I would like to design a Inventory system. Some key features listed below.
Multi User
Multi Branch
Support Online and offline Invoicing
Multi Currency
Language requirements : -
C# 2.0
SQL2005 Server
I appreciate your valuable suggestions and ideas to design perfect Inventory system.
If you have any Database sample model to design such a system please don't hesitate to inform me.
Thanks.
You have some of your requirements listed here, but you do not have enough information to complete a design of an invoicing system, plus you have an unrealistic goal of a perfect inventory system - what is perfect for one person is imperfect for another; I'd settle for aiming for best of breed if I were you.
Do you have access to your customers? If you do, you need to sit down with them and find out what they want. A good way to do this is to model their working processes. Write down what steps they do from start to finish, and what influences their work (known as external actors or interfaces). This is a long process, but will end up with you being able to state exactly what is done, when, and in what order, plus the functional and non-functional constraints on the system.
Once you have this information, actually designing the physical system is relatively straightforward. Good luck.
[Big hint] The process I have described here makes heavy use of UML.[/Big hint]
Closed. This question needs to be more focused. It is not currently accepting answers.
Want to improve this question? Update the question so it focuses on one problem only by editing this post.
Closed 2 years ago.
Improve this question
I've had some interesting conversations recently about software development metrics, in particular how they can be used in a reasonably large organisation to help development teams work better. I know there have been Stack Overflow questions about which metrics are good to use - like this one, but my question is more about which metrics are useful to which stakeholders, and at what level of aggregation.
As an example, my view is that code coverage is a useful metric in the following ways (and maybe others):
For a team's own internal use when combined with other measurements.
For facilitating/enabling/mentoring
teams, where it might be instructive
when considered on a team-by-team
basis as a trend (e.g. if team A and
B have coverage this month of 75 and
50, I'd be more concerned with team A
than B if the previous month they'd
had 80 and 40).
For senior management
when presented as an aggregated
statistic across a number of teams or
a whole department.
But I don't think it's useful for senior management to see this on a team-by-team basis, as this encourages artifical attempts to bolster coverage with tests that merely exercise, rather than test, code.
I'm in an organisation with a couple of levels in its management hierarchy, but where the vast majority of managers are technically minded and able (with many still getting their hands dirty). Some of the development teams are leading the way in driving towards agile development practices, but others lag, and there is now a serious mandate from the top for this to be the way the organisation works. A couple of us are starting a programme to encourage this. In this sort of an organisation, what sort of metrics do you think are useful, to whom, why, and at what level of aggregation?
I don't want people to feel their performance is being assessed based on a metric that they can artificially influence; at the same time, the senior management are going to want some sort of evidence that progress is being made. What advice or caveats can you provide based on experience in your own organisations?
EDIT
We are definitely wanting to use metrics as a tool for organisational improvement not as a tool for individual performance measurement.
A tale from personal experience. Apologies for the length.
A few years ago our development group tried setting "proper" measurable objectives for individuals and team leaders. The experiment lasted for just one year, because hard metrics didn't really work very well for individual objectives (see my question on the subject for some links and further discussion).
Note that I was a team leader, and involved in planning it all with my technical boss and the other team leaders, so the objectives weren't something dictated from on high by clueless upper management -- at the time we really wanted them to work. It is also worth noting that the bonus structure inadvertently encouraged competition between developers. Here are my observations on the things we tried.
Customer-visible issues
In our case, we counted outages on the service we provided to customers. In a shrink-wrapped product it might be the number of bugs reported by customers.
Advantages: This was the only real measure that was visible to upper management. It was also the most objective, being measured outside the development group.
Disadvantages: There weren't that many outages -- just around one per developer for the whole year -- which meant that failing or exceeding the objective was a matter of "pinning blame" for the few outages that did occur in each team. This led to bad feeling and loss of morale.
Amount of work completed
Advantages: This was the only positive measure. Everything else was "we notice when bad things happen," which was demoralising. Its inclusion was also necessary because, without it, a developer who did nothing all year would exceed all the other objectives, which clearly wouldn't be in the interests of the company. Measuring the amount of work completed checked the natural optimism of developers when estimating task size, which was useful.
Disadvantages: The measure of "work completed" was based on estimates provided by the developers themselves (usually a good thing), but making it part of their objectives encouraged gaming of the system to inflate estimates. We had no other viable measure of work completed: I think the only possible valuable way of measuring productivity is "impact on the company bottom line," but most developers are so far removed from direct sales that this is rarely practical at an individual level.
Defects found in new production code
We measured defects introduced into new production code during the year, as it was felt that bugs from previous years should not count against any individual in this year's objectives. Defects spotted by internal quality teams were included in the count even if they didn't impact customers.
Advantages: Surprisingly few. The time lag between the introduction of a defect and its discovery meant that there was really no immediate feedback mechanism to improve code quality. Macro trends at a team level were more useful.
Disadvantages: There was a heavy focus on the negative, since this objective was only invoked when a defect was found and we needed someone to blame for it. Developers were reluctant to record defects they found themselves, and a simple count meant that minor bugs were as bad as severe problems. Since the number of defects per individual was still quite low, the number of minor and severe defects didn't even out as it might with a larger sample. Old defects were not included, so the group's reputation for code quality (based on all bugs found) did not always match the measurable introduced-this-year count.
Timeliness of project delivery
We measured timeliness as the percentage of work delivered to internal QA teams by the stated deadline.
Advantages: Unlike counting defects, this was a measure that was under immediate, direct control of the developers, as they effectively decided when the work was complete. The presence of the objective focused the mind on completing tasks. This helped the team commit to realistic amounts of work, and improved the perception by internal customers of the development group's ability to deliver on promises.
Disadvantages: As the only objective directly under the developers' control, it was maximised at the expense of code quality: on the day of a deadline, given the choice between saying a task is complete or doing further testing to improve confidence in its quality, the developer would choose to mark it complete and hope any resulting bugs never come to the surface.
Complaints from internal customers
To gauge how well developers communicated with internal customers during development and subsequent support of their software, we decided that the number of complaints received about each individual would be recorded. The complaints would be validated by the manager, to avoid any possible vindictiveness.
Advantages: Really nothing I can recall. Measured at a sufficiently large group level it becomes a more useful "customer satisfaction" score.
Disadvantages: Not only highly negative, but also a subjective measure. As with other objectives, the numbers for each individual were around the zero mark, which meant that a single comment about someone could mean the difference between "infinitely exceeded" and "did not meet".
General comments
Bureaucracy: While our task management tools held much of the data for these metrics, there was still quite a lot of manual effort involved to collate it all. The time spent obtaining all the numbers was not enjoyable, generally focused on negative aspects of our work and may not even have been reclaimed by increased productivity.
Morale: For the measures where individuals were blamed for problems, not only did those with "bad" scores feel demotivated, but so did those with "good" scores, as they didn't like the loss in team morale and sometimes felt they were ranked higher not because they were better but because they were luckier.
Summary
So what did we learn from the episode? In later years we tried to re-use some of the ideas but in a "softer" way, where there was less emphasis on individual blame and more on team improvement.
It is impossible to define objectives for individual developers that are objectively measurable, add value to the company and cannot be gamed, so don't bother to try.
Customer issues and defects can be counted at a wider team level, if the location of the defect is unequivocally the responsibility of that team -- that is, you don't ever have to play the "blame game".
Once you measure defects only at the level of responsibility for a code module, you can (and should) measure old bugs as well as new ones, since it is in that group's interest to eliminate all defects.
Measuring defect counts at a group level increases the sample size per group, and so anomalies between minor and severe defects are smoothed out and a simple "number of bugs" measure can mean something, such as to see if you are improving month-on-month.
Include something that upper management care about, because keeping them happy is your primary purpose as a development group. In our case it was customer-visible outages, so even if the measure is sometimes arbitrary or seemingly unfair, if it's what the bosses are measuring then you need take notice too.
Upper management don't need to see metrics they don't have in their own objectives. This way it avoids the temptation to blame individuals for errors.
Measuring timeliness of project delivery did change developer behaviour and put a focus on completing tasks. It improved estimation and allowed the group to make realistic promises. If it were easy to collect the timeliness information then I would consider using it again at a team level to measure improvement over time.
All of this doesn't help when you are required to set measurable objectives for individual developers, but hopefully the ideas will be more useful for team improvement.
The key thing about metrics is knowing what you are using them for. Are you using them as a tool for improvement, a tool for reward, a tool for punishment, etc. It sounds like you're planning to use them as a tool for improvement.
The number one principle when setting metrics is to keep the information relevant so that the person receiving it can use it to make a decision. Most likely a senior manager cannot dictate the micro level of whether you need more tests, less complexity, etc. But a team leader can do that.
Therefore, I don't believe a measure of code coverage is going to be useful to management beyond the individual team. At the macro level, the organisation is probably interested in:
Cost of delivery
Timeliness of delivery
Scope of delivery & external quality
Internal quality won't be high on their list of things to cover off. It's a development team's mission to make it clear that internal quality (maintainability, test coverage, self-documenting code, etc) is a key factor in achieving the other three.
Therefore you should target metrics to more senior managers which cover off those three such as:
Overall Velocity (note that comparing velocity between teams is often artificial)
Expected vs Actual scope delivered to agreed timelines
Number of production defects (possibly per capita)
And measure things like code coverage, code complexity, cut 'n' paste score (code repetition using flay or similar), method length, etc at a team level where the recipients of the information can really make a difference.
A metric is a way of answering a question about a project, team or company. Before you start looking for the answers, you need to decide what questions you want to ask.
Typical questions include:
what is the quality of our code?
is the quality improving or degrading over time?
how productive is the team? Is it improving or degrading?
how effective is our testing?
...and so on.
Each question will require a different set of metrics to answer. Collecting metrics without knowing what questions you want answered is at best a waste of time and at worst counterproductive.
You also need to be aware that there is an 'uncertainty principle' at work - unless you are very careful the act of collecting metrics will change people's behaviour, often in unexpected and sometimes detrimental ways. This is especially so if people believe they are being evaluated on the metrics, or worse still have the metrics tied to some reward or punishment scheme.
I recommend reading Gerald Weinberg's Quality Software Management Vol 2: First Order Measurement. He goes into a lot of detail on software metrics, but says the most important are often what he calls "Zero Order Measurement" - asking people their opinion on how a project is going. All four volumes in the series are expensive and hard to get hold of, but well worth it.
Software writing
What must be optimised?
CPU(s) use, memory(s) use, memory cache(s) use, user time use, code size at run-time, data size at run-time, graphics performance, file access performance, network access performance, bandwidth use, code conciseness and readability, electricity use, (count of) distinct API calls used, (count of) distinct methods and algorithms used, maybe more.
How much must it be optimised?
It must be optimised the minimum reasonable amount (except in areas where surpassing acceptance test criteria is desirable) required to pass acceptance tests, facilitate maintenance, facilitate audit and meet user requirements.
("... for legal/illegal input test data and legal/illegal test events in all test states at all required test data volumes and test request volumes for all current and future test integration scenarios.")
Why the minimum reasonable amount?
Because optimised code is harder to write and so costs more.
What leadership is required?
Coding standards, basic structure, acceptance criteria and guidance on levels of optimisation required.
How can success of software writing be measured?
Cost
Time
Acceptance test passes
Extent to which acceptance tests it is desirable to surpass are surpassed
User approval
Ease of maintenance
Ease of audit
Degree of absence of over-optimisation
What cost/time should be ignored in assessing aggregate performance of programmers?
Wasted cost/time incurred because of requirements (inc architecture) changes
Extra cost/time incurred because of deficiencies in platforms/tools
But this cost/time should be included in assessing aggregate performance of teams (inc architects, managers).
How can success of architects be measured?
Other measures plus:
Instances of "avoiding early" being affected by deficiencies in platforms/tools
Degree of absence of changes in architecture
As I said in What is the fascination with code metrics?, metrics include:
different populations, meaning the scope of interest is not the same for developer or for manager
trends meaning any metrics in itself is meaningless without its associated trend, in order to take the decision to act upon it or to ignore it.
We are using a tool able to provide:
lots of micro-level metrics (interesting for developers), with trends.
lots of rules with multi-level (UI, Data, Code) static analysis capabilities
lots of aggregations rules (meaning those vast number of metrics are condensed in several domains of interests, adequate for higher level of populations)
The result is an analysis which can be drilled-down, from high level aggregation domains (security, architecture, practices, documentation, ...) all the way down to some line of code.
The current feedback is:
project managers can get defensive very quickly when some rules are not respected and make their global note significantly lower.
Each study has to be re-tailored to respect each project quirks.
The benefit is the definition of a contract where exceptions are acknowledged but rules to be respected are defined.
higher levels (IT department, stakeholder) use the global notes just as one element of their evaluation of the progress made.
They will actually look more closely at other elements based on delivery cycles: how often are we able to iterate and put an application into production?, how many errors did we had to solve before that release? (in term of merges, or in term of pre-production environment not correctly setup), what immediate feedbacks are generated by a new release of an application?
So:
which metrics are useful to which stakeholders, and at what level of aggregation
At high level:
the (static analysis) metrics are actually the result of low-level metric aggregations, and organized by domains.
Other metrics (more "operational-oriented", based on the release cycle of the application, and not just on the static analysis of the code) are taken into account
The actual ROI is achieved through other actions (like six-sigma studies)
At lower level:
the static analysis is enough (but has to encompass multi-level tiers applications, with sometimes multi-languages developments)
the actions are piloted by the trends and importance
the study has to be approved/supported by all levels of hierarchy to be accepted/acted upon (in particular, budget for the ensuing refactoring has to be validated)
If you have some Lean background/knowledge, then I would suggest the system that Mary Poppendieck recommends (that I've already mentioned in this previous answer). This system is based on three holistic measurements that must be taken as a package:
Cycle time
From product concept to first release or
From feature request to feature deployment or
From bug detection to resolution
Business Case Realization (without this, everything else is irrelevant)
P&L or
ROI or
Goal of investment
Customer Satisfaction
e.g. Net Promoter Score
The aggregation level is product/project level and I believe that these metrics are helpful for everybody (developers should never forget that they don't write code for fun, they write code to create value and should always keep that in mind).
Teams may (and actually do) use technical metrics to measure quality standards conformance which are integrated in the Definition of Done (as "no increase of the technical debt"). But high quality is not a end in itself, it's just a mean to achieve short cycle time (to be a fast company) which is the real target (with Business Case Realization and Customer Satisfaction).
This is a bit of a side note to the main question, but I had a very similar experience to Paul Stephensons answer above. One thing I would add to that is about collection of data and visibility of metrics.
In our case, the development director was meant to collate a bunch of data from various disparate systems and distribute individual metric results once a month. This often didn't happen, as it was a time consuming job and he was a busy man.
The results of this were:
Unhappy developers, as performance bonuses were based on metrics and people didn't know how they were getting on.
Some time consuming multiple entry of data into various different systems.
If you are going down this route, you need to be sure that all metric data can be collated automatically and is easily visible to those it affects.
One of the interesting approaches that's currently getting some hype is Kanban. It's fairly Agile. What's particularly interesting is that it permits a metric of "work done" to be applied. I havn't used/encountered this in actual practice yet, but I'd like to work towards getting a kanban-ish flow going at my job.
Interestingly I just finished reading PeopleWare, and the authors strongly discourage individual metrics being made visible to superiors (even direct managers), but that aggregate metrics should be very visible.
As far as code specific metrics I think it's good for a team to know the state of the code at the current time, and to know the trends affecting the code as it matures and grows.
The question is obviously not focussed on .NET, but I think the .NET product NDepend has done a lot of work to define and document common metrics that are useful.
The documentation section on metrics is educational reading, even if you're not doing .NET.
Software metrics have been with us for a long time and as best I
can tell nothing to date has emerged individually or in aggregate
that is capable of guiding projects during development. The nut of
the problem is that we want to use objective measures and these
can only measure what has happened,
not what is happening or about to happen.
By the time we have measured, analyzed and interpreted some
series of metrics we are reacting to things that
have already gone wrong, or very occasionally, gone right.
I don't want to underplay the importance of learning from
objective metrics but I do want to
point out that this is a reactive not a pro-active response.
Developing a "confidence index" may be a better way of monitoring
whether project is on-track or headed for trouble. Try
developing a voting system where a reasonable number of
representatives from each project area of interest are asked
to anonymously vote their
confidence from time to. Confidence is voted in two areas:
1) Things are on-track 2) Things will continue to be on-track or get
back on-track.
These are purely subjective measurements from people closest to the
"action".
Feed the results into a Kanban type chart where the
columns represent voting areas and you
should have a pretty good idea where to focus your attention. Use
question 1 to evaluate whether management reacted to the
previous voting cycle appropriately. Use question 2 to identify
where management should focus next.
This idea is based on each of us having a comfort level
within our own area of responsibility. Our confidence level
is a product of experience, knowledge within our
domain of expertise, the number and severity of problems
we are facing, the amount of time we have to accomplish our
tasks, the quality of the information we are working with and
a whole bunch of other factors.
MBWA (Management By Walking Around) is often touted as
one of the most effective tools we have - this is a variation of it.
This technique is not much use at the level of
individual teams because it only reflects the general mood
of the team. Kind of like using someone’s watch to tell them
the time. However, at higher levels of management it should
be quite informative.
For example team A and team B are working on different applications that need to implement a similar feature. The feature in question relies on a database and the database is under the control of team B. Even though the user interfaces of the two applications are based on different technologies, the functionality is supposed to be roughly the same. Both teams have their own requirements and design documents. The functionality can be changed based on feedback from either team but then both teams have to update their requirement and design documents.
The teams are geographically distributed and members of each team itself are also geographically distributed. Both teams work with the same client entity but different people. Each team has their own business analyst (requirements specialist).
I am trying to make the technical communication between the teams more formal than email so that we can avoid misunderstandings.
How do you make sure that if team B changes the database and or the feature functionality, the other team gets properly notified about it? Do you use some formal text based documents such as interface contracts? Can you share any templates for those? Or do you use some other mechanism?
A couple of things from my own experience (which sounds very similar to yours)
You should try and have a single design document for the database part of the solution which as djna suggests should be posted on a wiki or similar, with a defined public contract for interaction with the data. This is a good step in the right direction, as it will give everybody a kind of 'shared vision' which helps people converge towards doing the right thing. The contracts should try to ensure that the data access is done in a standardised way.
However, from experience, the code does not always follow the spec exactly, so i would also assign a single owner from one of the teams, whose responsibility is the integration of both systems to the database.
i would then implement a continuous nightly build process with tests, and this build should include the database. This will hopefully flag any issues earlier in the process.
From the project i worked on, you may still have occasional disagreements and breakdowns, eventually we merged both teams. This was the best solution of all for us!!
Hope this helps a little
What about having a Team site (both as one team) or a Wiki so that both teams are aware of the change.
Regular stand-up meetings. Via a conference call. Stand-up == brief, highly focused, information centered. Delegate discussion to individual discussion outside meeting, reporting back at next.
There does need to be an overall authority though, to mediate where agreement cannot be reached and to ensure overall solution integrity.
I agree with Wiki or other collaborative site for publishing the current reality.
What's the point of using Fit/FitNesse instead of xUnit-style integration tests? It has really strange and very unclear syntax in my opinion.
Is it really only to make product owners write tests? They won't! It's too complicated for them. So why should anyone Fit/FitNesse?
Update So it's totally suitable for business-rules tests only?
The whole point is to work with non-programmers, often even completely non-technical people like prospect users of a business application, on what application should do and then put it into tests. While making tests work is certainly too complicated for them, they should be able to discuss tables of sample data filled out in e.g. Word. And the great thing is, unlike traditional specification, those documents live with your application because automated tests force you to update them.
See Introduction To Fit and Fit Workflow by James Shore and follow links to the rest of documentation if you want.
Update: Depends on what you mean by business rules? ;-) Some people would understand it very narrowly (like in business rules engines etc), others---very broadly.
As I see it, Fit is a tool that allows you to write down business (as in domain) use cases with rich realistic examples in a document, which the end users or domain experts (in some domains) can understand, verify and discuss. At the same time these examples are in machine readable form so they can be used to drive automated testing, You neither write the document entirely by yourself, nor requre them to do it. Instead it's a product of callaboration and discussion that reflects growing understanding of what application is going to do, on both sides. Examples get richer as you progress and more corner cases are resolved.
What application will do, not how, is important. It's a form of functional spec. As such it's rather broad and not really organized by modules but rather usage scenarios.
The tests that come out of examples will test external behavior of application in aspects important from business point of view. Yes, you might call it business rules. But lets look at Diego Jancic's example of credit scoring, just with a little twist. What if part of fit document is 1) listing attributes and their scores and then 2) providing client data and checking results, Then which are the actual business rules: scoring table (attributes and their scores) or application logic computing the score for each client (based on scoring table)? And which are tested?
Fit/FitNesse tests seem more suitable for acceptance testing. Other tests (when you don't care about cooperation with clients, users, domain experts, etc., you just want to automate testing) probably will be easier to write and maintain in more traditional ways. xUnit is nice for unit testing and api tests. Each web framework should have some tool for web app/service testing integrated in its modify-build-test-deploy cycle, eg. django has its little test client. You've lots to chose from.
And you always can write your own tool (or preferably tweak some existing) to better fit (pun intended) some testing in your particular domain of interest.
One more general thought. It's often (not always!!!) better to encode your tests, "business rules" and just about anything, in some form of well defined data that is interpreted by some simple, generic piece of code. Then it's easy to use the data in some other way: generate documentation, migrate to new testing framework, port application to new environment/programming language, use to check conformance with some external rules or other system (just use your imagination). It's much harder to pull such information out from code, eg. simple hardcoded unit tests or business rules.
Fit stores test cases as data. In very specific format because of how it's intended to be used, but still. Your domain specific tests may use different formats like simple CSV, JSON or YAML.
The idea is that you (the programmer) defines an easy to understand format, such as an excel sheet. Then, the product owner enters information that is hard to understand for people that is not in the business... and you just validate that your code works as the PO expects running Fit.
The way used in xUnit, can be used for programmers as an input for easy to understand or simple information.
If you're going to need to enter a lot of weird examples with multiple fields in your xUnit test, it will became hard to read.
Imagine a case where you have to decide whether to give a loan to a customer, based on the Age, Married/Single, Amount of Childrens, Wage, Activity, ...
As a programmer, you cannot write that information; and a risk manager cannot write a xUnit test.
Helps reduce redundancy in regression and bug testing. Build manageable repository of test cases. Its like build once and use for ever.
It is very useful during cooperation of the QA and devs teams: QA could show to developer the result of the failed test and a developer will easyly help to solve an environment issue and will understand steps for reproducing a bug.
It is suitable for UI and even for API testing.
In FogBugz 6, how do I represent the concepts of a "feature" versus a "task"? As defined by Joel Spolsky, the owner of Fog Creek Software (which makes FogBugz), a feature is essentially a user-visible capability. To estimate the time to implement a feature, the developer should break the implementation into short tasks (2 days max) to ensure they think about each step.
FogBugz has only cases. I can't tell whether they're supposed to correspond to features or tasks. Some FogBugz documentation indicates that each case is a task, which is fine except there is no way to group all the tasks for a given feature together. This is especially odd given that, before FogBugz 6, Joel advocated using a spreadsheet with that grouped all the tasks for each feature. But his own software doesn't appear to meaningfully support that grouping.
I realize that the Joel article I reference includes a disclaimer pointing to a later article. However, the later article does not settle this issue, in fact it doesn't discuss features versus tasks at all, which is surprising given how well Joel advocates for those concepts in the first article.
For FogBugz 6.0 and earlier:
Make a case for each work item (task). FogBugz calls them "Features," only to distinguish them from bugs, but you do want one case for each task.
The best way to group a bunch of tasks is to make a Release (Fix-For) and assign all of the tasks to that release.
Responding to AviD's comment/question to Joel:
So, if you have 10 new features coming
in the next version, with each feature
needing 5 tasks to implement, you
recommend creating 10 releases? And
how do I define that these are the
features/"releases" that are to be
included in the upcoming release?
Here is how we dealt with this specific problem in our development process:
First, we made a regular release schedule: monthly internal releases and quarterly external releases. This schedule never changes but task assignment / feature completion does. This is hugely important in terms of simplifying our inter-human communication: don't try to argue with the calendar.
Major features ("10 new features" in your example) are turned into cases (e.g., case 101 to case 110).
Each task that is a sub-component of a major feature also gets created as a sub-case with a description of what makes this chunk of work an important part of the larger picture. Previously, in Fogbugz 6, we used the "See also" feature by allowing it to search the text for us ("This is a sub-component of case 101" for example). This was effectively the same thing but less aesthetic.
Now that we've broken down the work to its finest level of usefulness, we bring the actual developers into the discussion. Each task and major feature is individually assigned to a particular developer.
The developer determines when they can get their assigned work done by picking the appropriate internal release date that they think they can commit to.
At this point, we have a rough sketch of what will get done for each release. Further refinements continue as the working people actually estimate the hours that they'll need to do the work, enabling evidence-based scheduling, etc.
For AviD's question, though, he would have the release-assignment problem solved by step 5 above.
However, I think point 6 is the most interesting as that's where you really get a solid schedule. For example, if developers are having trouble estimating a larger task, they break it down into sub-cases even further. Notice how my assessment of "finest level of usefulness" can differ (perhaps greatly) from the person who really needs to get the work done.
This is also a time when a developer can reach out to someone else and say "I can do most of this but it would really help if person X could help me with this little piece Y." This is actually where I get most of my development tasking: I personally sit in multiple places during this process, from large-scale planning meetings to little fiddly tasks that no-one else has time to do.
PS: Making it a personal goal to get this answer rated higher than Joel's.... ;-)
PPS: My original response is now overcome by events since Fogbugz 7 has lovely sub-tasks. Program managers love those reports.
You may have better luck asking your questions in the FogBugz Discussion Forum
We use a combination of projects in order to accomplish your grouping goals. We also commonly setup a project "parking" Wiki where links to development cases, technical documentation, systems requirements, user documentation, external links to resources etc. can all be placed. It provides a good "one-stop-shop" for everything related to that project.
As part of that Wiki, we would then setup two specific projects. One in relation to the large overall goals/outlines similar to what might correspond to your Project Management charts/whatnot. One in relation to the development tasks of each feature as they are broken down into the smaller and more manageable chunks. You can then, as was mentioned use case linking to both reference the "master" cases in the other project as well as reference the project Wiki itself so that you can quickly and easily get back to all of your project related information which is conveniently in one spot.
You can accomplish a pile of different organizational structures using FogBugz, you just have to approach things a little differently sometimes in order to hit each and every situation.
Hope that helps.
haha, that article has a disclaimer, but I understand what you are saying.
We use Fogbugz and the only 'Feature' that I am aware of is under category and I don't think you can associated it with sub-tasks.
You can type in 'Case N' is the feature for this task if you just wanted to reference it in the case text.
That kind of stuff sound like is lies more in the project management domain instead of software used to track bugs.
thats a good question, i have asked that myself, too..
we currently test-drive fogbugz for 45 days in a group of 5 developers, and we currently create a "release" for major features. in fact we do not release it, but multiple releases together when something is ready.
there should definately be some sort of advanced task grouping in fogbugz.