  • compliance to risk as non-compliance
  • process in control as risk of uncontrolled process variance
  • reliability as risk of product unreliability
  • access as risk of security breach
  • milestones as risk of not achieving milestones.

Or in other words, in the risk domain, failure to achieve objectives.

Thus in the risk domain, the focus is not on the objectives per se, but on the risk to achieving the objectives. Risk Management is applied to control the risks and enhance the likelihood of achieving the objectives. Risk can be looked at as a two-sided coin: opportunity or danger. Either way, the same approach can be used to manage risk.

To determine if you or your organization are reframing things in terms of risk, or operating in the risk domain, look for this evidence. Do discussions of objectives cover risk? Is the likelihood and consequence of risk factored into decision making? Is any attention paid to assessing likelihood of risks happening, and if the consequences are severe, is any effort put into determining risk management and mitigation options.