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Clayton Kershaw

San Francisco Giants

Los Angeles Dodgers left-hander Clayton Kershaw will take the mound on Saturday against the San Francisco Giants in what could be the final regular-season start at Dodger Stadium of his storied career.

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Dodgers' Clayton Kershaw aims to add to legendary career vs. Giants

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Big News Network.com

Sales

Digital art

20, and sold out within one hour for a total of 74.5 ETH ($168,434). Velocity Series_PER KRISTIAN STOVELAND The collection: Pursuit by Per Kristian Stoveland, launched in conjunction with the Japan Grand Prix,and holders of the original Velocity Pass NFT ...

Bybit And Digital Artist Per Kristian Stoveland Sell Out Exclusive Collection, Open Edition Sales Ongoing

Mena FN

Single

Masataka Yoshida hit a go-ahead RBI single that ended up being the Red Sox' winning run Friday night. Read more on Boston.com.

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Boston Red Sox

Chicago White Sox

Watch: Masataka Yoshida strokes go-ahead RBI single for the Red Sox in the eighth inning

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Boston.com

Speaking to reporters earlier in the day, Brent Rooker admitted he “would be lying” if he said the possibility of reaching 30 home runs this season was not something he was chasing. Based on how he’s swinging the bat these days,

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Rooker chases a 30 homer season with long ball vs. Detroit

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Rookies

Major League Baseball postseason

It'll be great to see stars like Ronald Acuña Jr., Freddie Freeman, Mookie Betts and Randy Arozarena back in the postseason. But the playoffs are a stage for rising stars to make a name for themselves,

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13 rookies ready for the October spotlight

Houston

The Squad

Former Webb City Cardinal and Missouri Southern pitcher Logan VanWey has shown the Houston Astros' front office enough to climb from Double-A to Triple-A. In his final three performances with the Corpus Christi Hooks,

VanWey called up to Houston's Triple-A squad

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Yahoo! Sports

Buck Showalter

The excitement was short-lived. Alec Bohm drove in the winning run and the Phillies handed the Mets a 5-4 loss in 10 innings.

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Brett Baty’s clutch homer not enough as Mets fall to Phillies in extra innings

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New York Daily News

Charlie Morton

Washington

Morton pitched to five batters in the bottom of the first inning, walking two with one strikeout. There was no obvious indication there was an injury - Morton's velocity was in the ballpark of his normal, with his seven fastballs averaging 93.9 versus a season average of 94.9. Morton threw 24 pitches in the first inning.

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Sports Illustrated

UPDATED: Charlie Morton leaves start early versus Washington

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Orion

Prospect

Orion Kerkering has spanned five levels of pro baseball in one season, which has given him plenty of time to talk to minor leaguers about their career aspirations. One thing he noticed was how specific their goals were.

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Major League Baseball

‘Don’t stress about promotions’: How Phillies prospect Orion Kerkering jumped from low A to the big leagues in one year

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Philadelphia Inquirer on MSN.com

Mars

Solar sail

A recent study submitted to Acta Astronautica and currently available on the arXiv preprint server explores the potential for using aerographite solar sails for traveling to Mars and interstellar space,

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Solar sails could reach Mars in just 26 days

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Phys.org

Get the most recent info and news about Velocity on HackerNoon, where 10k+ technologists publish stories for 4M+ monthly readers.

Velocity delivers a streamlined, single-source approach to managed services for over 15 years – continually earning the trust of its growing client base in the retail, hospitality and motion picture industries. With an in-house team of seasoned software development and engineering experts and numerous hardware and software design and utility patents, Velocity offers highly customized, customer-focused and best-in-class solutions, by integrating the latest technologies available into all its product offerings. Based in Holland, Ohio, right outside of Toledo, and founded in 2005, Velocity is a privately held company with approximately 500 employees. The company has nine redundant data centers, more than 5,500 certified technicians throughout the U.S., and 450 carrier agreements and is a CLEC in all 50 states. Further information can be found at www.velocitymsc.com.

Velocity

By Professional Scrum Trainer, , ILLIA Pavlichenko Scrum.org In this article, I will discuss the dangerous dynamic that can arise when a Product Owner, Scrum Master, or the management of an organization focuses a Development Team on velocity. What does velocity refer to? The concept of velocity signifies: The speed at which a Development Team converts Product Backlog Items into a Product Increment that is RELEASABLE. Pay particular attention to the highlighted word. Feature velocity is applicable when a Development Team can deliver an Increment that is releasable at least once per Sprint. In this case, Done = DoD = releasable. Awesome! But even in this case velocity does not show: Whether the client’s problem was resolved. Whether team is working on the highest priority problems. Amount of value delivered. Level of client satisfaction. Velocity only shows that the team was busy with something. But is this an accurate measure of the success of the products and services? Do the clients value products based on how busy company’s staff are? To put it another way, Velocity reflects the volume of a Development Team’s output. Unfortunately, this is not enough for the creation of successful products and services. The feature velocity of component teams = 0 Component teams have the most stable feature velocity. Because it always equals zero. Component teams are by definition not able to convert Product Backlog Items into value for a client. At a minimum they need integration with other component teams. When a team has Undone work In my opinion, the most dangerous dynamic arises in cases where a Development Team is not capable of generating a Product Increment that is releasable each Sprint. This means that Done = DoD + Undone and team optimizes just the part of the whole flow. Let us examine a system diagram that shows the link between the strength of DoD and organizational agility. The stronger the DoD, the smaller Undone work in the Sprint. Undone work limits the team regarding the number of potential releases, and, as a result, also regarding the amount of feedback that can be received from the market. The more feedback, the more decisions can be made by the Product Owner on the re-ordering of a Product Backlog. That could be called organizational agility — being able to quickly change the direction of a Product’s development. This may prompt a Scrum Team to undertake additional improvements to create an even stronger and more exhaustive DoD. d By strengthening the DoD, velocity decreases an becomes real How is the strengthening of a DoD reflected in velocity? The velocity will decrease at least in the short term. But this is not a problem if the goal is flow optimization (shortest Lead Time), learning and agility. Velocity decreases and becomes more real! But how likely is it that a Development Team would strengthen the DoD, if they know that team effectiveness is evaluated according to the velocity? My answer is unlikely. Focus on velocity keeps the team away from strengthening their DoD. As a result, that inhibits feedback from market, learning and agility. Focusing on velocity inhibits organizational agility. When I was a young and an inexperienced Scrum Master many years ago, I focused my teams on velocity excessively, which reduced their agility and increased the amount of Undone work. Nowadays, my advice to Scrum Masters who are just starting out goes something like this: Forget about velocity, if your team cannot produce an increment that is releasable at least every Sprint. Focus on strengthening your DoD first. What should we measure then? I recommend focusing on metrics that show the ability to deliver actual value to the market and satisfy client’s needs. For example, Scrum.org has developed framework , and is offering a range of metrics that shows: Evidence-Based Management A team’s ability to create value in the long term The speed at which value is generated (Time 2 Market). How much actual value is delivered to the market. n In conclusio I would like to repeat once more the fundamental idea that I want to convey with this article. The basic idea of a Scrum is to create an increment that is releasable at least every Sprint. If your team is already at that stage, then the concept of velocity is useful and genuinely demonstrates the speed at which a team converts Product Backlog Item elements into an increment. If not, please focus on strengthening Definition of Done (DoD) and flow optimization. The Article’s Main Ideas Velocity denotes the speed at which a Development Team converts Product Backlog Items into a Product Increment that is releasable. Velocity does not show whether clients’ problems are being resolved, nor whether value is being delivered, as reflects volume of output. Velocity only shows that a team was busy with something. The feature velocity of component teams is always zero. When team focuses on velocity and has Undone, it is unlikely they would strengthen the DoD. Focusing on velocity inhibits organizational agility. Focus on the value that is actually delivered to the market. Scrum ON! Originally published at agilix.nl on February 15, 2019.

Why focus on Velocity inhibits Agility

I don’t know about you — but when you talk about stocks, or markets, or funds — the general rule of thumb is: Past performance is not an indicator of future outcomes. Have you noticed that is software engineering, we tend to this advice? We tend to use our to our and our . We like to look at to determine what we can achieve within the . Why do we ignore this commonly accepted rule of thumb from finance? Are humans and our efforts really more predictable than a market? I don’t think so — but I’ll dig deeper. ignore current velocity calculate next velocity future velocities past performance next sprint/quarter/year Recording Velocity One of the things you’ll find most “ ” teams doing is recording . If it’s not the team, it’ll be the . It’s their job to give some security to a business and be able to say what they think they can while . Velocity is normally (from experience) regarded as the number of your team can get “ ” in a sprint. Basically, you record this over time to get to a point where you can predict what the deal will be able to achieve next sprint (and beyond). agile velocity PO (Product Owner) achieve minimizing risk story points done P.S. I put done in quotes because every team’s definition of done is different. Your team needs to figure this out for yourself. Some previous definition of done’s I’ve had are: Merged to master. QA tested. Deployed to live. Development finished. Story points? Story points are of the required for a story. They should be associated with a . Obviously, there are to every rule. When you’re first estimating, you’ll probably end up using . But it should be a direct conversion. Generally, I’ve used T-Shirt size estimates and sometimes they have numbers associated with those sizes. You add up all your story points done and that will give you the velocity for that week. very rough estimates effort never time exceptions days not one-to-one XS, S, M, L (after large, the stories should be broken up), XL, XXL, XXXL etc. 1, 2, 3, 5, 7, 13, etc. Is Velocity Meaningful? Normally, when a member joins a team (or leaves), it’ll probably take around for velocity to . Why’s that? Because it takes a time for a team to build and to measure their performance accurately for their products. So, while you can record velocity, it probably until your team builds the trust. That said, it is good to keep at it during this first six months to build up the trust in the numbers. But can you ever trust the numbers completely? They’re just rough guides remember. Some stories might have hidden complexity. Over time, your team will figure this out and your estimates will improve. 6 months stabilize long trust won’t mean anything Using Velocity — what does it mean? You can’t compare two teams’ velocities. It just won’t work. One team may and one team may . will have for the teams. So why would you even use them? In my team at Agoda, rather than the PO (Product Owner) say what will be completed in a quarter to management, we work the PO to determine our past quarter’s velocity and can use that to give an of what we’ll get done next quarter. This means that you have ample stories in the backlog estimated. underestimate overestimate Story points different meanings with approximation Now, this does not mean that you’ll work day and night to complete what you committed to. No. This means that you can manage expectations of management and the team. PO’s are always coming up with ideas and changing plans. Guess what? You can (based on your estimates) stories out of your commitments if your PO changes plans all the time. You can say “if you add this story — it will probably remove the bottom two from the quarterly goals. Are you okay with that?”. The PO will most likely answer yes and you aren’t stuck with unmanageable goals. kick To Sum it All Up is a funny metric that be across an organisation. You can to use velocity to future commitments and/or sprints, but that doesn’t mean that it’ll be 100% accurate. Plans change all the time. People will come and go from your teams. However, it can be useful to predict what features you might want to include and how to them. You should use story points and time to base your estimates. Story points should not be related to time, but to effort. Lastly, figure out what your “done” is. Velocity cannot consistent try predict roughly prioritise not Originally published at www.alexaitken.nz on July 9, 2018.

Past Velocity and Prediction

The Story-book of Science by Jean-Henri Fabre, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . THE VELOCITY OF SOUND CHAPTER XLII. THE VELOCITY OF SOUND “UNDER that big white cloud that you call cumulus,” said Emile, “there is at this very moment a storm. We have just seen the lightning and heard the thunder. Here, on the contrary, the sky is blue. So it does not rain everywhere at the same time. When rain is falling in one country, it is fine in others. And yet, when it rains here the whole sky is covered with clouds.” “You need only put your hand over your eyes to hide the sky,” his uncle explained. “A cloud much farther off, but also much larger, produces the same effect: it veils what is surrounding us and makes it all cloudy. But that is only in appearance; beyond the region covered by the cloud the sky may be serene and the weather magnificent. Under the cumulus where the thunder is growling now, it rains, you may be sure, and the sky looks black. To the people in that region the surroundings present only a rainy appearance, because they are wrapped in clouds; if they were to go elsewhere, beyond the clouds, they would find the sky as serene as we have it here.” “With a fast horse they could, then,” suggested Emile, “get from under the clouds, leave the rain, and come into fine weather; as also they could leave the sunshine and get into the rain under the clouds.” “Sometimes that would be possible, but more often not, because clouds can cover large areas. Besides, they travel, they go from one country to another, with such speed that the best horseman could not follow them in their course. You have all seen the shadow of the clouds run over the ground when the wind blows. Hills, valleys, plains, water-courses, all are crossed in less than no time. The shadow of a cloud passes over you at the moment you reach the top of a hill. Before you have taken three steps to descend into the valley, the shadow, with giant strides, is mounting the opposite slopes. Who could flatter himself that he could follow the cloud and keep under its cover? “If rain sometimes falls over great stretches of country, it is never general, absolutely. If it should rain at one time over a whole province, what is that compared with the earth? A clod compared with a large field. Chased by the wind, clouds run hither and thither in the vast spaces of the atmosphere. They travel, and on their way throw a shadow or precipitate rain. Where they pass there is rain; everywhere else, no. In the same place there can even be both rain and fine weather, according as one is below or above the clouds. You know that on a mountain-top the clouds are sometimes beneath one. The plain under the clouds may receive a hard shower, while on the summit the sun shines without a single drop of rain.” “All that is easily understood,” said Jules. “It is my turn now, Uncle, to ask you a question. From the storm-cloud that we see from here, there first came a flash of lightning; then, after waiting some time, the sound of the thunder was heard. Why do not the sound and the lightning come together?” “Two things tell us of the thunderbolt: light and noise. The light is the flash of the lightning, the noise is thunder. Likewise in the discharge of firearms there is the light produced by the ignition of the powder and the noise resulting therefrom. At the scene of the explosion light and noise are coincident; but for persons at a distance the light, which travels at an incomparably greater velocity, arrives before the sound, which moves more slowly. If you note the discharge of a gun a considerable distance away, you see first the flash and smoke of the explosion, and do not hear the report until some time after; the more distant the explosion, the longer the time. Light travels an immense distance in an exceedingly short time. The flash of the explosion, therefore, reaches the eye at the very instant of its occurrence. If the sound does not arrive until after, it is because it travels much less rapidly and, in order to cover a considerable distance, requires considerable time, which is easily measured. “Suppose ten seconds pass between the flash of a cannon’s discharge and the arrival of the sound. The distance is measured between the place where the explosion occurred and that where it was heard. It is found to be 3400 meters. Sound, therefore, moves through the air, in a single second, a distance of 340 meters. That is a good rate of speed, comparable with that of the cannon-ball, but nothing, after all, in comparison with the inconceivable velocity of light. “The unequal rapidity with which sound and light travel accounts for the following fact. From a distance a wood-cutter is seen chopping wood, or a mason cutting stone. We see the ax strike the wood, the mallet tap the stone, and some time after we hear the sound.” Bells Ringing “One Sunday before church,” interposed Jules, “I was watching from a distance the ringing of the bell. I saw the tongue strike and the sound did not come until later. Now I see the reason.” “If you count the number of seconds between the appearance of the flash and the instant the thunder begins to be heard, you can tell what distance you are from the storm-cloud.” “Is a second very long!” Emile asked. “It is about the length of one beat of the pulse. All we have to do, then, is to count, one, two, three, four, etc., without haste, but not too slowly, to have about the number of seconds. Note the instant the flash lights up the stormy cumulus, and count slowly until you hear the thunder.” With watchful eye and attentive ear all began the observation. Finally a flash was seen. They counted, the uncle beating time. One—two—three—four—five—At twelve came the thunder, but so faint that they could only just hear it. “It took twelve seconds for the sound of the thunder to reach us,” said Uncle Paul. “From what distance does it come, if sound travels 340 meters a second?” “You must multiply 340 by twelve,” replied Claire. “Well, Miss, do it.” Claire made the calculation. The result was 4080 meters. “The flash of lightning was 4080 meters away; we are more than a league from the storm-cloud,” said her uncle. “How easy that is!” exclaimed Emile. “You count one, two, three, four, and without moving you know how far away the thunderbolt has just fallen.” “The longer the time between the flash and the noise, the farther away is the cloud. When the report comes at the same time as the flash, the explosion is quite near. Jules knows that well since the day of the storm in the pine woods.” “I have heard that there is no longer any danger after the lightning is seen,” said Claire. “A thunderbolt is as rapid as light. An electric explosion is, therefore, ended as soon as the flash appears, and all danger is then passed; for the thunder, however loud it may be, can do no harm.” About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Jean-Henri Fabre (2018). The Story-book of Science. Urbana, Illinois: Project Gutenberg. Retrieved https://www.gutenberg.org/cache/epub/56795/pg56795-images.html This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html.

THE VELOCITY OF SOUND

The A B C of Relativity by Bertrand Russells, is part of the HackerNoon Books Series. You can jump to any chapter in this book here . III. THE VELOCITY OF LIGHT III. THE VELOCITY OF LIGHT Most of the curious things in the theory of relativity are connected with the velocity of light. If the reader is to grasp the reasons for such a serious theoretical reconstruction, he must have some idea of the facts which made the old system break down. The fact that light is transmitted with a definite velocity was first established by astronomical observations. Jupiter’s moons are sometimes eclipsed by Jupiter, and it is easy to calculate the times when this ought to occur. It was found that when Jupiter was unusually near the earth an eclipse of one of his moons would be observed a few minutes earlier than was expected; and when Jupiter was unusually remote, a few minutes later than was expected. It was found that these deviations could all be accounted for by assuming that light has a certain velocity, so that what we observe to be happening in Jupiter really happened a little while ago—longer ago when Jupiter is distant than when it is near. Just the same velocity of light was found to account for similar facts in regard to other parts of the solar system. It was therefore accepted that light in vacuo always travels at a certain constant rate, almost exactly 300,000 kilometers a second. (A kilometer is about five-eighths of a mile.) When it became established that light consists of waves, this velocity was that of propagation of waves in the ether—at least they used to be in the ether, but now the ether has grown somewhat shadowy, though the waves remain. This same velocity is that of the waves used in wireless telegraphy (which are like light waves, only longer) and in X-rays (which are like light waves, only shorter). It is generally held nowadays to be the velocity with which gravitation is propagated, though Eddington considers this not yet certain. (It used to be thought that gravitation was propagated instantaneously, but this view is now abandoned.) So far, all is plain sailing. But as it became possible to make more accurate measurements, difficulties began to accumulate. The waves were supposed to be in the ether, and therefore their velocity ought to be relative to the ether. Now since the ether (if it exists) clearly offers no resistance to the motions of the heavenly bodies, it would seem natural to suppose that it does not share their motion. If the earth had to push a lot of ether before it, in the sort of way that a steamer pushes water before it, one would expect a resistance on the part of the ether analogous to that offered by the water to the steamer. Therefore the general view was that the ether could pass through bodies without difficulty, like air through a coarse sieve, only more so. If this were the case, then the earth in its orbit must have a velocity relative to the ether. If, at some point of its orbit, it happened to be moving exactly with the ether, it must at other points be moving through it all the faster. If you go for a circular walk on a windy day, you must be walking against the wind part of the way, whatever wind may be blowing; the principle in this case is the same. It follows that, if you choose two days six months apart, when the earth in its orbit is moving in exactly opposite directions, it must be moving against an ether wind on at least one of these days. Now if there is an ether wind, it is clear that, relatively to an observer on the earth, light signals will seem to travel faster with the wind than across it, and faster across it than against it. This is what Michelson and Morley set themselves to test by their famous experiment. They sent out light signals in two directions at right angles; each was reflected from a mirror, and came back to the place from which both had been sent out. Now anybody can verify, either by trial or by a little arithmetic, that it takes longer to row a given distance on a river upstream and then back again, than it takes to row the same distance across the stream and back again. Therefore, if there were an ether wind, one of the two light signals, which consist of waves in the ether, ought to have traveled to the mirror and back at a slower average rate than the other. Michelson and Morley tried the experiment, they tried it in various positions, they tried it again later. Their apparatus was quite accurate enough to have detected the expected difference of speed or even a much smaller difference, if it had existed, but not the smallest difference could be observed. The result was a surprise to them as to everybody else; but careful repetitions made doubt impossible. The experiment was first made as long ago as 1881, and was repeated with more elaboration in 1887. But it was many years before it could be rightly interpreted. The supposition that the earth carries the neighboring ether with it in its motion was found to be impossible, for a number of reasons. Consequently a logical deadlock seemed to have arisen, from which at first physicists sought to extricate themselves by very arbitrary hypotheses. The most important of these was that of Fitzgerald, developed by Lorentz, and known as the Fitzgerald contraction hypothesis. According to this hypothesis, when a body is in motion it becomes shortened in the direction of motion by a certain proportion depending upon its velocity. The amount of the contraction was to be just enough to account for the negative result of the Michelson-Morley experiment. The journey up stream and down again was to have been really a shorter journey than the one across the stream, and was to have been just so much shorter as would enable the slower light wave to traverse it in the same time. Of course the shortening could never be detected by measurement, because our measuring rods would share it. A foot rule placed in the line of the earth’s motion would be shorter than the same foot rule placed at right angles to the earth’s motion. This point of view resembles nothing so much as the White Knight’s “plan to dye my whiskers green, and always use so large a fan that they could not be seen.” The odd thing was that the plan worked well enough. Later on, when Einstein propounded his special theory of relativity (1905), it was found that the theory was in a certain sense correct, but only in a certain sense. That is to say, the supposed contraction is not a physical fact, but a result of certain conventions of measurement which, when once the right point of view has been found, are seen to be such as we are almost compelled to adopt. But I do not wish yet to set forth Einstein’s solution of the puzzle. For the present, it is the nature of the puzzle itself that I want to make clear. On the face of it, and apart from hypotheses ad hoc, the Michelson-Morley experiment (in conjunction with others) showed that, relatively to the earth, the velocity of light is the same in all directions, and that this is equally true at all times of the year, although the direction of the earth’s motion is always changing as it goes round the sun. Moreover, it appeared that this is not a peculiarity of the earth, but is true of all bodies: if a light signal is sent out from a body, that body will remain at the center of the waves as they travel outwards, no matter how it may be moving—at least, that will be the view of observers moving with the body. This was the plain and natural meaning of the experiments, and Einstein succeeded in inventing a theory which accepted it. But at first it was thought logically impossible to accept this plain and natural meaning. A few illustrations will make it clear how very odd the facts are. When a shell is fired, it moves faster than sound: the people at whom it is fired first see the flash, then (if they are lucky) see the shell go by, and last of all hear the report. It is clear that if you could put a scientific observer on the shell, he would never hear the report, as the shell would burst and kill him before the sound had overtaken him. But if sound worked on the same principles as light, our observer would hear everything just as if he were at rest. In that case, if a screen, suitable for producing echoes, were attached to the shell and traveling with it, say a hundred yards in front of it, our observer would hear the echo of the report from the screen after just the same interval of time as if he and the shell were at rest. This, of course, is an experiment which cannot be performed, but others which can be performed will show the difference. We might find some place on a railway where there is an echo from a place further along the railway—say a place where the railway goes into a tunnel—and when a train is traveling along the railway, let a man on the bank fire a gun. If the train is traveling towards the echo, the passengers will hear the echo sooner than the man on the bank; if it is traveling in the opposite direction, they will hear it later. But these are not quite the circumstances of the Michelson-Morley experiment. The mirrors in that experiment correspond to the echo, and the mirrors are moving with the earth, so that echo ought to move with the train. Let us suppose that the shot is fired from the guard’s van, and the echo comes from a screen on the engine. We will suppose the distance from the guard’s van to the engine to be the distance that sound can travel in a second (about one-fifth of a mile), and the speed of the train to be one-twelfth of the speed of sound (about sixty miles an hour). We now have an experiment which can be performed by the people in the train. If the train were at rest, the guard would hear the echo in two seconds; as it is, he will hear it in 2 and ²/₁₄₃ seconds. From this difference, if he knows the velocity of sound, he can calculate the velocity of the train, even if it is a foggy night so that he cannot see the banks. But if sound behaved like light, he would hear the echo in two seconds however fast the train might be traveling. Various other illustrations will help to show how extraordinary—from the point of view of tradition and common sense—are the facts about the velocity of light. Every one knows that if you are on an escalator you reach the top sooner if you walk up than if you stand still. But if the escalator moved with the velocity of light (which it does not do even in New York), you would reach the top at exactly the same moment whether you walked up or stood still. Again: if you are walking along a road at the rate of four miles an hour, and a motor-car passes you going in the same direction at the rate of forty miles an hour, if you and the motor-car both keep going the distance between you after an hour will be thirty-six miles. But if the motor-car met you, going in the opposite direction, the distance after an hour would be forty-four miles. Now if the motor-car were traveling with the velocity of light, it would make no difference whether it met or passed you: in either case, it would, after a second, be 186,000 miles from you. It would also be 186,000 miles from any other motor-car which happened to be passing or meeting you less rapidly at the previous second. This seems impossible: how can the car be at the same distance from a number of different points along the road? Let us take another illustration. When a fly touches the surface of a stagnant pool, it causes ripples which move outwards in widening circles. The center of the circle at any moment is the point of the pool touched by the fly. If the fly moves about over the surface of the pool, it does not remain at the center of the ripples. But if the ripples were waves of light, and the fly were a skilled physicist, it would find that it always remained at the center of the ripples, however it might move. Meanwhile a skilled physicist sitting beside the pool would judge, as in the case of ordinary ripples, that the center was not the fly, but the point of the pool touched by the fly. And if another fly had touched the water at the same spot at the same moment, it also would find that it remained at the center of the ripples, even if it separated itself widely from the first fly. This is exactly analogous to the Michelson-Morley experiment. The pool corresponds to the ether; the fly corresponds to the earth; the contact of the fly and the pool corresponds to the light signal which Messrs. Michelson and Morley send out; and the ripples correspond to the light waves. Such a state of affairs seems, at first sight, quite impossible. It is no wonder that, although the Michelson-Morley experiment was made in 1881, it was not rightly interpreted until 1905. Let us see what, exactly, we have been saying. Take the man walking along a road and passed by a motor-car. Suppose there are a number of people at the same point of the road, some walking, some in motor-cars; suppose they are going at varying rates, some in one direction and some in another. I say that if, at this moment, a light flash is sent out from the place where they all are, the light waves will be 186,000 miles from each ne of them after a second by his watch, although the travelers will not any longer be all in the same place. At the end of a second by your watch it will be 186,000 miles from you, and it will also be 186,000 miles from a person who met you when it was sent out, but was moving in the opposite direction, after a second by his watch—assuming both to be perfect watches. How can this be? There is only one way of explaining such facts, and that is, to assume that watches and clocks are affected by motion. I do not mean that they are affected in ways that could be remedied by greater accuracy in construction; I mean something much more fundamental. I mean that, if you say an hour has elapsed between two events, and if you base this assertion upon ideally careful measurements with ideally accurate chronometers, another equally precise person, who has been moving rapidly relatively to you, may judge that the time was more or less than an hour. You cannot say that one is right and the other wrong, any more than you could if one used a clock showing Greenwich time and another a clock showing New York time. How this comes about, I shall explain in the next chapter. There are other curious things about the velocity of light. One is, that no material body can ever travel as fast as light, however great may be the force to which it is exposed, and however long the force may act. An illustration may help to make this clear. At exhibitions one sometimes sees a series of moving platforms, going round and round in a circle. The outside one goes at four miles an hour; the next goes four miles an hour faster than the first; and so on. You can step across from each to the next; until you find yourself going at a tremendous pace. Now you might think that, if the first platform does four miles an hour, and the second does four miles an hour relatively to the first, then the second does eight miles an hour relatively to the ground. This is an error; it does a little less, though so little less that not even the most careful measurements could detect the difference. I want to make quite clear what it is that I mean. I will suppose that, in the morning, when the apparatus is just about to start, three men with ideally accurate chronometers stand in a row, one on the ground, one on the first platform, and one on the second. The first platform moves at the rate of four miles an hour with respect to the ground. Four miles an hour is 352 feet in a minute. The man on the ground, after a minute by his watch, notes the place on the ground opposite the man on the first platform, who has been standing still while the platform carried him along. The man on the ground measures the distance on the ground from himself to the point opposite the man on the first platform, and finds it is 352 feet. The man on the first platform, after a minute by his watch, notes the point on his platform opposite to the man on the second platform. The man on the first platform measures the distance from himself to the point opposite the man on the second platform; it is again 352 feet. Problem: how far will the man on the ground judge that the man on the second platform has traveled in a minute? That is to say, if the man on the ground, after a minute by his watch, notes the place on the ground opposite the man on the second platform, how far will this be from the man on the ground? You would say, twice 352 feet, that is to say, 704 feet. But in fact it will be a little less, though so little less as to be inappreciable. The discrepancy is owing to the fact that the two watches do not keep perfect time, in spite of the fact that each is [Pg 42]accurate from its owner’s point of view. If you had a long series of such moving platforms, each moving four miles an hour relatively to the one before it, you would never reach a point where the last was moving with the velocity of light relatively to the ground, not even if you had millions of them. The discrepancy, which is very small for small velocities, becomes greater as the velocity increases, and makes the velocity of light an unattainable limit. How all this happens, is the next topic with which we must deal. Note. The negative result of the Michelson-Morley experiment has recently been called in question by Professor Dayton C. Miller, as a result of observations by what is said to be an improved method. His claim is set forth by Professor Silberstein in Nature, May 23, 1925, and discussed unfavorably by Eddington in the issue of June 6. The matter is sub judice, but it seems highly questionable whether the results bear out the interpretation which is put upon them. About HackerNoon Book Series: We bring you the most important technical, scientific, and insightful public domain books. This book is part of the public domain. Bertrand Williams (2004). THE A B C OF RELATIVITY. Urbana, Illinois: Project Gutenberg. Retrieved October 2022, from https://www.gutenberg.org/files/67104/67104-h/67104-h.htm This eBook is for the use of anyone anywhere at no cost and with almost no restrictions whatsoever. You may copy it, give it away or re-use it under the terms of the Project Gutenberg License included with this eBook or online at www.gutenberg.org , located at https://www.gutenberg.org/policy/license.html .

The Velocity of Light 

Interest rates increased by 157%! No, I'm not talking about the Fed's latest decision but about the slowdown, Fictional Inc. faced after releasing version 3.0 of their platform. Fortunately for them, the product release was incredibly successful, and they're starting to see revenue growth quickly picking up, but they now need to think about how they're going to deal with their technical debt they introduced as part of the release. The new tech debt that's been introduced as part of a new release can be thought of as increasing the interest rate and increasing the slowdown the team faces in the future. (I'm going to assume you're fairly familiar with the concept of technical debt here, but if you need a refresher to get up to speed here's a quick ) primer Ok, you’re probably not going to hear an engineering manager talk like this about their technical debt. But why not? Being able to measure and quantify the ongoing impact of your if you want to put together an actionable plan to address it. tech debt is critical When we think about technical debt, the is the amount of time lost on current and future development to your existing levels of technical debt. interest This means it's the critical piece of the debt to consider when thinking about future decisions to pay back the (the cost of rewriting, refactoring, or fixing the code responsible for the debt) - since we'll only ever consider it if the interest is high enough. principal What's a Healthy Level of Technical Debt? Technical debt clearly slows down new development - but that on its own doesn't mean that we should be fixing tech debt everywhere. Going back to rewrite or refactor existing code can be significantly costly - so we only want to pay back our technical debt principal if our interest (the amount it's slowing us down moving forward) exceeds our principal. One obvious problem immediately crops up - the principal is a fixed unit of time (hours to fix/rewrite) but the interest is a rate of hours lost per time. To account for this we need to introduce the idea of an - the time over which we care about whether the future slowdowns from technical debt exceeds the cost of the rewrite. The impact interval you care about will be heavily dependent on your company, your typical planning process, and its stage or the lifecycle of your codebase - but I'll personally usually look at a 3 month impact interval. At our early stage as a company, looking at anything in year-long + timescales is too broad, but anything shorter than 2–3 months will heavily underestimate the impact of technical debt as we'll see later. impact interval This means that our level of tech debt is not worth addressing if: For example: if we had a small project that we knew had tech debt that slowed us down by 2 hour/week, it would take us 4 days to refactor away that debt, and care about a 3 month impact interval then we wouldn't spend the time to pay off that debt yet. Now, this doesn't actually answer the level of what is a healthy level of technical debt - because I think we can all agree that facing huge slowdowns on the team isn't healthy. Instead we now have a quick way to determine when we should or shouldn't focus on rewriting and refactoring. We'll take a look at what a healthy level of debt actually is a bit later in the article. How Do We Measure Technical Debt? Determining our tech debt interest rate requires us to figure out how much we are being slowed down by different decisions we've made. Unfortunately, there's not an obvious or trivial way to track how much your development is being slowed down - but there are three different approaches you can take to get good approximations. Velocity Based Measurement The most direct way to tie slowdowns to different sections of our codebase is to look at how velocity varies over time, across different sections of your project. Looking across different areas of the codebase you can start to identify variations (eg. any development touching this analysis section takes 3x as long as anything else) across the different sections. Looking at the variation of an area over time also can give you some indication of how new development has impacted the rate of future development and gives an indication of the level of interest your team is dealing with. For example: If we have a relatively simple project with 4 different areas that we'll work on then we can look at how the velocity changes over time (here we're tracking velocity in story points/developer month). Velocity Based Measurement of Technical Debt's Impact From here we can see that D has always taken ~3x as long to work on as any of the other areas for similarly complex tasks. This implies that it has 3x the interest as all of the other sections of the codebase. B used to be relatively on par with A & C, but starting in month 4 it all of a sudden jumped up to take 2x the time. This suggests that we introduced some debt here that's doubled our interest rate vs what it was before for B. One thing to call out is that we're not talking about the interest rate for the entire codebase, but instead interest rate for individual components/areas - that's because the slowdowns that are introduced by build ups in technical debt aren't issues that affect everything that we do, instead they're localized to one part of the codebase. usually There are some important caveats to think about when it comes to velocity based measurement. Velocity can be volatile and can depend on factors independent of technical debt like new (or existing) bugs, mis-aligned estimations, technical hurdles, or external project delays. Estimations have a level of inherent uncertainty and can be an inaccurate measure to begin with. Gathering and analyzing this data can be tricky and time consuming. One quick proxy for velocity based measurement is to ask your engineering team to estimate relatively how long it takes to complete a project/task in each major area of your codebase. Agree on some established baseline for a well understood/frequently used area and then have everyone estimate each other area as a percentage or multiple of that baseline. While not quite as rigorous as a full velocity based measurement approach it can give a quick idea of your relative tech debt interest based on your team's insight and intuition. Issue Based Measurement A different approach is to identify specific instances of technical debt within your project and estimate how much they may be each slowing you down. Part of this can be done by using automated tools, such as static analysis tools, to find common issues around code quality that may have impacts on readability, extendability, or maintainability of a project. For each type of issue you can assign it an interest cost (eg. 5 min/week or 1%) based on your team's experience in dealing with these types of issues. But, this will only capture a subset of technical debt causing issues - others will be more subtle or more bespoke to your codebase and will only be observed while your team is actively working on that area of the code. In this instance, you'll want to record the specific issue (tied to an area of your codebase) along with the estimated impact it has in slowing down development. For tracking these issues we recommend using some sort of issue tracker - either in an issue backlog in GitHub, Jira, etc or using a purpose built tech debt issue tracker like . Stepsize Some of the drawbacks to this approach are: The time estimations tied to specific issues can be inaccurate Some issues can easily go undetected for a long period of time Quality Based Measurement There are a variety of code quality metrics that you can use to get an overall sense of the status of your codebase and, in turn, get an estimate of how much technical debt you currently have impacting future development in each area. At Sourcery, we tend to look at , , and Method Length as the critical metrics when looking within a function or class - but you can also look at things like Maintainability Index, Doc & Test Coverage, Duplication Rate, and many others. Complexity Working Memory Similar to the Issue based approach, you can assign a relative impact of different scores (or of an overall quality or health score) to the ongoing and future slowdown in development due to technical debt. Research has shown strong negative correlation between things like Complexity & Velocity as well as with code quality and bug risk, maintenance load, and more. Looking at an example - let's revisit the simple 4 part codebase we looked at in the section on Velocity Based Measurement. We can easily see the problem sections of this project in the table (highlighted in red) and calculating the Interest estimate is relatively straightforward - simply sum up the interest impacts of the different components. Some of the drawbacks to this approach are: You need to define Interest impact estimates on different quality metrics (I'm looking to put some together as a baseline, but it will be fairly codebase dependent). To do this you'll probably want to look at some velocity based measurement and tie that to quality. Quality metrics themselves are imperfect and can . vary significantly from language to language This quality based measurement approach is the least precise of the three approaches we've looked at - but it's very effective at giving a holistic look at different areas of your project over time. You can combine this approach with the issue based approach we just discussed to balance tracking specific issues alongside tracking general quality and health issues across each section of your project. Looking at Codebase Interaction Frequency For all three of these approaches we need to have a way to map impact in different sections of our codebase against the frequency with which we actually touch that section of the codebase. If there is a section of our project which is a nightmare to deal with but which no one ever touches any more then it's not actually heavily impacting our ongoing technical debt. Conversely, a small but persistent slowdown on a section of the codebase that's contributed to every day can result in huge time losses very quickly. To account for this we'll need to look at how often each area of our project is contributed to. There are a few different approaches we can take here - looking at the Git history to understand which area is broadly touched most often, using more focused tooling like to get more digestible historical contribution data, or using a forward facing approach by looking at our upcoming plans and priorities to understand where our team will be spending most of their time over the next several months. Codescene Regardless of how we get the data - we can then get a breakdown of what percentage of our time we will be spending interacting with each section of our codebase. Combining this together with the Interest contribution that we've already determined we can now see exactly how much we expect to be slowed down by when dealing with each section of our codebase moving forward. Continuing on our example from earlier - if we took a forward facing view and new all of the projects we were going to work on in the next 3 months and could confidently estimate that this was the amount of time spent in each area of the codebase (remember this is a very simple project): We now can tie that back to the Interest estimates we had from our Velocity Based approach and our Quality Metric Based approach and get a good idea of where we're being slowed down the most. Here we're using the slowdowns in velocity we saw for work on sections B & C from when we looked at velocity-based measurement earlier and are using that to calculate how much lost time we expect due to tech debt in the next three months. Overall we expect to see more than 28 developer months worth of effort extra to be spent just on the debt. An important thing to consider from this approach is that all of this is looking at relative velocity - so the baseline projects are treated as having effectively no debt, which isn't normally accurate. The other issue with this approach is that it doesn't take into account variations in future debt levels - which are likely to occur. But they're hard to predict, so it is easier to disregard them. Here we've taken our the typical projected delays based on the code quality of each section and projected that out over the next three months. Across the board we see significantly lower debt impact projections than when we used the velocity method. This is because the slowdown estimates based on tech debt are lower than what we were seeing in the velocity case - we might need to do some more calibrating in this case! Just as with the velocity based metric this isn't taking into account future changes in tech debt - but both estimates can help us determine how we should prioritize rewriting and refactoring the different sections of our project. Managing Interest and Debt We've looked at a few different ways to account for how much our technical debt is impacting us on an ongoing basis, but we haven't fully answered the question as to what's a healthy level of technical debt. Unfortunately, there isn't really a precise number. In the short term, accepting some debt might be pragmatic. But, in the long run we'll want to aim to keep our debt close to zero. Because lingering interest is going to prove very costly and tech debt keeps building upon itself. But, we don't want to be spending all of our time refactoring and rewriting issues that give us only marginal gains. As we discussed earlier we generally don't want to spend time addressing areas of the codebase where: But, at the extreme case of this we could wind up with a case where we're massively slowed down by a high level of debt that is extremely costly to fix - which isn't a good situation either. The best approach is to fall somewhere in the middle. Set aside time in your ongoing planning to address technical debt issues and refactor existing code - prioritizing by what is currently the costliest to you. And continue to push that until you see significant diminishing returns from reducing your debt.

Tech Debt Calculation: Velocity-Based Vs. Issue-Based Vs. Quality-Based Measurements Explained

Cálculo de la deuda tecnológica: basado en la velocidad vs. Basado en problemas vs. Explicación de las mediciones basadas en la calidad

Calcul de la dette technologique : Vs basé sur la vélocité. Vs basés sur les problèmes. Mesures basées sur la qualité expliquées

टेक ऋण गणना: वेग-आधारित बनाम। मुद्दा-आधारित बनाम। गुणवत्ता-आधारित मापन समझाया गया

技術的負債の計算: 速度ベースの対。問題ベースの対。品質ベースの測定の説明

Cálculo da dívida técnica: baseado em velocidade vs. Com base em questões vs. Medições baseadas na qualidade explicadas

Tính toán nợ công nghệ: Dựa trên tốc độ Vs. Dựa trên vấn đề Vs. Giải thích các phép đo dựa trên chất lượng

技术债务计算：基于速度的对比。基于问题的对比。基于质量的测量解释

In the previous article, we looked at the . But how do we measure our velocity to know how long each sprint is going to take and plan ahead? Sprint Velocity Best Practices In this guide, we’re going to dive into: What is sprint velocity? What formulas you can use to measure it? 3 mistakes to avoid when measuring sprint velocity What Is Sprint Velocity? The Agile management framework is based around sprints — short periods of work, moving towards a specific goal. measures the amount of work your can complete within the average sprint. Sprint velocity scrum team There are several different ways to count sprint velocity. You could find the average number of , the average , or even the . The higher the score, the more your team is getting done. story points hours of work done number of ideal days Why Does Sprint Velocity Matter? When you create a roadmap for developing your product, it’s common to set a target date for each major stage. But how do you know what is achievable? Sprint velocity , and how many sprints it will take to reach bigger goals. In turn, this can inform your estimated delivery dates. helps you estimate what you can feasibly get done within each sprint Sprint velocity metrics are also very informative when it comes to productivity. By tracking the velocity of your team over time, you can or spending too much time comparing notes on the latest Wordle. see whether you are becoming more efficient How Do You Measure Sprint Velocity? While sprint velocity is based on data, it’s more of an estimate than a hard figure. To come up with a meaningful number, you need to track the amount of work done in at least five sprints. Then, you can plug your data into one of these sprint velocity formulas: 1) Sprint Velocity in Story Points Measuring sprint velocity via story points is a good idea, because these units take into account the complexity of work done, not just the time spent on the job. To find your sprint velocity, add up all the completed user stories within each sprint. Then, multiply this figure by the number of story points required for each user story: 5 user stories × 8 story points = 40 story points (Total) In this case, the team completed five user stories. Each of those user stories involved eight story points worth of work. To find your sprint velocity, repeat this process for multiple previous sprints and then find the average: Sprint 1: 36 story points Sprint 2: 40 story points Sprint 3: 38 story points 36 story points + 40 story points + 38 story points = 114 story points 114 story points ÷ 3 sprints = 38 story points/sprint (average) In this case, your sprint velocity is 38 story points per sprint on average. Not bad! 2) Sprint Velocity in Hours If you prefer to use a more traditional metric, you can just as easily calculate sprint velocity in hours. In this case, find the number of hours your team spent on each sprint: Sprint 1: 360 hours Sprint 2: 356 hours Sprint 3: 400 hours Then, add all your hours together and divide by the number of sprints to get your average sprint velocity: 360 hrs + 356 hrs + 400 hrs = 1,116 hours 1116 hours ÷ 3 sprints = 372 hours/sprint (average) For more granular statistics, you can perform the same calculation to find sprint velocity per story. 3) Sprint Velocity in Story Points and Ideal Days An alternative method for measuring sprint velocity is using ideal days. This option is , rather than the performance of your entire team. better suited to analyzing the performance of individuals The calculation for this metric builds on the one mentioned above. First, you need to find out how many hours were completed in each sprint. Next, you need to divide the number of hours of work completed by the number of hours in an ideal day. Sprint: 42 hours Ideal day: 8 hours 42 hrs ÷ 8 hrs = 5.25 ideal days Finally, we can add together the number of ideal days completed in all the sprints, and divide this figure by the number of sprints. Sprint 1: 5.25 ideal days Sprint 2: 4.5 ideal days Sprint 3: 6 ideal days 5.25 ideal days + 4.5 ideal days + 6 ideal days = 15.75 ideal days 15.75 ideal days ÷ 3 sprints = 5.25 ideal days/sprint (average) If you don’t want to run through the numbers yourself you can plug your data into this . free sprint velocity calculator What Is the Best Way to Visualise Sprint Velocity? So far, we have looked at how you can estimate your sprint velocity from recent sprints. However, this figure only becomes truly useful when you have something to compare it with. Here are two common ways that Scrum teams track their sprint velocity over time: 1) Sprint Velocity Chart Perhaps the easiest way to track your productivity is with a . This is a simple graph that shows how your average changes over time. sprint velocity chart To add some extra context, you can also include the expected amount of work for each sprint. This will reveal whether your team is consistently hitting expectations, or falling short. It will also give you a sense of how to adjust your future estimated workloads. 2) Sprint Velocity Burndown Charts When you’re on a tight deadline, you might want to keep an extra close eye on your sprint velocity. show you how much work you have completed, how much work is still outstanding, and how much time you have left to get it done. Burndown charts While this option is a little more complicated to set up, it provides a really helpful overview for project managers. In one glance, they can clearly see if the team is on schedule or lagging behind. Image credit: Wikipedia 3 mistakes to avoid when measuring sprint velocity 1) Not taking technical debt into account is the silent velocity killer. To measure sprint velocity, you need to ensure that you know your codebase problems well. Technical debt Track and prioritize your technical debt regularly to see which parts of the code can be problematic and will affect your team velocity. The easiest way to do it is to use the Stepsize and extensions. They’ll help your Engineers see issues in the codebase and report them directly from their editor reducing context switching. VSCode JetBrains 2) Using velocity to measure the performance of a team The main goal of measuring sprint velocity is to plan future sprints and report estimations, not measuring your team performance. As says, “When a measure becomes a target, it ceases to be a good measure.” So don’t compare your teams’ velocity and find other . Goodhart’s metrics for your team performance 3) Focusing on the numbers too much Make the quality of your code your main focus. When you feel like you should be getting more done in the week, a natural reaction might be to increase your working hours. While this may work for an individual sprint, it’s not going to provide long-term improvement. It can also lead to burnout in your team. Try to . Encourage your team to get things right the first time, even if it takes a little longer. In the long run, this will actually save a lot of rework and improve your . focus on quality code quality Take Control of Your Sprint Velocity As we have discovered, sprint velocity is an important metric. There are many different ways to measure it, and even more ways to improve it. Here’s what we have learned: Sprint velocity is a good measure of productivity You can measure it in story points, hours, or ideal days It’s best tracked using regular charts or burndown charts To improve your sprint velocity, focus on quality and not quantity Follow these steps, and you might be surprised just how much your team can get done in your next sprint! Also Published Here

Measuring Sprint Velocity

With much of the DevOps stack having matured and good practices becoming more mainstream, the need for quality in software has quickly become a central issue. This article is the first in a series in which we’ll shine the spotlight on software quality from a DevOps context. Introduction Trends have companies focused on customer experience as a way to differentiate themselves from their competitors. However, it seems that one of the worst-kept secrets in the software industry that is still one of the most reliable ways to differentiate your company from your competitors. If your product is constantly breaking and your competitors are more reliable and have comparable functionality, your organization will eventually run out of customer goodwill. quality Also, there are high costs that stem from poor quality. Maintenance takes longer, and that stifles innovation. Toilsome work leads to burnout, which leads to attrition. That, in turn, leads to lost organizational knowledge, which exacerbates maintenance, onboarding, and innovation. So it’s no surprise that one of the few things that business people, managers, and software engineers agree on is that quality is of critical importance. Curiously, when it comes time to take the actual steps to build quality in, it’s often the first thing to go. It often becomes a choice between delivery “on time” or quality. The irony here is that, like so many aspects of software, focus on one concern is often counter-productive and ends up being harmful to our original intent. In this case, the habit of prioritizing delivery over quality usually leads to longer and longer delivery times. So how might we change the trajectory of software organizations struggling with this problem? This behaviour isn’t something that can be talked-away or an issue that will magically disappear once some fancy new technology is in place. Cultures that generate technical debt generally need to change their approach on some fundamental level. In this article, we’ll examine one of the most typical pitfalls around software quality and look at ways to resolve the issues that arise from it. The Early Velocity Trap It feels great when you’re working on new features. Every sprint, you’re wowing your stakeholders by showing off snazzy new functionality (this is especially prevalent at the beginning of a project when everything is ). Everyone is happy and the best of friends because there’s a clear feeling of progress and innovation, and it’s . Your team is developing with this incredible velocity for weeks or even months — you’re bonafide heroes. greenfield fun Unfortunately, there’s a problem lurking under the surface that entire time. It is the most insidious problem in software. Developers don’t notice it because it’s hard to see that things get a little slower every week. Stakeholders don’t notice it because it makes sense that delivery plateaus. After all, now the team is working on the “hard stuff.” Where this begins to hit home is the development workflow. Builds that took seconds now take minutes. Unit tests (if you have them) take minutes to run, and forget about those integration tests — now they’re up to more than an hour! Code coverage drops, dependency versions are out of date, SonarQube issues seem to be breeding like jack-rabbits, and architectural changes that we’ve been putting off now seem like significant undertakings (8 points ). at least In response, the team agrees to throw a “technical debt user story” into their backlog and to “get to it as soon as we have time.” Or even worse, the team says, “we’ll get to it later,” and proceeds to forget about it. Deferring the problem is the . technical debt trap https://knowyourmeme.com/memes/its-a-trap Before we explore a solution, let’s understand the consequences of simply not addressing tech debt. This approach is an option that many people try to rationalize. Examples: “This change isn’t going to live past three months, so we don’t need unit tests.” “There’s a new major version that’s coming out later this year, and we’ll have to do this again then. Do we want to do this twice?” “Nobody is going to reuse this” “The Customer isn’t willing to pay for — they want ” quality features! If left long enough, the decision to ignore tech debt inevitably leads to one place: . That could mean many things, such as the end of the team, cancellation of the product, putting it into maintenance mode, divestiture, or even the company's failure. the end of the product Any ignored technical debt starts a that leaves teams struggling to stay afloat as they swim in a slowly increasing pool of defects. Eventually, forward progress halts because defects have grown beyond the ability of the team to fix anything. As a result, life becomes misery because the brutal workflows are laborious for developers to work in, and stakeholders eventually get impatient and demand changes. These conditions can lead to rushed features where changes get rammed through, resulting in even more misery. downward spiral To make matters worse, as DevOps practices have gained traction, elite performers have widened the gap between competitors slower to the game. In the old days, the downward spiral was a slow one — teams could make significant progress for months or even years with minimal effort put towards quality. Nowadays, that downward spiral happens a lot faster if you make the mistake of accelerating delivery (say, with a Continuous Delivery pipeline) without having quality-promoting practices in place. Solution: The Three Ways of DevOps If any of this sounds familiar, please know that it doesn’t have to be like this at all. Software organizations can achieve massive gains in velocity by adopting DevOps practices. Teams and organizations can follow a similar journey to those chronicled in DevOps lore like (shameless plug: see ) and and described in much greater detail from tactical ( ) and strategic ( ) perspectives. There aren’t many reasons not to investigate at this point, so check those sources out. If you’re curious about a handy set of principles for approaching DevOps, learn about (another shameless plug: head on over to my article . The Phoenix Project my book summary The Unicorn Project , The DevOps Handbook Accelerate The Three Ways Applying the Three Ways of DevOps to Accelerate Your Organization ) Additionally, this offers even broader approaches. DZone article Solution: Dedicate Regular Time to Technical Debt Cleanup Technical debt is best dealt with by the people closest to the code: the developers. Often this work is treated the same as some feature that you can get away with prioritizing later, secretly hoping it slips out of the bottom of your backlog into oblivion. Tech debt is different —it’s something that your team has to build habits around. I suggest starting with 10% to 20% of developer time. That translates to 1/2 day to 1 day per week. There are exceptions, of course. For example, you may need to plan bigger chunks of work, like implementing a new library, refactoring a large part of your system, or extracting part of your codebase into microservices. However, to be in a position to entertain thoughts of that sort of technical debt, you’ll need to ensure that all of the little things taken care of: Dependencies should be up to date and relatively easy to upgrade. Your tests should be up to date, and you should have decent coverage on your unit tests. If you don’t have some level of acceptance testing in place, you’re probably opening the door to regressions, which will suck up more of your time. So automate aggressively, or plan to test manually. A Side-Note on Refactoring Some teams confuse with . is when you restructure your code (either production or test code) to address some non-functional requirement (e.g., readability) without changing the behaviour. That seems relatively straightforward. The subtlety that needs some attention is that substantially changing your implementation without the backing of solid automated tests isn’t really in the spirit of refactoring. You might as well call it what it is: a rewrite. If you engage in a rewrite, it’s an excellent idea to make sure you do so and put in the missing automated tests. rewriting refactoring Refactoring Conclusion As teaches us, it’s not so easy to know that things are heading downhill when you’re in the thick of development. Don’t allow yourself or your team to become victims of false confidence. The boost you get from the feeling of early progress is excellent, but it can come at a price if you want to avoid the crushing lows that result if you ignore technical debt. Healthy skepticism mixed with curiosity is a vital outlook to develop. hindsight bias With the accelerated pace of DevOps workflows that are quickly becoming the norm, these skills are even more critical. Not just individual developers and teams, but entire software organizations. We must avoid burnout at all costs to prevent a downward spiral from starting. The bright side is that there is an abundance of knowledge around the practices, philosophies, tools, and research easily accessible. At this point, it’s a matter of professional responsibility to at least become familiar with it. Check out the material in the links above and engage people in your organization. Try different things and pay attention to what thought leaders and look for advice in the stories coming out of organizations finding success in their digital transformations. Best of luck in your journey! Disclaimer I’m an employee of IBM. The views expressed in this blog are mine alone. They don’t necessarily reflect the positions, strategies, or opinions of the company.

The Early Velocity Trap

In this article, you’ll learn what velocity means in the context of an agile/scrum methodology and how you can improve it to allow your team to move faster and ship more stuff. Speed is a crucial ingredient to all companies, especially startups. The defining characteristic of startups that end up making it against the odds, is their ability to move fast. So what does speed mean for engineering teams? Velocity. In this article, you’ll learn what velocity means in the context of an agile/scrum methodology and how you can actually improve it to allow your team to move faster and ultimately ship more stuff. What does velocity mean in agile? Velocity is a metric that tracks how much work your team was successfully able to complete in their sprint. This is normally done by adding up all the effort estimates to see how many of these were completed in that time period. As velocity is based on your effort estimates, it requires these to be accurate (it generally takes around 4-5 sprints to find your average). According to , Martin Fowler A typical approach is to average the velocity the past three time periods to determine velocity for future time periods. How do you improve velocity? 1. Maintain a laser focus If your team is faced with new tasks and distractions once the sprint has already begun, your velocity is guaranteed to suffer. That’s why it’s so important to clearly define the tasks and prioritize them before you begin your sprint. Be consistent when it comes to accepting or rejecting changes from the rest of the company, everyone should be aware of the deadline for submitting ideas and features to the engineering team. 2. Fix your technical debt is the silent velocity killer. Technical debt Developers are constantly under pressure to deliver features faster (hell, that’s probably why you’re reading this article). We all know that this pressure results in shortcuts and assumptions, which are probably necessary at the time. However, it’s easy to forget these concessions and if they’re not dealt with, they turn into technical debt that will weigh your team down. To optimize for velocity, you need to ensure that your codebase is well maintained. For smaller pieces of tech debt, engineers should follow the , for medium to large pieces of debt you could consider using a technical debt management tool. boy scout rule ‍ 3. Always do retrospectives Retrospectives (or retros) are a key part of the agile methodology. It allows the team to identify what went right or wrong in the sprint and how to improve for next time. As mentions, Maruti Techlabs The most important benefit is that it cuts through hierarchy and gives equal power to the team members to open up and present their views effectively. Ensure that these retros happen in a trusted environment, without blame, so you get maximum transparency. The meetings will require time and participation (developer kryptonite combo), but it’s a tried and tested practice that will lead to extremely valuable insights and tweaks that will ultimately speed up your velocity. 4. Boost team morale A happy team is a productive team. Make sure the team is rallied around a common goal and that they have clear ways of expressing feedback if they’re not happy (like the aforementioned retros). The work that is done should also feel satisfying, try to bridge the gap between the business side of the company and the engineering team, by, for example, showing how many users started to use the feature that was built in the last sprint ( is a great tool for visualizing this). Hotjar Don't forget to cheer for the maintenance and tech debt heroes: the people who refactored this nasty function, fixed that bug, reviewed these pull requests, and ultimately saved the team hours of work by keeping the codebase healthy. Key takeaway So there you have it, 4 ways to improve your team’s velocity. It’s important to remember that your velocity cannot be constantly increased (you don’t want to end up with inflated estimates). Instead, try to evaluate it periodically and make the changes that you feel will have the greatest impact on the team. Previously published at https://www.stepsize.com/blog/the-engineers-complete-guide-to-improving-velocity

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velocitymsc.com

751 employees

Since 2005

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Velocity

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